osf.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "初始化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import polars as pl\n",
    "from polars import col\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 如何选出指定日期的数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "构造数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "dates\n",
       "</th>\n",
       "<th>\n",
       "values\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"2016-07-02\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"2016-08-10\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"2016-08-31\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"2016-09-10\"\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (4, 2)\n",
       "┌────────────┬────────┐\n",
       "│ dates      ┆ values │\n",
       "│ ---        ┆ ---    │\n",
       "│ str        ┆ i64    │\n",
       "╞════════════╪════════╡\n",
       "│ 2016-07-02 ┆ 1      │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2016-08-10 ┆ 2      │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2016-08-31 ┆ 3      │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2016-09-10 ┆ 4      │\n",
       "└────────────┴────────┘"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\n",
    "    \"dates\": [\"2016-07-02\", \"2016-08-10\",  \"2016-08-31\", \"2016-09-10\"],\n",
    "    \"values\": [1, 2, 3, 4]\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "eager模式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "dates\n",
       "</th>\n",
       "<th>\n",
       "values\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "date\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "2016-08-10\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2016-08-31\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 2)\n",
       "┌────────────┬────────┐\n",
       "│ dates      ┆ values │\n",
       "│ ---        ┆ ---    │\n",
       "│ date       ┆ i64    │\n",
       "╞════════════╪════════╡\n",
       "│ 2016-08-10 ┆ 2      │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2016-08-31 ┆ 3      │\n",
       "└────────────┴────────┘"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# eager\n",
    "# step1 :通过with_column对列进行变换\n",
    "# step2 :使用filter进行条件筛选\n",
    "(df.with_column(pl.col(\"dates\").str.strptime(pl.Date)) \n",
    " .filter(\n",
    "     col(\"dates\").is_between(datetime(2016, 8, 9), datetime(2016, 9, 1))\n",
    "     )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "或者用lazy模式"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 按另一列的值是否满足条件来对新增一列并赋值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "\"d\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "\"e\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 2)\n",
       "┌─────┬─────┐\n",
       "│ a   ┆ b   │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ str │\n",
       "╞═════╪═════╡\n",
       "│ 1   ┆ a   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ b   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ c   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ d   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 5   ┆ e   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\n",
    "    \"a\": [1, 2, 3, 4, 5],\n",
    "    \"b\": list(\"abcde\")\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "new\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "\"d\"\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "\"e\"\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 3)\n",
       "┌─────┬─────┬─────┐\n",
       "│ a   ┆ b   ┆ new │\n",
       "│ --- ┆ --- ┆ --- │\n",
       "│ i64 ┆ str ┆ i64 │\n",
       "╞═════╪═════╪═════╡\n",
       "│ 1   ┆ a   ┆ 1   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ b   ┆ 2   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ c   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ d   ┆ 10  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 5   ┆ e   ┆ 10  │\n",
       "└─────┴─────┴─────┘"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.with_column(\n",
    "    pl.when(pl.col(\"a\") > 3).then(\n",
    "        10\n",
    "    ).otherwise(\n",
    "        pl.col(\"a\")\n",
    "    ).alias(\"new\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 缺失值判断(is_null)填补：用另一列，用均值等形式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (10, 2)\n",
       "┌──────┬─────┐\n",
       "│ a    ┆ b   │\n",
       "│ ---  ┆ --- │\n",
       "│ i64  ┆ i64 │\n",
       "╞══════╪═════╡\n",
       "│ 0    ┆ 0   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1    ┆ 1   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2    ┆ 2   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3    ┆ 3   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ ...  ┆ ... │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 6    ┆ 6   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ null ┆ 7   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 8    ┆ 8   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ null ┆ 9   │\n",
       "└──────┴─────┘"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import polars as pl\n",
    "# from polars import col\n",
    "\n",
    "df = pl.DataFrame({\n",
    "    \"a\": [0, 1, 2, 3, None, 5, 6, None, 8, None],\n",
    "    \"b\": range(10),\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "a_filled_lag\n",
       "</th>\n",
       "<th>\n",
       "a_filled_mean\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "0.0\n",
       "</td>\n",
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       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "2.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "3.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "4.5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "5.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "6.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "4.5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "8.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "4.5\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (10, 4)\n",
       "┌─────┬─────┬──────────────┬───────────────┐\n",
       "│ a   ┆ b   ┆ a_filled_lag ┆ a_filled_mean │\n",
       "│ --- ┆ --- ┆ ---          ┆ ---           │\n",
       "│ i64 ┆ i64 ┆ i64          ┆ f64           │\n",
       "╞═════╪═════╪══════════════╪═══════════════╡\n",
       "│ 0   ┆ 0   ┆ 0            ┆ 0.0           │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 1   ┆ 1   ┆ 1            ┆ 1.0           │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2   ┆ 2   ┆ 2            ┆ 2.0           │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3   ┆ 3   ┆ 3            ┆ 3.0           │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ... ┆ ... ┆ ...          ┆ ...           │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 6   ┆ 6   ┆ 6            ┆ 6.0           │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 7   ┆ 7   ┆ 6            ┆ 4.5           │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 8   ┆ 8   ┆ 8            ┆ 8.0           │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 9   ┆ 9   ┆ 8            ┆ 4.5           │\n",
       "└─────┴─────┴──────────────┴───────────────┘"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df.with_columns([\n",
    "    \n",
    "    # 如果a为、null，则用对应行的 b 值进行填充\n",
    "    pl.when(col(\"a\").is_null()).then(\n",
    "        col(\"b\")).otherwise(\n",
    "            col(\"a\")).alias(\"a\"),\n",
    "    \n",
    "    # 如果a为、null，则用对应行的上一行的 b 值进行填充\n",
    "    # 且生成新的列，而不是在原列上填充\n",
    "    pl.when(col(\"a\").is_null()).then(\n",
    "        col(\"b\").shift(1)).otherwise(\n",
    "            col(\"a\")).alias(\"a_filled_lag\"),\n",
    "    \n",
    "    # 均值填充\n",
    "    pl.when(col(\"a\").is_null()).then(\n",
    "        col(\"b\").mean()).otherwise(\n",
    "            col(\"a\")).alias(\"a_filled_mean\")\n",
    "\n",
    "])\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 列的描述性统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "describe\n",
       "</th>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "c\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"mean\"\n",
       "</td>\n",
       "<td>\n",
       "2.266667\n",
       "</td>\n",
       "<td>\n",
       "5.0\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"std\"\n",
       "</td>\n",
       "<td>\n",
       "1.101514\n",
       "</td>\n",
       "<td>\n",
       "1.0\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"min\"\n",
       "</td>\n",
       "<td>\n",
       "1.0\n",
       "</td>\n",
       "<td>\n",
       "4.0\n",
       "</td>\n",
       "<td>\n",
       "0.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"max\"\n",
       "</td>\n",
       "<td>\n",
       "3.0\n",
       "</td>\n",
       "<td>\n",
       "6.0\n",
       "</td>\n",
       "<td>\n",
       "1.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"median\"\n",
       "</td>\n",
       "<td>\n",
       "2.8\n",
       "</td>\n",
       "<td>\n",
       "5.0\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 4)\n",
       "┌──────────┬──────────┬─────┬──────┐\n",
       "│ describe ┆ a        ┆ b   ┆ c    │\n",
       "│ ---      ┆ ---      ┆ --- ┆ ---  │\n",
       "│ str      ┆ f64      ┆ f64 ┆ f64  │\n",
       "╞══════════╪══════════╪═════╪══════╡\n",
       "│ mean     ┆ 2.266667 ┆ 5.0 ┆ null │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ std      ┆ 1.101514 ┆ 1.0 ┆ null │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ min      ┆ 1.0      ┆ 4.0 ┆ 0.0  │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ max      ┆ 3.0      ┆ 6.0 ┆ 1.0  │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ median   ┆ 2.8      ┆ 5.0 ┆ null │\n",
       "└──────────┴──────────┴─────┴──────┘"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\n",
    "    'a': [1.0, 2.8, 3.0],\n",
    "    'b': [4, 5, 6],\n",
    "    \"c\": [True, False, True]\n",
    "    })\n",
    "df.describe()\n",
    "# df.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 选取最小值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "c\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 3)\n",
       "┌─────┬─────┬─────┐\n",
       "│ a   ┆ b   ┆ c   │\n",
       "│ --- ┆ --- ┆ --- │\n",
       "│ i64 ┆ i64 ┆ i64 │\n",
       "╞═════╪═════╪═════╡\n",
       "│ 1   ┆ 5   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 1   ┆ 2   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ 4   ┆ 5   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 5   ┆ 2   ┆ 7   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ 5   ┆ 2   │\n",
       "└─────┴─────┴─────┘"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import polars as pl\n",
    "\n",
    "df = pl.DataFrame({\n",
    "    \"a\": [1,4,2,5,2],\n",
    "    \"b\": [5,1,4,2,5],\n",
    "    \"c\": [3,2,5,7,2]\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "shape: (5,)\n",
       "Series: 'a' [i64]\n",
       "[\n",
       "\t1\n",
       "\t1\n",
       "\t2\n",
       "\t2\n",
       "\t2\n",
       "]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.min(axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "返回pl.DF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "min\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
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       "</tr>\n",
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       "1\n",
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       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
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       "<td>\n",
       "2\n",
       "</td>\n",
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       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 1)\n",
       "┌─────┐\n",
       "│ min │\n",
       "│ --- │\n",
       "│ i64 │\n",
       "╞═════╡\n",
       "│ 1   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 1   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2   │\n",
       "└─────┘"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(\n",
    "    df.min(axis=1).alias('min')\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "或者"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "min\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
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       "2\n",
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       "2\n",
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       "2\n",
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       "</div>"
      ],
      "text/plain": [
       "shape: (5, 1)\n",
       "┌─────┐\n",
       "│ min │\n",
       "│ --- │\n",
       "│ i64 │\n",
       "╞═════╡\n",
       "│ 1   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 1   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2   │\n",
       "└─────┘"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(\n",
    "    pl.min([\"a\", \"b\", \"c\"]) \n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "或者\n",
    "https://stackoverflow.com/questions/69888178/calculating-rowwise-minimum-of-two-series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "literal\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
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       "2\n",
       "</td>\n",
       "</tr>\n",
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       "</div>"
      ],
      "text/plain": [
       "shape: (5, 1)\n",
       "┌─────────┐\n",
       "│ literal │\n",
       "│ ---     │\n",
       "│ i64     │\n",
       "╞═════════╡\n",
       "│ 1       │\n",
       "├╌╌╌╌╌╌╌╌╌┤\n",
       "│ 1       │\n",
       "├╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2       │\n",
       "├╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2       │\n",
       "├╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2       │\n",
       "└─────────┘"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(\n",
    "    pl.fold(int(1e9), \n",
    "            lambda acc, a: pl.when(acc > a).then(a).otherwise(acc), [\"a\", \"b\", \"c\"]\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 取出一个Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pl.DataFrame({\n",
    "    \"A\": [1, 2, 3],\n",
    "    \"B\": [1, 2, 3]\n",
    "})\n",
    "\n",
    "assert isinstance(df[\"A\"], pl.Series)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 生成各种形式的滞后项"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
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       "<tr>\n",
       "<td>\n",
       "i64\n",
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       "1\n",
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       "2\n",
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      "text/plain": [
       "shape: (5, 2)\n",
       "┌─────┬─────┐\n",
       "│ a   ┆ b   │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ i64 │\n",
       "╞═════╪═════╡\n",
       "│ 1   ┆ 5   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ 4   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 2   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 5   ┆ 1   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# some initial dataframe\n",
    "df = pl.DataFrame({\n",
    "    \"a\": [1, 2, 3, 4, 5],\n",
    "    \"b\": [5, 4, 3, 2, 1]\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a_lag_1\n",
       "</th>\n",
       "<th>\n",
       "b_lag_0\n",
       "</th>\n",
       "<th>\n",
       "b_lag_1\n",
       "</th>\n",
       "<th>\n",
       "b_lag_2\n",
       "</th>\n",
       "<th>\n",
       "b_lag_3\n",
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       "<th>\n",
       "b_lag_4\n",
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       "i64\n",
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       "i64\n",
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       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
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       "3\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 6)\n",
       "┌─────────┬─────────┬─────────┬─────────┬─────────┬─────────┐\n",
       "│ a_lag_1 ┆ b_lag_0 ┆ b_lag_1 ┆ b_lag_2 ┆ b_lag_3 ┆ b_lag_4 │\n",
       "│ ---     ┆ ---     ┆ ---     ┆ ---     ┆ ---     ┆ ---     │\n",
       "│ i64     ┆ i64     ┆ i64     ┆ i64     ┆ i64     ┆ i64     │\n",
       "╞═════════╪═════════╪═════════╪═════════╪═════════╪═════════╡\n",
       "│ null    ┆ 5       ┆ null    ┆ null    ┆ null    ┆ null    │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 1       ┆ 4       ┆ 5       ┆ null    ┆ null    ┆ null    │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2       ┆ 3       ┆ 4       ┆ 5       ┆ null    ┆ null    │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3       ┆ 2       ┆ 3       ┆ 4       ┆ 5       ┆ null    │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 4       ┆ 1       ┆ 2       ┆ 3       ┆ 4       ┆ 5       │\n",
       "└─────────┴─────────┴─────────┴─────────┴─────────┴─────────┘"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# a function that returns a lazy evaluated expression\n",
    "def lag(name: str, n: int) -> pl.Expr:\n",
    "    return pl.col(name).shift(n).suffix(f\"_lag_{n}\")\n",
    "\n",
    "# a lazy evaluated expression assigned to a variable\n",
    "lag_foo = lag(\"a\", 1)\n",
    "\n",
    "out = df.select(\n",
    "    [lag_foo,] +\n",
    "    [lag(\"b\", i) for i in range(5)]  # create exprs with a list comprehension\n",
    ")\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 统计出现的频率并重复这个频率到每个值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "md5\n",
       "</th>\n",
       "<th>\n",
       "row_count\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (6, 2)\n",
       "┌─────┬───────────┐\n",
       "│ md5 ┆ row_count │\n",
       "│ --- ┆ ---       │\n",
       "│ str ┆ u32       │\n",
       "╞═════╪═══════════╡\n",
       "│ a   ┆ 3         │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ a   ┆ 3         │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ b   ┆ 1         │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ c   ┆ 2         │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ c   ┆ 2         │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ a   ┆ 3         │\n",
       "└─────┴───────────┘"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import polars as pl\n",
    "\n",
    "df = pl.DataFrame({\"md5\": [\"a\", \"a\", \"b\",\"c\",\"c\",\"a\"]})\n",
    "out_df = df.select([\n",
    "    pl.col(\"*\"),\n",
    "    pl.col(\"md5\").count().over(\"md5\").alias(\"row_count\"),\n",
    "])\n",
    "\n",
    "out_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "比如我们新增一列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "<th>\n",
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       "<th>\n",
       "weighted\n",
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       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
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       "<tbody>\n",
       "<tr>\n",
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       "123\n",
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       "<td>\n",
       "3\n",
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       "<td>\n",
       "369\n",
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       "<td>\n",
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       "<tr>\n",
       "<td>\n",
       "333\n",
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       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "333\n",
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       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "666\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "1332\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "666\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "1332\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "123\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "369\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (6, 3)\n",
       "┌─────┬───────────┬──────────┐\n",
       "│ md5 ┆ row_count ┆ weighted │\n",
       "│ --- ┆ ---       ┆ ---      │\n",
       "│ i64 ┆ u32       ┆ i64      │\n",
       "╞═════╪═══════════╪══════════╡\n",
       "│ 123 ┆ 3         ┆ 369      │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 123 ┆ 3         ┆ 369      │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 333 ┆ 1         ┆ 333      │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 666 ┆ 2         ┆ 1332     │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 666 ┆ 2         ┆ 1332     │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 123 ┆ 3         ┆ 369      │\n",
       "└─────┴───────────┴──────────┘"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import polars as pl\n",
    "\n",
    "df = pl.DataFrame({\"md5\": [123, 123, 333,666,666,123]})\n",
    "out_df = df.select([\n",
    "    pl.col(\"*\"),\n",
    "    pl.col(\"md5\").count().over(\"md5\").alias(\"row_count\"),\n",
    "]).with_column(\n",
    "    # 出现的频数越高，对其按权重扩大\n",
    "    (pl.col(\"md5\") * pl.col(\"row_count\")).alias(\"weighted\")\n",
    ")\n",
    "\n",
    "out_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "md5\n",
       "</th>\n",
       "<th>\n",
       "count\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 2)\n",
       "┌─────┬───────┐\n",
       "│ md5 ┆ count │\n",
       "│ --- ┆ ---   │\n",
       "│ str ┆ u32   │\n",
       "╞═════╪═══════╡\n",
       "│ a   ┆ 3     │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ c   ┆ 2     │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ b   ┆ 1     │\n",
       "└─────┴───────┘"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\"md5\": [\"a\", \"a\", \"b\",\"c\",\"c\",\"a\"]})\n",
    "out_df = df.groupby(\n",
    "    \"md5\"\n",
    ").count()\n",
    "out_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 判断某列包含某个字符串的那些行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"hello\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"world\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"everyone\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 2)\n",
       "┌─────┬──────────┐\n",
       "│ a   ┆ b        │\n",
       "│ --- ┆ ---      │\n",
       "│ i64 ┆ str      │\n",
       "╞═════╪══════════╡\n",
       "│ 1   ┆ hello    │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2   ┆ world    │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3   ┆ everyone │\n",
       "└─────┴──────────┘"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import polars as pl\n",
    "\n",
    "df = pl.DataFrame({\"a\": [1, 2, 3], \"b\": [\"hello\", \"world\", \"everyone\"]})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "shape: (3,)\n",
       "Series: 'a' [bool]\n",
       "[\n",
       "\tfalse\n",
       "\tfalse\n",
       "\tfalse\n",
       "]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search = \"hello\"\n",
    "\n",
    "df[\"b\"].str.contains(search)  # this works\n",
    "\n",
    "# df[\"a\"].str.contains(search)  # 因为a is not of type Utf8\n",
    "df[\"a\"].cast(pl.Utf8).str.contains(search)  # this works"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### arr属性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "my_column\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "list\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "[1, 2, 3]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[1, 2, 3]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[1, 2, 3]\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 1)\n",
       "┌────────────┐\n",
       "│ my_column  │\n",
       "│ ---        │\n",
       "│ list [i64] │\n",
       "╞════════════╡\n",
       "│ [1, 2, 3]  │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [1, 2, 3]  │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [1, 2, 3]  │\n",
       "└────────────┘"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\"my_column\": [[1,2,3],[1,2,3],[1,2,3]]})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "my_column\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "list\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "[1, 2, ... 5]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[1, 2, ... 5]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[1, 2, ... 5]\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 1)\n",
       "┌───────────────┐\n",
       "│ my_column     │\n",
       "│ ---           │\n",
       "│ list [i64]    │\n",
       "╞═══════════════╡\n",
       "│ [1, 2, ... 5] │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [1, 2, ... 5] │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [1, 2, ... 5] │\n",
       "└───────────────┘"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.with_column(pl.col(\"my_column\").arr.concat([4, 5]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 与pandas中的merge对应"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "```python\n",
    "# pandas \n",
    "# CPU times: user 1.64 s, sys: 867 ms, total: 2.5 s\n",
    "# Wall time: 2.52 s\n",
    "df1.merge(df2, left_on=\"a\", right_on=\"b\")\n",
    "\n",
    "# polars\n",
    "# CPU times: user 5.59 s, sys: 199 ms, total: 5.79 s\n",
    "# Wall time: 780 ms\n",
    "df1p.join(df2p, left_on=\"a\", right_on=\"b\")\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 类似于pandas中的transform函数是over\n",
    "#### 新增一列，内容为每个组，组内的序号，使用cumcount函数\n",
    "\n",
    "Get an array with the cumulative count computed at every element.   \n",
    "Counting from 0 to len"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "date\n",
       "</th>\n",
       "<th>\n",
       "code\n",
       "</th>\n",
       "<th>\n",
       "price\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day3\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day4\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day3\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (9, 3)\n",
       "┌──────┬──────┬───────┐\n",
       "│ date ┆ code ┆ price │\n",
       "│ ---  ┆ ---  ┆ ---   │\n",
       "│ str  ┆ str  ┆ i64   │\n",
       "╞══════╪══════╪═══════╡\n",
       "│ day1 ┆ a    ┆ 1     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ a    ┆ 2     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ day3 ┆ a    ┆ 3     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ day4 ┆ a    ┆ 4     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ ...  ┆ ...  ┆ ...   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ b    ┆ 6     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ day3 ┆ b    ┆ 7     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ day1 ┆ c    ┆ 8     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ c    ┆ 9     │\n",
       "└──────┴──────┴───────┘"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "day = ['day1','day2','day3','day4','day1','day2','day3','day1','day2']\n",
    "code = [\"a\",\"a\",\"a\",\"a\",\"b\",\"b\",\"b\",\"c\",\"c\"]\n",
    "price = [1,2,3,4,5,6,7,8,9]\n",
    "df = pl.DataFrame({\"date\":day,\"code\":code,\"price\":price})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "date\n",
       "</th>\n",
       "<th>\n",
       "code\n",
       "</th>\n",
       "<th>\n",
       "price\n",
       "</th>\n",
       "<th>\n",
       "codeindex\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day3\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day4\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day3\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (9, 4)\n",
       "┌──────┬──────┬───────┬───────────┐\n",
       "│ date ┆ code ┆ price ┆ codeindex │\n",
       "│ ---  ┆ ---  ┆ ---   ┆ ---       │\n",
       "│ str  ┆ str  ┆ i64   ┆ u32       │\n",
       "╞══════╪══════╪═══════╪═══════════╡\n",
       "│ day1 ┆ a    ┆ 1     ┆ 0         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ a    ┆ 2     ┆ 1         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day3 ┆ a    ┆ 3     ┆ 2         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day4 ┆ a    ┆ 4     ┆ 3         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ...  ┆ ...  ┆ ...   ┆ ...       │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ b    ┆ 6     ┆ 1         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day3 ┆ b    ┆ 7     ┆ 2         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day1 ┆ c    ┆ 8     ┆ 0         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ c    ┆ 9     ┆ 1         │\n",
       "└──────┴──────┴───────┴───────────┘"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.select([\n",
    "    pl.all(),\n",
    "    # 即按code分组\n",
    "    # 然后通过pl.col(\"date\").cumcount()为每组生成序号\n",
    "    pl.col(\"date\").cumcount().over(\"code\").alias(\"codeindex\"),\n",
    "]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "其实把date换做code也是可以的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "date\n",
       "</th>\n",
       "<th>\n",
       "code\n",
       "</th>\n",
       "<th>\n",
       "price\n",
       "</th>\n",
       "<th>\n",
       "codeindex\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day3\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day4\"\n",
       "</td>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day3\"\n",
       "</td>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day1\"\n",
       "</td>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"day2\"\n",
       "</td>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (9, 4)\n",
       "┌──────┬──────┬───────┬───────────┐\n",
       "│ date ┆ code ┆ price ┆ codeindex │\n",
       "│ ---  ┆ ---  ┆ ---   ┆ ---       │\n",
       "│ str  ┆ str  ┆ i64   ┆ u32       │\n",
       "╞══════╪══════╪═══════╪═══════════╡\n",
       "│ day1 ┆ a    ┆ 1     ┆ 0         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ a    ┆ 2     ┆ 1         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day3 ┆ a    ┆ 3     ┆ 2         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day4 ┆ a    ┆ 4     ┆ 3         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ...  ┆ ...  ┆ ...   ┆ ...       │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ b    ┆ 6     ┆ 1         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day3 ┆ b    ┆ 7     ┆ 2         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day1 ┆ c    ┆ 8     ┆ 0         │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ day2 ┆ c    ┆ 9     ┆ 1         │\n",
       "└──────┴──────┴───────┴───────────┘"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.select([\n",
    "    pl.all(),\n",
    "    pl.col(\"code\").cumcount().over(\"code\").alias(\"codeindex\"),\n",
    "]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 判断两个pl.DF是否相同"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import polars as pl\n",
    "pl.DataFrame({\"x\": [1,2,3]}).frame_equal(\n",
    "    pl.DataFrame({\"x\": [1,2,3]}))  # True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 拆分并统计句子中的词频"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "idx\n",
       "</th>\n",
       "<th>\n",
       "lines\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "\"                            Would never order again.\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"   I'm not sure it gives me any type of glow and ...\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"   Goes on smoothly a bit sticky and color is clo...\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"       Preferisco altri prodotti della stessa marca.\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "\"        The moisturizing advertised is non-existent.\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 2)\n",
       "┌─────┬─────────────────────────────────────┐\n",
       "│ idx ┆ lines                               │\n",
       "│ --- ┆ ---                                 │\n",
       "│ i64 ┆ str                                 │\n",
       "╞═════╪═════════════════════════════════════╡\n",
       "│ 0   ┆                             Woul... │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 1   ┆    I'm not sure it gives me any ... │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2   ┆    Goes on smoothly a bit sticky... │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3   ┆        Preferisco altri prodotti... │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 4   ┆         The moisturizing adverti... │\n",
       "└─────┴─────────────────────────────────────┘"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv = \"\"\"\n",
    "0,                            Would never order again.\n",
    "1,   I'm not sure it gives me any type of glow and ...\n",
    "2,   Goes on smoothly a bit sticky and color is clo...\n",
    "3,       Preferisco altri prodotti della stessa marca.\n",
    "4,        The moisturizing advertised is non-existent.\n",
    "\"\"\".encode()\n",
    "\n",
    "df = pl.read_csv(csv, has_header=False, new_columns=[\"idx\", \"lines\"])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "lines\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "list\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "[\"\", \"\", ... \"again.\"]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[\"\", \"\", ... \"...\"]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[\"\", \"\", ... \"clo...\"]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[\"\", \"\", ... \"marca.\"]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[\"\", \"\", ... \"non-existent.\"]\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 1)\n",
       "┌───────────────────────────────┐\n",
       "│ lines                         │\n",
       "│ ---                           │\n",
       "│ list [str]                    │\n",
       "╞═══════════════════════════════╡\n",
       "│ [\"\", \"\", ... \"again.\"]        │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [\"\", \"\", ... \"...\"]           │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [\"\", \"\", ... \"clo...\"]        │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [\"\", \"\", ... \"marca.\"]        │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [\"\", \"\", ... \"non-existent.\"] │\n",
       "└───────────────────────────────┘"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(pl.col(\"lines\").str.split(\" \"))\n",
    "# 注意，str.split(\" \")中还包含了空格的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "<td>\n",
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       "\"moisturizing\"\n",
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       "\"advertised\"\n",
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       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"is\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"non-existent.\"\n",
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       "shape: (86, 1)\n",
       "┌───────────────┐\n",
       "│ lines         │\n",
       "│ ---           │\n",
       "│ str           │\n",
       "╞═══════════════╡\n",
       "│               │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│               │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│               │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│               │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ...           │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ moisturizing  │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ advertised    │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ is            │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ non-existent. │\n",
       "└───────────────┘"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select( pl.col(\"lines\").str.split(\" \").flatten() )\n",
    "# 拉平"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "1\n",
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       "\"non-existent.\"\n",
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       "...\n",
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       "\"me\"\n",
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       "1\n",
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       "<tr>\n",
       "<td>\n",
       "\"prodotti\"\n",
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       "<td>\n",
       "1\n",
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       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"della\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
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       "<tr>\n",
       "<td>\n",
       "\"Would\"\n",
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       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Preferisco\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"on\"\n",
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       "<td>\n",
       "1\n",
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       "<td>\n",
       "\"of\"\n",
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       "1\n",
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       "<td>\n",
       "\"...\"\n",
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       "shape: (35, 2)\n",
       "┌────────────┬───────┐\n",
       "│ words      ┆ count │\n",
       "│ ---        ┆ ---   │\n",
       "│ str        ┆ u32   │\n",
       "╞════════════╪═══════╡\n",
       "│ is         ┆ 2     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ and        ┆ 2     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ sticky     ┆ 1     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ Goes       ┆ 1     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ ...        ┆ ...   │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ Preferisco ┆ 1     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ on         ┆ 1     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ of         ┆ 1     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ ...        ┆ 1     │\n",
       "└────────────┴───────┘"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "(\n",
    "    df.select( pl.col(\"lines\").str.split(\" \").flatten().alias(\"words\"))\n",
    "    .groupby(\"words\").agg(pl.count())\n",
    "    .sort(\"count\", reverse=True)\n",
    "    .filter(pl.col(\"words\").str.lengths() > 0)  \n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 先分组，如等于组内最值，则取出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
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       "</th>\n",
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       "y\n",
       "</th>\n",
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       "i64\n",
       "</td>\n",
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       "i64\n",
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       "shape: (4, 2)\n",
       "┌─────┬─────┐\n",
       "│ x   ┆ y   │\n",
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       "│ i64 ┆ i64 │\n",
       "╞═════╪═════╡\n",
       "│ 0   ┆ 1   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 0   ┆ 2   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ 3   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(dict(\n",
    "    x=[0, 0, 1, 1], \n",
    "    y=[1, 2, 3, 3])\n",
    ")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        vertical-align: top;\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "x\n",
       "</th>\n",
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       "y\n",
       "</th>\n",
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      "text/plain": [
       "shape: (3, 2)\n",
       "┌─────┬─────┐\n",
       "│ x   ┆ y   │\n",
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       "│ i64 ┆ i64 │\n",
       "╞═════╪═════╡\n",
       "│ 0   ┆ 2   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ 3   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按x分组后，y的两个组内最大值为2和3\n",
    "# 当y取这两个值的时候，选出\n",
    "df.filter(\n",
    "    (  pl.col(\"y\") == pl.max(\"y\").over(\"x\") )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 判断出否为重复值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
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       "shape: (5, 2)\n",
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       "│ a   ┆ b   │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ str │\n",
       "╞═════╪═════╡\n",
       "│ 1   ┆ x   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ y   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ z   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ x   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ s   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(\n",
    "    {\n",
    "        \"a\": [1, 2, 3, 1, 3],\n",
    "        \"b\": [\"x\", \"y\", \"z\", \"x\",\"s\"],\n",
    "    }\n",
    ")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 删除重复值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "shape: (5,)\n",
       "Series: '' [bool]\n",
       "[\n",
       "\ttrue\n",
       "\tfalse\n",
       "\tfalse\n",
       "\ttrue\n",
       "\tfalse\n",
       "]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.is_duplicated()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"x\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"y\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"z\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"s\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (4, 2)\n",
       "┌─────┬─────┐\n",
       "│ a   ┆ b   │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ str │\n",
       "╞═════╪═════╡\n",
       "│ 1   ┆ x   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ y   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ z   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ s   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.distinct(subset=[\"a\",\"b\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
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       "<td>\n",
       "str\n",
       "</td>\n",
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       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"x\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"y\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"z\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 2)\n",
       "┌─────┬─────┐\n",
       "│ a   ┆ b   │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ str │\n",
       "╞═════╪═════╡\n",
       "│ 1   ┆ x   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ y   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ z   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.distinct(subset=[\"a\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
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       "groups\n",
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       "values\n",
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       "<td>\n",
       "str\n",
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       "<td>\n",
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       "<td>\n",
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       "<td>\n",
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       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
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       "</tr>\n",
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       "<td>\n",
       "\"b\"\n",
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       "<td>\n",
       "18\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "19\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "20\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "21\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "22\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "23\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "24\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "25\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "26\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "27\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "28\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "29\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (30, 2)\n",
       "┌────────┬────────┐\n",
       "│ groups ┆ values │\n",
       "│ ---    ┆ ---    │\n",
       "│ str    ┆ i64    │\n",
       "╞════════╪════════╡\n",
       "│ a      ┆ 0      │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ a      ┆ 1      │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ a      ┆ 2      │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ a      ┆ 3      │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ ...    ┆ ...    │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ b      ┆ 26     │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ b      ┆ 27     │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ b      ┆ 28     │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ b      ┆ 29     │\n",
       "└────────┴────────┘"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\n",
    "    \"groups\": [\"a\"] * 10 + [\"b\"] * 20,\n",
    "    \"values\": range(30)\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 获取分组的前20%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以使用 head(10) 来获取 col 中的前 10 个元素。  \n",
    "但是，如果组的长度不同，我需要在每个组中获取前 20% 的元素，  \n",
    "例如 10 个元素组中的 2 个元素。  \n",
    "例如 20 个元素组中的 4 个元素。 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果我们的代码这么写，得到的结果不是我们想要的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "groups\n",
       "</th>\n",
       "<th>\n",
       "values\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "list\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "[10, 11, ... 13]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "[0, 1]\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 2)\n",
       "┌────────┬──────────────────┐\n",
       "│ groups ┆ values           │\n",
       "│ ---    ┆ ---              │\n",
       "│ str    ┆ list [i64]       │\n",
       "╞════════╪══════════════════╡\n",
       "│ b      ┆ [10, 11, ... 13] │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ a      ┆ [0, 1]           │\n",
       "└────────┴──────────────────┘"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.groupby(\"groups\")\n",
    "    .agg( pl.all().head(pl.count() * 0.2) )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "所以要explode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "groups\n",
       "</th>\n",
       "<th>\n",
       "values\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
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       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
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       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "13\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (6, 2)\n",
       "┌────────┬────────┐\n",
       "│ groups ┆ values │\n",
       "│ ---    ┆ ---    │\n",
       "│ str    ┆ i64    │\n",
       "╞════════╪════════╡\n",
       "│ b      ┆ 10     │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ b      ┆ 11     │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ b      ┆ 12     │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ b      ┆ 13     │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ a      ┆ 0      │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ a      ┆ 1      │\n",
       "└────────┴────────┘"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.groupby(\"groups\")\n",
    "    .agg( pl.all().head(pl.count() * 0.2) )\n",
    "    .explode( pl.all().exclude(\"groups\") )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "exclude(\"groups\")\n",
    "```\n",
    "其实就是这一部分不展开，但是会在values展开后被自动广播"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "那么来学一下explode函数，explode前面其实是被展开的那个列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "list\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "[1, 2, 3]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "[4, 5, 6]\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 1)\n",
       "┌────────────┐\n",
       "│ b          │\n",
       "│ ---        │\n",
       "│ list [i64] │\n",
       "╞════════════╡\n",
       "│ [1, 2, 3]  │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ [4, 5, 6]  │\n",
       "└────────────┘"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\"b\": [[1, 2, 3], [4, 5, 6]]})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (6, 1)\n",
       "┌─────┐\n",
       "│ b   │\n",
       "│ --- │\n",
       "│ i64 │\n",
       "╞═════╡\n",
       "│ 1   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 3   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 4   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 5   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 6   │\n",
       "└─────┘"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(pl.col(\"b\").explode())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 新建了列，固定值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "VERSION\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"x\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"y\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"z\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"x\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"s\"\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 3)\n",
       "┌─────┬─────┬─────────┐\n",
       "│ a   ┆ b   ┆ VERSION │\n",
       "│ --- ┆ --- ┆ ---     │\n",
       "│ i64 ┆ str ┆ i32     │\n",
       "╞═════╪═════╪═════════╡\n",
       "│ 1   ┆ x   ┆ 6       │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2   ┆ y   ┆ 6       │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3   ┆ z   ┆ 6       │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 1   ┆ x   ┆ 6       │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3   ┆ s   ┆ 6       │\n",
       "└─────┴─────┴─────────┘"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(\n",
    "    {\n",
    "        \"a\": [1, 2, 3, 1, 3],\n",
    "        \"b\": [\"x\", \"y\", \"z\", \"x\",\"s\"],\n",
    "    }\n",
    ")\n",
    "df\n",
    "df.with_column(pl.lit(6).alias('VERSION'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### pl.DF与pandas.DF的互转"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### pl.DF  to pd.DF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pl.DataFrame(\n",
    "    {\n",
    "        \"a\": [1, 2, 3, 1, 3],\n",
    "        \"b\": [\"x\", \"y\", \"z\", \"x\",\"s\"],\n",
    "    }\n",
    ")\n",
    "dfp = df.to_pandas()\n",
    "# 转为pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### pd.DF to pl.DF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type is <class 'polars.internals.frame.DataFrame'>\n"
     ]
    }
   ],
   "source": [
    "print('type is {}'.format(type(pl.DataFrame(dfp))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### pl.Series to pd.Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pds = pl.Series([1, 2, 3]).to_pandas()\n",
    "pds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### pl.Series to pd.Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "shape: (3,)\n",
       "Series: '' [i64]\n",
       "[\n",
       "\t1\n",
       "\t2\n",
       "\t3\n",
       "]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pl.Series(pds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 批量修改列名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a_c\n",
       "</th>\n",
       "<th>\n",
       "b_d\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 2)\n",
       "┌─────┬─────┐\n",
       "│ a_c ┆ b_d │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ i64 │\n",
       "╞═════╪═════╡\n",
       "│ 1   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ 4   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\n",
    "    \"a.c\": [1, 2],\n",
    "    \"b.d\": [3, 4]\n",
    "})\n",
    "df.columns = list(map(lambda x: x.replace(\".\", \"_\"), df.columns))\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 列名排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "c\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "bool\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "true\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "false\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 3)\n",
       "┌─────┬───────┬─────┐\n",
       "│ a   ┆ b     ┆ c   │\n",
       "│ --- ┆ ---   ┆ --- │\n",
       "│ str ┆ bool  ┆ i64 │\n",
       "╞═════╪═══════╪═════╡\n",
       "│ a   ┆ true  ┆ 1   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ b   ┆ false ┆ 2   │\n",
       "└─────┴───────┴─────┘"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\n",
    "    \"c\": [1, 2],\n",
    "    \"a\": [\"a\", \"b\"],\n",
    "    \"b\": [True, False]\n",
    "})\n",
    "\n",
    "df.select(sorted(df.columns))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分组后按组内索引取到对应的行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "x\n",
       "</th>\n",
       "<th>\n",
       "y\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (6, 2)\n",
       "┌─────┬─────┐\n",
       "│ x   ┆ y   │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ i64 │\n",
       "╞═════╪═════╡\n",
       "│ 1   ┆ 1   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 0   ┆ 2   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 0   ┆ 4   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ 5   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 0   ┆ 6   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(dict(x=[1,0,1,0,1,0], y=[1,2,3,4,5,6]))\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面的代码表示取到组内索引为0和2的行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "x\n",
       "</th>\n",
       "<th>\n",
       "y\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "list\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "[1, 5]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "[2, 6]\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 2)\n",
       "┌─────┬────────────┐\n",
       "│ x   ┆ y          │\n",
       "│ --- ┆ ---        │\n",
       "│ i64 ┆ list [i64] │\n",
       "╞═════╪════════════╡\n",
       "│ 1   ┆ [1, 5]     │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 0   ┆ [2, 6]     │\n",
       "└─────┴────────────┘"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(\"x\").agg(pl.all().take([0, 2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "version\n",
       "</th>\n",
       "<th>\n",
       "testsuite\n",
       "</th>\n",
       "<th>\n",
       "status\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "\"scan1\"\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "85\n",
       "</td>\n",
       "<td>\n",
       "\"scan2\"\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "87\n",
       "</td>\n",
       "<td>\n",
       "\"scan3\"\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 3)\n",
       "┌─────────┬───────────┬────────┐\n",
       "│ version ┆ testsuite ┆ status │\n",
       "│ ---     ┆ ---       ┆ ---    │\n",
       "│ i64     ┆ str       ┆ str    │\n",
       "╞═════════╪═══════════╪════════╡\n",
       "│ 9       ┆ scan1     ┆ ok     │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 85      ┆ scan2     ┆ ok     │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 87      ┆ scan3     ┆ ok     │\n",
       "└─────────┴───────────┴────────┘"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import polars as pl\n",
    "\n",
    "df = pl.DataFrame(\n",
    "    {\"version\": [9, 85, 87], \"testsuite\": [\"scan1\", \"scan2\", \"scan3\"], \"status\": [\"ok\"] * 3})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "testsuite\n",
       "</th>\n",
       "<th>\n",
       "85\n",
       "</th>\n",
       "<th>\n",
       "87\n",
       "</th>\n",
       "<th>\n",
       "9\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"scan1\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"scan2\"\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"scan3\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 4)\n",
       "┌───────────┬──────┬──────┬──────┐\n",
       "│ testsuite ┆ 85   ┆ 87   ┆ 9    │\n",
       "│ ---       ┆ ---  ┆ ---  ┆ ---  │\n",
       "│ str       ┆ str  ┆ str  ┆ str  │\n",
       "╞═══════════╪══════╪══════╪══════╡\n",
       "│ scan1     ┆ null ┆ null ┆ ok   │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ scan2     ┆ ok   ┆ null ┆ null │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ scan3     ┆ null ┆ ok   ┆ null │\n",
       "└───────────┴──────┴──────┴──────┘"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wide = df.pivot(index=\"testsuite\", \n",
    "                columns='version', \n",
    "                values='status',\n",
    "                maintain_order=False)\n",
    "wide"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['9', '85', '87']"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df[\"version\"].to_list()\n",
    "cols = df[\"version\"].cast(pl.Utf8).to_list()\n",
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "testsuite\n",
       "</th>\n",
       "<th>\n",
       "9\n",
       "</th>\n",
       "<th>\n",
       "85\n",
       "</th>\n",
       "<th>\n",
       "87\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"scan1\"\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"scan2\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"scan3\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"ok\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 4)\n",
       "┌───────────┬──────┬──────┬──────┐\n",
       "│ testsuite ┆ 9    ┆ 85   ┆ 87   │\n",
       "│ ---       ┆ ---  ┆ ---  ┆ ---  │\n",
       "│ str       ┆ str  ┆ str  ┆ str  │\n",
       "╞═══════════╪══════╪══════╪══════╡\n",
       "│ scan1     ┆ ok   ┆ null ┆ null │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ scan2     ┆ null ┆ ok   ┆ null │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ scan3     ┆ null ┆ null ┆ ok   │\n",
       "└───────────┴──────┴──────┴──────┘"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wide[ [\"testsuite\"] + cols ]\n",
    "# 把 cols 的每个值作为列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
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       "<th>\n",
       "x\n",
       "</th>\n",
       "<th>\n",
       "y\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (4, 2)\n",
       "┌─────┬─────┐\n",
       "│ x   ┆ y   │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ i64 │\n",
       "╞═════╪═════╡\n",
       "│ 1   ┆ 1   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ 2   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 0   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 0   ┆ 4   │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(dict(x=[1,1,0,0], y=[1,2,3,4]))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "x\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
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      "text/plain": [
       "shape: (1, 1)\n",
       "┌─────┐\n",
       "│ x   │\n",
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       "│ u32 │\n",
       "╞═════╡\n",
       "│ 4   │\n",
       "└─────┘"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(\n",
    "     pl.first().len()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用alias复制和使用rename重命名列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "column1\n",
       "</th>\n",
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       "column2\n",
       "</th>\n",
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       "column3\n",
       "</th>\n",
       "<th>\n",
       "column4\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 4)\n",
       "┌─────────┬─────────┬─────────┬─────────┐\n",
       "│ column1 ┆ column2 ┆ column3 ┆ column4 │\n",
       "│ ---     ┆ ---     ┆ ---     ┆ ---     │\n",
       "│ i64     ┆ i64     ┆ i64     ┆ i64     │\n",
       "╞═════════╪═════════╪═════════╪═════════╡\n",
       "│ 1       ┆ 4       ┆ 7       ┆ 10      │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2       ┆ 5       ┆ 8       ┆ 11      │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3       ┆ 6       ┆ 9       ┆ 12      │\n",
       "└─────────┴─────────┴─────────┴─────────┘"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k2 = pl.DataFrame({\"column1\": [1,2,3],\n",
    "                   \"column2\": [4,5,6],\n",
    "                   \"column3\": [7,8,9],\n",
    "                   \"column4\": [10,11,12]})\n",
    "k2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "column1\n",
       "</th>\n",
       "<th>\n",
       "column2\n",
       "</th>\n",
       "<th>\n",
       "column3\n",
       "</th>\n",
       "<th>\n",
       "column4\n",
       "</th>\n",
       "<th>\n",
       "new column 1\n",
       "</th>\n",
       "<th>\n",
       "column5\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 6)\n",
       "┌─────────┬─────────┬─────────┬─────────┬──────────────┬─────────┐\n",
       "│ column1 ┆ column2 ┆ column3 ┆ column4 ┆ new column 1 ┆ column5 │\n",
       "│ ---     ┆ ---     ┆ ---     ┆ ---     ┆ ---          ┆ ---     │\n",
       "│ i64     ┆ i64     ┆ i64     ┆ i64     ┆ i64          ┆ i64     │\n",
       "╞═════════╪═════════╪═════════╪═════════╪══════════════╪═════════╡\n",
       "│ 1       ┆ 4       ┆ 7       ┆ 10      ┆ 1            ┆ 10      │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2       ┆ 5       ┆ 8       ┆ 11      ┆ 2            ┆ 11      │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3       ┆ 6       ┆ 9       ┆ 12      ┆ 3            ┆ 12      │\n",
       "└─────────┴─────────┴─────────┴─────────┴──────────────┴─────────┘"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 其实都变成了新增\n",
    "k2.with_columns([pl.col(\"column1\").alias(\"new column 1\"), \n",
    "                 pl.col(\"column4\").alias(\"column5\")])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "new column 1\n",
       "</th>\n",
       "<th>\n",
       "column2\n",
       "</th>\n",
       "<th>\n",
       "column3\n",
       "</th>\n",
       "<th>\n",
       "column4\n",
       "</th>\n",
       "<th>\n",
       "column5\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 5)\n",
       "┌──────────────┬─────────┬─────────┬─────────┬─────────┐\n",
       "│ new column 1 ┆ column2 ┆ column3 ┆ column4 ┆ column5 │\n",
       "│ ---          ┆ ---     ┆ ---     ┆ ---     ┆ ---     │\n",
       "│ i64          ┆ i64     ┆ i64     ┆ i64     ┆ i64     │\n",
       "╞══════════════╪═════════╪═════════╪═════════╪═════════╡\n",
       "│ 1            ┆ 4       ┆ 7       ┆ 10      ┆ 10      │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2            ┆ 5       ┆ 8       ┆ 11      ┆ 11      │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3            ┆ 6       ┆ 9       ┆ 12      ┆ 12      │\n",
       "└──────────────┴─────────┴─────────┴─────────┴─────────┘"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k2.rename(\n",
    "    {'column1':'new column 1'}\n",
    ").with_columns( [pl.col(\"column4\").alias(\"column5\")])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用alisa交换两列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "column1\n",
       "</th>\n",
       "<th>\n",
       "column2\n",
       "</th>\n",
       "<th>\n",
       "column3\n",
       "</th>\n",
       "<th>\n",
       "column4\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 4)\n",
       "┌─────────┬─────────┬─────────┬─────────┐\n",
       "│ column1 ┆ column2 ┆ column3 ┆ column4 │\n",
       "│ ---     ┆ ---     ┆ ---     ┆ ---     │\n",
       "│ i64     ┆ i64     ┆ i64     ┆ i64     │\n",
       "╞═════════╪═════════╪═════════╪═════════╡\n",
       "│ 7       ┆ 4       ┆ 1       ┆ 10      │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 8       ┆ 5       ┆ 2       ┆ 11      │\n",
       "├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤\n",
       "│ 9       ┆ 6       ┆ 3       ┆ 12      │\n",
       "└─────────┴─────────┴─────────┴─────────┘"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 其实都变成了新增\n",
    "k2.with_columns([pl.col(\"column1\").alias(\"column3\"), \n",
    "                 pl.col(\"column3\").alias(\"column1\")])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 通过parse_dates参数，在读入时自动解析日期格式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "ID\n",
       "</th>\n",
       "<th>\n",
       "start\n",
       "</th>\n",
       "<th>\n",
       "last_updt\n",
       "</th>\n",
       "<th>\n",
       "end\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "date\n",
       "</td>\n",
       "<td>\n",
       "datetime\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2008-10-31\n",
       "</td>\n",
       "<td>\n",
       "2020-11-28 12:48:53\n",
       "</td>\n",
       "<td>\n",
       "\"12/31/2008\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "2007-10-31\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"12/31/2007\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "2006-10-31\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"12/31/2006\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 4)\n",
       "┌─────┬────────────┬─────────────────────┬────────────┐\n",
       "│ ID  ┆ start      ┆ last_updt           ┆ end        │\n",
       "│ --- ┆ ---        ┆ ---                 ┆ ---        │\n",
       "│ i64 ┆ date       ┆ datetime[μs]        ┆ str        │\n",
       "╞═════╪════════════╪═════════════════════╪════════════╡\n",
       "│ 1   ┆ 2008-10-31 ┆ 2020-11-28 12:48:53 ┆ 12/31/2008 │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2   ┆ 2007-10-31 ┆ null                ┆ 12/31/2007 │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3   ┆ 2006-10-31 ┆ null                ┆ 12/31/2006 │\n",
       "└─────┴────────────┴─────────────────────┴────────────┘"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from io import StringIO\n",
    "\n",
    "my_csv = StringIO(\n",
    "\"\"\"\n",
    "ID,start,last_updt,end\n",
    "1,2008-10-31, 2020-11-28 12:48:53,12/31/2008\n",
    "2,2007-10-31, 2021-11-29 01:37:20,12/31/2007\n",
    "3,2006-10-31, 2021-11-30 23:22:05,12/31/2006\n",
    "\"\"\"\n",
    ")\n",
    "\n",
    "pl.read_csv(my_csv, parse_dates=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用repeat和explode对agg进行广播"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "x\n",
       "</th>\n",
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       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
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       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
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       "2\n",
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       "<tr>\n",
       "<td>\n",
       "3\n",
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       "</tr>\n",
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      "text/plain": [
       "shape: (3, 1)\n",
       "┌─────┐\n",
       "│ x   │\n",
       "│ --- │\n",
       "│ i64 │\n",
       "╞═════╡\n",
       "│ 1   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2   │\n",
       "├╌╌╌╌╌┤\n",
       "│ 3   │\n",
       "└─────┘"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(dict(x=[1,2,3]))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "y\n",
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       "i64\n",
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       "<td>\n",
       "i32\n",
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       "<tr>\n",
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       "<tr>\n",
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       "3\n",
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       "<td>\n",
       "1\n",
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       "shape: (3, 2)\n",
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       "└─────┴─────┘"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df.with_column(pl.lit(1).alias(\"y\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
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   "source": [
    "\n",
    "df = pl.DataFrame(dict(x=[1,1,0,0])).groupby(\"x\")\n",
    "df.agg( pl.repeat(1, pl.count() ) ).explode(\n",
    "    pl.col('literal')\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 一个复杂的应用场景\n",
    "https://stackoverflow.com/questions/71552672/how-to-filter-record-sequences-from-a-polars-dataframe-using-multiple-threads"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "应用场景  \n",
    "首先我们有各个时期，本来每个时期对每个用户都应该有记录的  \n",
    "但是部分id中间断了，只有它在某个时期没有记录，那么关于这个用户的后面的记录都删掉"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
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       "└─────┴─────┴───────┘"
      ]
     },
     "execution_count": 88,
     "metadata": {},
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    }
   ],
   "source": [
    "df = pl.DataFrame({'Id': [1,1,2,2,2,2,3,3,4,4,4,5,5,5,6,6,6],\n",
    " 'Age': [1,4,1,2,3,4,1,2,1,2,3,1,2,4,2,3,4],\n",
    " 'Value': [1,142,4,73,109,145,6,72,-8,67,102,-1,72,150,72,111,149]})\n",
    "df"
   ]
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  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
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     "execution_count": 93,
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   ],
   "source": [
    "df2 = df.filter(\n",
    "    pl.col('Age').rank().over('Id') == pl.col('Age')\n",
    ")\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "尝试一点点来解析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
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       "<tr>\n",
       "<td>\n",
       "15.5\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (17, 1)\n",
       "┌──────┐\n",
       "│ Age  │\n",
       "│ ---  │\n",
       "│ f32  │\n",
       "╞══════╡\n",
       "│ 3.0  │\n",
       "├╌╌╌╌╌╌┤\n",
       "│ 15.5 │\n",
       "├╌╌╌╌╌╌┤\n",
       "│ 3.0  │\n",
       "├╌╌╌╌╌╌┤\n",
       "│ 8.0  │\n",
       "├╌╌╌╌╌╌┤\n",
       "│ ...  │\n",
       "├╌╌╌╌╌╌┤\n",
       "│ 15.5 │\n",
       "├╌╌╌╌╌╌┤\n",
       "│ 8.0  │\n",
       "├╌╌╌╌╌╌┤\n",
       "│ 12.0 │\n",
       "├╌╌╌╌╌╌┤\n",
       "│ 15.5 │\n",
       "└──────┘"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 首先来看一下age被排序后的情况\n",
    "df.select(\n",
    "    pl.col('Age').rank()\n",
    ")\n",
    "# 我们可以看到，所有的值被计算了值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "shape: (17, 1)\n",
       "┌─────┐\n",
       "│ Age │\n",
       "│ --- │\n",
       "│ f32 │\n",
       "╞═════╡\n",
       "│ 1.0 │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2.0 │\n",
       "├╌╌╌╌╌┤\n",
       "│ 1.0 │\n",
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       "│ 2.0 │\n",
       "├╌╌╌╌╌┤\n",
       "│ ... │\n",
       "├╌╌╌╌╌┤\n",
       "│ 3.0 │\n",
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       "│ 1.0 │\n",
       "├╌╌╌╌╌┤\n",
       "│ 2.0 │\n",
       "├╌╌╌╌╌┤\n",
       "│ 3.0 │\n",
       "└─────┘"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 然后我们对秩进行了分组，按照id分的\n",
    "df.select(\n",
    "    pl.col('Age').rank().over('Id')\n",
    ")\n",
    "# 如果我分组后的值，跟Age的值一样，那就说明没有缺失"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "那么问题来了，如果我们这里的age，不是数字呢？而是时间，或者一些字符编码呢？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "shape: (17, 3)\n",
       "┌──────┬─────┬───────┐\n",
       "│ Id   ┆ Age ┆ Value │\n",
       "│ ---  ┆ --- ┆ ---   │\n",
       "│ str  ┆ i64 ┆ i64   │\n",
       "╞══════╪═════╪═══════╡\n",
       "│ a    ┆ 1   ┆ 1     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ a    ┆ 4   ┆ 142   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ b    ┆ 1   ┆ 4     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ b    ┆ 2   ┆ 73    │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ ...  ┆ ... ┆ ...   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ wang ┆ 4   ┆ 150   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 风   ┆ 2   ┆ 72    │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 风   ┆ 3   ┆ 111   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 风   ┆ 4   ┆ 149   │\n",
       "└──────┴─────┴───────┘"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(\n",
    "    {'Id': ['a','a','b','b','b','b','c','c','xuan','xuan','xuan','wang','wang','wang','风','风','风'],\n",
    " 'Age': [1,4,1,2,3,4,1,2,1,2,3,1,2,4,2,3,4],\n",
    " 'Value': [1,142,4,73,109,145,6,72,-8,67,102,-1,72,150,72,111,149]})\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过cumcount生成组内索引/序号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\"c\"\n",
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       "2\n",
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       "<td>\n",
       "72\n",
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       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"xuan\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
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       "<td>\n",
       "-8\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"xuan\"\n",
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       "<td>\n",
       "2\n",
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       "<td>\n",
       "67\n",
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       "<tr>\n",
       "<td>\n",
       "\"xuan\"\n",
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       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "102\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"wang\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
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       "<td>\n",
       "-1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"wang\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "72\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (12, 3)\n",
       "┌──────┬─────┬───────┐\n",
       "│ Id   ┆ Age ┆ Value │\n",
       "│ ---  ┆ --- ┆ ---   │\n",
       "│ str  ┆ i64 ┆ i64   │\n",
       "╞══════╪═════╪═══════╡\n",
       "│ a    ┆ 1   ┆ 1     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ b    ┆ 1   ┆ 4     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ b    ┆ 2   ┆ 73    │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ b    ┆ 3   ┆ 109   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ ...  ┆ ... ┆ ...   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ xuan ┆ 2   ┆ 67    │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ xuan ┆ 3   ┆ 102   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ wang ┆ 1   ┆ -1    │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ wang ┆ 2   ┆ 72    │\n",
       "└──────┴─────┴───────┘"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.with_column(\n",
    "    pl.col('Id').over('Id').cumcount().alias('code')\n",
    ").filter(\n",
    "    pl.col('Age').rank().over('Id') == pl.col('Age')\n",
    ").drop('code')\n",
    "# 最后再把组内索引去掉"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 组内排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "group\n",
       "</th>\n",
       "<th>\n",
       "value\n",
       "</th>\n",
       "<th>\n",
       "value2\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
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       "1\n",
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       "<td>\n",
       "6\n",
       "</td>\n",
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       "5\n",
       "</td>\n",
       "</tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (7, 3)\n",
       "┌───────┬───────┬────────┐\n",
       "│ group ┆ value ┆ value2 │\n",
       "│ ---   ┆ ---   ┆ ---    │\n",
       "│ i64   ┆ i64   ┆ i64    │\n",
       "╞═══════╪═══════╪════════╡\n",
       "│ 2     ┆ 3     ┆ 5      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 4     ┆ 4      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 3     ┆ 3      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 1     ┆ 2      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 1     ┆ 1      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 3     ┆ 0      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 6     ┆ 5      │\n",
       "└───────┴───────┴────────┘"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\n",
    "  'group': [2,2,1,1,2,2,1],\n",
    "  'value': [3,4,3,1,1,3,6],\n",
    "  'value2': [5,4,3,2,1,0,5],\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这是直接按'value','value2'进行联动排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "5\n",
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       "</div>"
      ],
      "text/plain": [
       "shape: (7, 3)\n",
       "┌───────┬───────┬────────┐\n",
       "│ group ┆ value ┆ value2 │\n",
       "│ ---   ┆ ---   ┆ ---    │\n",
       "│ i64   ┆ i64   ┆ i64    │\n",
       "╞═══════╪═══════╪════════╡\n",
       "│ 2     ┆ 1     ┆ 1      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 1     ┆ 2      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 3     ┆ 0      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 3     ┆ 3      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 3     ┆ 5      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 4     ┆ 4      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 6     ┆ 5      │\n",
       "└───────┴───────┴────────┘"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(\n",
    "    pl.all().sort_by(['value','value2'])\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这是先对group进行分组，再对'value','value2'排序？？  \n",
    "还是先对'value','value2'排序，再对group分组？这似乎和结果对不上。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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      "text/plain": [
       "shape: (7, 3)\n",
       "┌───────┬───────┬────────┐\n",
       "│ group ┆ value ┆ value2 │\n",
       "│ ---   ┆ ---   ┆ ---    │\n",
       "│ i64   ┆ i64   ┆ i64    │\n",
       "╞═══════╪═══════╪════════╡\n",
       "│ 2     ┆ 1     ┆ 1      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 3     ┆ 0      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 1     ┆ 2      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 3     ┆ 3      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 3     ┆ 5      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 4     ┆ 4      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 6     ┆ 5      │\n",
       "└───────┴───────┴────────┘"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(\n",
    "    pl.all().sort_by(['value','value2']).over('group')\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这是先对group进行分组，再对'value','value2'排序，再对结果进行group的排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "\n",
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       "i64\n",
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       "</tr>\n",
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       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (7, 3)\n",
       "┌───────┬───────┬────────┐\n",
       "│ group ┆ value ┆ value2 │\n",
       "│ ---   ┆ ---   ┆ ---    │\n",
       "│ i64   ┆ i64   ┆ i64    │\n",
       "╞═══════╪═══════╪════════╡\n",
       "│ 1     ┆ 1     ┆ 2      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 3     ┆ 3      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 1     ┆ 6     ┆ 5      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 1     ┆ 1      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 3     ┆ 0      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 3     ┆ 5      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2     ┆ 4     ┆ 4      │\n",
       "└───────┴───────┴────────┘"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select(\n",
    "    pl.all().sort_by(['value','value2']).over('group').sort_by(['group'])\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 从时间戳创建时间格式数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于polars的时间戮是从毫秒ms开始的，所以要乘以1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "epoch_seconds\n",
       "</th>\n",
       "</tr>\n",
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       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
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       "<tbody>\n",
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       "<td>\n",
       "1648457740\n",
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       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1648457750\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 1)\n",
       "┌───────────────┐\n",
       "│ epoch_seconds │\n",
       "│ ---           │\n",
       "│ i64           │\n",
       "╞═══════════════╡\n",
       "│ 1648457740    │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 1648457750    │\n",
       "└───────────────┘"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 原始数据是从秒开始的\n",
    "df = pl.DataFrame({\n",
    "    \"epoch_seconds\": [1648457740, 1648457740 + 10]\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "datetime\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "datetime\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "2022-03-28 08:55:40\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2022-03-28 08:55:50\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 1)\n",
       "┌─────────────────────┐\n",
       "│ datetime            │\n",
       "│ ---                 │\n",
       "│ datetime[ms]        │\n",
       "╞═════════════════════╡\n",
       "│ 2022-03-28 08:55:40 │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2022-03-28 08:55:50 │\n",
       "└─────────────────────┘"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MILLISECONDS_IN_SECOND = 1000;\n",
    "\n",
    "df.select(\n",
    "    (pl.col(\"epoch_seconds\") * MILLISECONDS_IN_SECOND).cast(\n",
    "        pl.Datetime).dt.with_time_unit(\"ms\").alias(\"datetime\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 拼接DF"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "rechunk the final DataFrame/Series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "c\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 3)\n",
       "┌─────┬─────┬─────┐\n",
       "│ a   ┆ b   ┆ c   │\n",
       "│ --- ┆ --- ┆ --- │\n",
       "│ i64 ┆ i64 ┆ i64 │\n",
       "╞═════╪═════╪═════╡\n",
       "│ 1   ┆ 2   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 5   ┆ 6   │\n",
       "└─────┴─────┴─────┘"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pl.DataFrame({\"a\": [1], \"b\": [2], \"c\": [3]})\n",
    "df2 = pl.DataFrame({\"a\": [4], \"b\": [5], \"c\": [6]})\n",
    "\n",
    "\n",
    "# new memory slab\n",
    "new_df = pl.concat([df1, df2], rechunk=True)\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "c\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 3)\n",
       "┌─────┬─────┬─────┐\n",
       "│ a   ┆ b   ┆ c   │\n",
       "│ --- ┆ --- ┆ --- │\n",
       "│ i64 ┆ i64 ┆ i64 │\n",
       "╞═════╪═════╪═════╡\n",
       "│ 1   ┆ 2   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 5   ┆ 6   │\n",
       "└─────┴─────┴─────┘"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# append free (no memory copy)\n",
    "new_df = df1.vstack(df2)\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "4\n",
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       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (6, 3)\n",
       "┌─────┬─────┬─────┐\n",
       "│ a   ┆ b   ┆ c   │\n",
       "│ --- ┆ --- ┆ --- │\n",
       "│ i64 ┆ i64 ┆ i64 │\n",
       "╞═════╪═════╪═════╡\n",
       "│ 1   ┆ 2   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 5   ┆ 6   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 5   ┆ 6   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 5   ┆ 6   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 5   ┆ 6   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 5   ┆ 6   │\n",
       "└─────┴─────┴─────┘"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# try to append in place\n",
    "df1.extend(df2)\n",
    "df1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "ham\n",
       "</th>\n",
       "<th>\n",
       "spam\n",
       "</th>\n",
       "<th>\n",
       "foo\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
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       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "22\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "33\n",
       "</td>\n",
       "<td>\n",
       "1\n",
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       "</table>\n",
       "</div>"
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      "text/plain": [
       "shape: (3, 3)\n",
       "┌─────┬──────┬─────┐\n",
       "│ ham ┆ spam ┆ foo │\n",
       "│ --- ┆ ---  ┆ --- │\n",
       "│ i64 ┆ i64  ┆ i64 │\n",
       "╞═════╪══════╪═════╡\n",
       "│ 2   ┆ 11   ┆ 3   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ 22   ┆ 2   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ 33   ┆ 1   │\n",
       "└─────┴──────┴─────┘"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 在前面添加一列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "z\n",
       "</th>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
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       "str\n",
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       "<td>\n",
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       "</tr>\n",
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       "<tr>\n",
       "<td>\n",
       "\"foo\"\n",
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       "</td>\n",
       "<td>\n",
       "true\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"foo\"\n",
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       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "false\n",
       "</td>\n",
       "</tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 3)\n",
       "┌─────┬─────┬───────┐\n",
       "│ z   ┆ a   ┆ b     │\n",
       "│ --- ┆ --- ┆ ---   │\n",
       "│ str ┆ i64 ┆ bool  │\n",
       "╞═════╪═════╪═══════╡\n",
       "│ foo ┆ 1   ┆ true  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ foo ┆ 2   ┆ null  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ foo ┆ 3   ┆ false │\n",
       "└─────┴─────┴───────┘"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\n",
    "    \"a\": [1, 2, 3],\n",
    "    \"b\": [True, None, False]\n",
    "})\n",
    "\n",
    "df.select([\n",
    "    pl.lit(\"foo\").alias(\"z\"),\n",
    "    pl.all()\n",
    "])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用apply函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里`np.left_shift(x, 8)`是位运算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "2\n",
       "</td>\n",
       "<td>\n",
       "512\n",
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       "<tr>\n",
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       "4\n",
       "</td>\n",
       "<td>\n",
       "1024\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "2048\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "16\n",
       "</td>\n",
       "<td>\n",
       "4096\n",
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       "</tbody>\n",
       "</table>\n",
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      "text/plain": [
       "shape: (4, 2)\n",
       "┌──────┬────────┐\n",
       "│ col1 ┆ result │\n",
       "│ ---  ┆ ---    │\n",
       "│ i64  ┆ i64    │\n",
       "╞══════╪════════╡\n",
       "│ 2    ┆ 512    │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 4    ┆ 1024   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 8    ┆ 2048   │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 16   ┆ 4096   │\n",
       "└──────┴────────┘"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "# import polars as pl\n",
    "\n",
    "\n",
    "df = pl.DataFrame({\"col1\": [2, 4, 8, 16]}).lazy()\n",
    "df.with_column(\n",
    "    pl.col(\"col1\").apply(lambda x: np.left_shift(x, 8).item()).alias(\"result\")\n",
    ").collect()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果需要传入两个列  \n",
    "If you need to pass multiple columns from Polars to the ufunc,   \n",
    "then use the struct expression with apply."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "col1\n",
       "</th>\n",
       "<th>\n",
       "shift\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "16\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (4, 2)\n",
       "┌──────┬───────┐\n",
       "│ col1 ┆ shift │\n",
       "│ ---  ┆ ---   │\n",
       "│ i64  ┆ i64   │\n",
       "╞══════╪═══════╡\n",
       "│ 2    ┆ 1     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 4    ┆ 1     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 8    ┆ 2     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 16   ┆ 2     │\n",
       "└──────┴───────┘"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\"col1\": [2, 4, 8, 16], \"shift\": [1, 1, 2, 2]})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "col1\n",
       "</th>\n",
       "<th>\n",
       "shift\n",
       "</th>\n",
       "<th>\n",
       "result\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "32\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "16\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "64\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (4, 3)\n",
       "┌──────┬───────┬────────┐\n",
       "│ col1 ┆ shift ┆ result │\n",
       "│ ---  ┆ ---   ┆ ---    │\n",
       "│ i64  ┆ i64   ┆ i64    │\n",
       "╞══════╪═══════╪════════╡\n",
       "│ 2    ┆ 1     ┆ 4      │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 4    ┆ 1     ┆ 8      │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 8    ┆ 2     ┆ 32     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 16   ┆ 2     ┆ 64     │\n",
       "└──────┴───────┴────────┘"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.with_column(\n",
    "    pl.struct([\"col1\", \"shift\"])\n",
    "    .apply(lambda cols: np.left_shift(cols[\"col1\"], cols[\"shift\"]).item())\n",
    "    .alias(\"result\")\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### join并填充缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "key\n",
       "</th>\n",
       "<th>\n",
       "var1\n",
       "</th>\n",
       "<th>\n",
       "var2\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"d\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (4, 3)\n",
       "┌─────┬──────┬──────┐\n",
       "│ key ┆ var1 ┆ var2 │\n",
       "│ --- ┆ ---  ┆ ---  │\n",
       "│ str ┆ i64  ┆ i64  │\n",
       "╞═════╪══════╪══════╡\n",
       "│ a   ┆ 1    ┆ 2    │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ b   ┆ 1    ┆ 2    │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ c   ┆ null ┆ 2    │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ d   ┆ 1    ┆ null │\n",
       "└─────┴──────┴──────┘"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pl.DataFrame({\"key\": [\"a\", \"b\", \"d\"], \"var1\": [1, 1, 1]})\n",
    "df2 = pl.DataFrame({\"key\": [\"a\", \"b\", \"c\"], \"var2\": [2, 2, 2]})\n",
    "df1.join(df2, on=\"key\", how=\"outer\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "key\n",
       "</th>\n",
       "<th>\n",
       "var1\n",
       "</th>\n",
       "<th>\n",
       "var2\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"a\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"b\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"c\"\n",
       "</td>\n",
       "<td>\n",
       "999\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"d\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "999\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (4, 3)\n",
       "┌─────┬──────┬──────┐\n",
       "│ key ┆ var1 ┆ var2 │\n",
       "│ --- ┆ ---  ┆ ---  │\n",
       "│ str ┆ i64  ┆ i64  │\n",
       "╞═════╪══════╪══════╡\n",
       "│ a   ┆ 1    ┆ 2    │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ b   ┆ 1    ┆ 2    │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ c   ┆ 999  ┆ 2    │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ d   ┆ 1    ┆ 999  │\n",
       "└─────┴──────┴──────┘"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.join(df2, on=\"key\", how=\"outer\").with_column(\n",
    "    pl.all().fill_null(999)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 设置显示的行数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pl.Config.set_tbl_rows(1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 加总部分列求和"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "id\n",
       "</th>\n",
       "<th>\n",
       "cat_a\n",
       "</th>\n",
       "<th>\n",
       "cat_b\n",
       "</th>\n",
       "<th>\n",
       "cat_c\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 4)\n",
       "┌─────┬───────┬───────┬───────┐\n",
       "│ id  ┆ cat_a ┆ cat_b ┆ cat_c │\n",
       "│ --- ┆ ---   ┆ ---   ┆ ---   │\n",
       "│ i64 ┆ i64   ┆ i64   ┆ i64   │\n",
       "╞═════╪═══════╪═══════╪═══════╡\n",
       "│ 1   ┆ 2     ┆ 5     ┆ 0     │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 2   ┆ 7     ┆ 1     ┆ 3     │\n",
       "└─────┴───────┴───────┴───────┘"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(\n",
    "    {\n",
    "        \"id\": [1, 2],\n",
    "        \"cat_a\": [2, 7],\n",
    "        \"cat_b\": [5, 1],\n",
    "        \"cat_c\": [0, 3]\n",
    "    }\n",
    ")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "id\n",
       "</th>\n",
       "<th>\n",
       "cat_a\n",
       "</th>\n",
       "<th>\n",
       "cat_b\n",
       "</th>\n",
       "<th>\n",
       "cat_c\n",
       "</th>\n",
       "<th>\n",
       "horizontal_sum\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (2, 5)\n",
       "┌─────┬───────┬───────┬───────┬────────────────┐\n",
       "│ id  ┆ cat_a ┆ cat_b ┆ cat_c ┆ horizontal_sum │\n",
       "│ --- ┆ ---   ┆ ---   ┆ ---   ┆ ---            │\n",
       "│ i64 ┆ i64   ┆ i64   ┆ i64   ┆ i64            │\n",
       "╞═════╪═══════╪═══════╪═══════╪════════════════╡\n",
       "│ 1   ┆ 2     ┆ 5     ┆ 0     ┆ 7              │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2   ┆ 7     ┆ 1     ┆ 3     ┆ 11             │\n",
       "└─────┴───────┴───────┴───────┴────────────────┘"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.with_column(\n",
    "    pl.fold(0, lambda acc, s: acc + s, pl.all().exclude(\"id\")).alias(\"horizontal_sum\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "先来学习下fold函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "a\n",
       "</th>\n",
       "<th>\n",
       "b\n",
       "</th>\n",
       "<th>\n",
       "c\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "2.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "3.0\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 3)\n",
       "┌─────┬─────┬─────┐\n",
       "│ a   ┆ b   ┆ c   │\n",
       "│ --- ┆ --- ┆ --- │\n",
       "│ i64 ┆ i64 ┆ f64 │\n",
       "╞═════╪═════╪═════╡\n",
       "│ 2   ┆ 1   ┆ 1.0 │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 1   ┆ 2   ┆ 2.0 │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ 3   ┆ 3.0 │\n",
       "└─────┴─────┴─────┘"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame(\n",
    "    {\n",
    "        \"a\": [2, 1, 3],\n",
    "        \"b\": [1, 2, 3],\n",
    "        \"c\": [1.0, 2.0, 3.0],\n",
    "    }\n",
    ")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "shape: (3,)\n",
       "Series: 'a' [f64]\n",
       "[\n",
       "\t4.0\n",
       "\t5.0\n",
       "\t9.0\n",
       "]"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.fold(lambda s1, s2: s1 + s2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "shape: (3,)\n",
       "Series: 'a' [f64]\n",
       "[\n",
       "\t1.0\n",
       "\t1.0\n",
       "\t3.0\n",
       "]"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.fold(lambda s1, s2: s1.zip_with(s1 < s2, s2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 根据另一个DF的值，对当前DF中某列的值进行修改"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "当df和df1中的TS列的值想值相等时  \n",
    "根据用df1中Dr的值替换df中mmsi的值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import polars as pl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "TS\n",
       "</th>\n",
       "<th>\n",
       "mmsi\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "13\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "14\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "15\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "16\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "17\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (7, 2)\n",
       "┌─────┬──────┐\n",
       "│ TS  ┆ mmsi │\n",
       "│ --- ┆ ---  │\n",
       "│ i64 ┆ i64  │\n",
       "╞═════╪══════╡\n",
       "│ 1   ┆ 11   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ 2   ┆ 12   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ 3   ┆ 13   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ 4   ┆ 14   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ 5   ┆ 15   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ 6   ┆ 16   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ 7   ┆ 17   │\n",
       "└─────┴──────┘"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pl.DataFrame({\"TS\": [1, 2, 3, 4, 5, 6, 7], \"mmsi\":[11,12,13,14,15,16,17]})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "TS\n",
       "</th>\n",
       "<th>\n",
       "Dr\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
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       "6\n",
       "</td>\n",
       "<td>\n",
       "22\n",
       "</td>\n",
       "</tr>\n",
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       "7\n",
       "</td>\n",
       "<td>\n",
       "23\n",
       "</td>\n",
       "</tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 2)\n",
       "┌─────┬─────┐\n",
       "│ TS  ┆ Dr  │\n",
       "│ --- ┆ --- │\n",
       "│ i64 ┆ i64 │\n",
       "╞═════╪═════╡\n",
       "│ 4   ┆ 21  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 6   ┆ 22  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 7   ┆ 23  │\n",
       "└─────┴─────┘"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pl.DataFrame({\n",
    "    \"TS\": [4, 6, 7], \n",
    "    \"Dr\": [21,22,23]})\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
       "<tr>\n",
       "<th>\n",
       "TS\n",
       "</th>\n",
       "<th>\n",
       "mmsi\n",
       "</th>\n",
       "<th>\n",
       "Dr\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
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       "21\n",
       "</td>\n",
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       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "15\n",
       "</td>\n",
       "<td>\n",
       "15\n",
       "</td>\n",
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       "</td>\n",
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       "22\n",
       "</td>\n",
       "<td>\n",
       "22\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "<td>\n",
       "23\n",
       "</td>\n",
       "<td>\n",
       "23\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (7, 3)\n",
       "┌─────┬──────┬─────┐\n",
       "│ TS  ┆ mmsi ┆ Dr  │\n",
       "│ --- ┆ ---  ┆ --- │\n",
       "│ i64 ┆ i64  ┆ i64 │\n",
       "╞═════╪══════╪═════╡\n",
       "│ 1   ┆ 11   ┆ 11  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 2   ┆ 12   ┆ 12  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 3   ┆ 13   ┆ 13  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 4   ┆ 21   ┆ 21  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 5   ┆ 15   ┆ 15  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 6   ┆ 22   ┆ 22  │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌┤\n",
       "│ 7   ┆ 23   ┆ 23  │\n",
       "└─────┴──────┴─────┘"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.join(\n",
    "    df1,\n",
    "    on=\"TS\",\n",
    "    how=\"left\"\n",
    ").with_column(\n",
    "    pl.col('Dr').fill_null( pl.col('mmsi') )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape: (7, 2)\n",
      "┌─────┬──────┐\n",
      "│ TS  ┆ mmsi │\n",
      "│ --- ┆ ---  │\n",
      "│ i64 ┆ i64  │\n",
      "╞═════╪══════╡\n",
      "│ 1   ┆ 11   │\n",
      "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
      "│ 2   ┆ 12   │\n",
      "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
      "│ 3   ┆ 13   │\n",
      "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
      "│ 4   ┆ 21   │\n",
      "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
      "│ 5   ┆ 15   │\n",
      "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
      "│ 6   ┆ 22   │\n",
      "├╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
      "│ 7   ┆ 23   │\n",
      "└─────┴──────┘\n"
     ]
    }
   ],
   "source": [
    "df = (\n",
    "    df.join(df1, on=\"TS\", how=\"left\")\n",
    "    .with_column(pl.col(\"Dr\").fill_null(pl.col(\"mmsi\")))\n",
    "    .drop(\"mmsi\")\n",
    "    .rename({\"Dr\": \"mmsi\"})\n",
    ")\n",
    "print(df)"
   ]
  }
 ],
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