polars官方学习3.1-3.3.ipynb

{
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  {
   "cell_type": "code",
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   "outputs": [
    {
     "data": {
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       "<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",
       "sepal_length\n",
       "</th>\n",
       "<th>\n",
       "sepal_width\n",
       "</th>\n",
       "<th>\n",
       "petal_length\n",
       "</th>\n",
       "<th>\n",
       "petal_width\n",
       "</th>\n",
       "<th>\n",
       "species\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "5.1\n",
       "</td>\n",
       "<td>\n",
       "3.5\n",
       "</td>\n",
       "<td>\n",
       "1.4\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4.9\n",
       "</td>\n",
       "<td>\n",
       "3.0\n",
       "</td>\n",
       "<td>\n",
       "1.4\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4.7\n",
       "</td>\n",
       "<td>\n",
       "3.2\n",
       "</td>\n",
       "<td>\n",
       "1.3\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4.6\n",
       "</td>\n",
       "<td>\n",
       "3.1\n",
       "</td>\n",
       "<td>\n",
       "1.5\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5.0\n",
       "</td>\n",
       "<td>\n",
       "3.6\n",
       "</td>\n",
       "<td>\n",
       "1.4\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5.4\n",
       "</td>\n",
       "<td>\n",
       "3.9\n",
       "</td>\n",
       "<td>\n",
       "1.7\n",
       "</td>\n",
       "<td>\n",
       "0.4\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4.6\n",
       "</td>\n",
       "<td>\n",
       "3.4\n",
       "</td>\n",
       "<td>\n",
       "1.4\n",
       "</td>\n",
       "<td>\n",
       "0.3\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5.0\n",
       "</td>\n",
       "<td>\n",
       "3.4\n",
       "</td>\n",
       "<td>\n",
       "1.5\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4.4\n",
       "</td>\n",
       "<td>\n",
       "2.9\n",
       "</td>\n",
       "<td>\n",
       "1.4\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4.9\n",
       "</td>\n",
       "<td>\n",
       "3.1\n",
       "</td>\n",
       "<td>\n",
       "1.5\n",
       "</td>\n",
       "<td>\n",
       "0.1\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5.4\n",
       "</td>\n",
       "<td>\n",
       "3.7\n",
       "</td>\n",
       "<td>\n",
       "1.5\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "4.8\n",
       "</td>\n",
       "<td>\n",
       "3.4\n",
       "</td>\n",
       "<td>\n",
       "1.6\n",
       "</td>\n",
       "<td>\n",
       "0.2\n",
       "</td>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.0\n",
       "</td>\n",
       "<td>\n",
       "3.0\n",
       "</td>\n",
       "<td>\n",
       "4.8\n",
       "</td>\n",
       "<td>\n",
       "1.8\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.9\n",
       "</td>\n",
       "<td>\n",
       "3.1\n",
       "</td>\n",
       "<td>\n",
       "5.4\n",
       "</td>\n",
       "<td>\n",
       "2.1\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.7\n",
       "</td>\n",
       "<td>\n",
       "3.1\n",
       "</td>\n",
       "<td>\n",
       "5.6\n",
       "</td>\n",
       "<td>\n",
       "2.4\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.9\n",
       "</td>\n",
       "<td>\n",
       "3.1\n",
       "</td>\n",
       "<td>\n",
       "5.1\n",
       "</td>\n",
       "<td>\n",
       "2.3\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5.8\n",
       "</td>\n",
       "<td>\n",
       "2.7\n",
       "</td>\n",
       "<td>\n",
       "5.1\n",
       "</td>\n",
       "<td>\n",
       "1.9\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.8\n",
       "</td>\n",
       "<td>\n",
       "3.2\n",
       "</td>\n",
       "<td>\n",
       "5.9\n",
       "</td>\n",
       "<td>\n",
       "2.3\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.7\n",
       "</td>\n",
       "<td>\n",
       "3.3\n",
       "</td>\n",
       "<td>\n",
       "5.7\n",
       "</td>\n",
       "<td>\n",
       "2.5\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.7\n",
       "</td>\n",
       "<td>\n",
       "3.0\n",
       "</td>\n",
       "<td>\n",
       "5.2\n",
       "</td>\n",
       "<td>\n",
       "2.3\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.3\n",
       "</td>\n",
       "<td>\n",
       "2.5\n",
       "</td>\n",
       "<td>\n",
       "5.0\n",
       "</td>\n",
       "<td>\n",
       "1.9\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.5\n",
       "</td>\n",
       "<td>\n",
       "3.0\n",
       "</td>\n",
       "<td>\n",
       "5.2\n",
       "</td>\n",
       "<td>\n",
       "2.0\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "6.2\n",
       "</td>\n",
       "<td>\n",
       "3.4\n",
       "</td>\n",
       "<td>\n",
       "5.4\n",
       "</td>\n",
       "<td>\n",
       "2.3\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5.9\n",
       "</td>\n",
       "<td>\n",
       "3.0\n",
       "</td>\n",
       "<td>\n",
       "5.1\n",
       "</td>\n",
       "<td>\n",
       "1.8\n",
       "</td>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (150, 5)\n",
       "┌──────────────┬─────────────┬──────────────┬─────────────┬───────────┐\n",
       "│ sepal_length ┆ sepal_width ┆ petal_length ┆ petal_width ┆ species   │\n",
       "│ ---          ┆ ---         ┆ ---          ┆ ---         ┆ ---       │\n",
       "│ f64          ┆ f64         ┆ f64          ┆ f64         ┆ str       │\n",
       "╞══════════════╪═════════════╪══════════════╪═════════════╪═══════════╡\n",
       "│ 5.1          ┆ 3.5         ┆ 1.4          ┆ 0.2         ┆ setosa    │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 4.9          ┆ 3.0         ┆ 1.4          ┆ 0.2         ┆ setosa    │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 4.7          ┆ 3.2         ┆ 1.3          ┆ 0.2         ┆ setosa    │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 4.6          ┆ 3.1         ┆ 1.5          ┆ 0.2         ┆ setosa    │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ...          ┆ ...         ┆ ...          ┆ ...         ┆ ...       │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 6.3          ┆ 2.5         ┆ 5.0          ┆ 1.9         ┆ virginica │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 6.5          ┆ 3.0         ┆ 5.2          ┆ 2.0         ┆ virginica │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 6.2          ┆ 3.4         ┆ 5.4          ┆ 2.3         ┆ virginica │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 5.9          ┆ 3.0         ┆ 5.1          ┆ 1.8         ┆ virginica │\n",
       "└──────────────┴─────────────┴──────────────┴─────────────┴───────────┘"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import polars as pl\n",
    "\n",
    "df = pl.read_csv(\"iris.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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",
       "species\n",
       "</th>\n",
       "<th>\n",
       "sepal_length\n",
       "</th>\n",
       "<th>\n",
       "sepal_width\n",
       "</th>\n",
       "<th>\n",
       "petal_length\n",
       "</th>\n",
       "<th>\n",
       "petal_width\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",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"setosa\"\n",
       "</td>\n",
       "<td>\n",
       "116.9\n",
       "</td>\n",
       "<td>\n",
       "81.7\n",
       "</td>\n",
       "<td>\n",
       "33.2\n",
       "</td>\n",
       "<td>\n",
       "6.1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"versicolor\"\n",
       "</td>\n",
       "<td>\n",
       "281.9\n",
       "</td>\n",
       "<td>\n",
       "131.8\n",
       "</td>\n",
       "<td>\n",
       "202.9\n",
       "</td>\n",
       "<td>\n",
       "63.3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"virginica\"\n",
       "</td>\n",
       "<td>\n",
       "324.5\n",
       "</td>\n",
       "<td>\n",
       "146.2\n",
       "</td>\n",
       "<td>\n",
       "273.1\n",
       "</td>\n",
       "<td>\n",
       "99.6\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 5)\n",
       "┌────────────┬──────────────┬─────────────┬──────────────┬─────────────┐\n",
       "│ species    ┆ sepal_length ┆ sepal_width ┆ petal_length ┆ petal_width │\n",
       "│ ---        ┆ ---          ┆ ---         ┆ ---          ┆ ---         │\n",
       "│ str        ┆ f64          ┆ f64         ┆ f64          ┆ f64         │\n",
       "╞════════════╪══════════════╪═════════════╪══════════════╪═════════════╡\n",
       "│ setosa     ┆ 116.9        ┆ 81.7        ┆ 33.2         ┆ 6.1         │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ versicolor ┆ 281.9        ┆ 131.8       ┆ 202.9        ┆ 63.3        │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ virginica  ┆ 324.5        ┆ 146.2       ┆ 273.1        ┆ 99.6        │\n",
       "└────────────┴──────────────┴─────────────┴──────────────┴─────────────┘"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    df.filter(\n",
    "        pl.col(\"sepal_length\") > 5  #筛选出sepal_length大于5的行\n",
    "        )\n",
    "      .groupby(\"species\")  #按species分组\n",
    "      .agg(pl.all().sum()) #计算所有列的组内求和\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 构建示例数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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",
       "nrs\n",
       "</th>\n",
       "<th>\n",
       "names\n",
       "</th>\n",
       "<th>\n",
       "random\n",
       "</th>\n",
       "<th>\n",
       "groups\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "f64\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",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "0.154163\n",
       "</td>\n",
       "<td>\n",
       "\"A\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"ham\"\n",
       "</td>\n",
       "<td>\n",
       "0.74\n",
       "</td>\n",
       "<td>\n",
       "\"A\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"spam\"\n",
       "</td>\n",
       "<td>\n",
       "0.263315\n",
       "</td>\n",
       "<td>\n",
       "\"B\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"egg\"\n",
       "</td>\n",
       "<td>\n",
       "0.533739\n",
       "</td>\n",
       "<td>\n",
       "\"C\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "0.014575\n",
       "</td>\n",
       "<td>\n",
       "\"B\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 4)\n",
       "┌──────┬───────┬──────────┬────────┐\n",
       "│ nrs  ┆ names ┆ random   ┆ groups │\n",
       "│ ---  ┆ ---   ┆ ---      ┆ ---    │\n",
       "│ i64  ┆ str   ┆ f64      ┆ str    │\n",
       "╞══════╪═══════╪══════════╪════════╡\n",
       "│ 1    ┆ foo   ┆ 0.154163 ┆ A      │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 2    ┆ ham   ┆ 0.74     ┆ A      │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 3    ┆ spam  ┆ 0.263315 ┆ B      │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ null ┆ egg   ┆ 0.533739 ┆ C      │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 5    ┆ null  ┆ 0.014575 ┆ B      │\n",
       "└──────┴───────┴──────────┴────────┘"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import polars as pl\n",
    "import numpy as np\n",
    "\n",
    "np.random.seed(12)\n",
    "\n",
    "df = pl.DataFrame(\n",
    "    {\n",
    "        \"nrs\": [1, 2, 3, None, 5],\n",
    "        \"names\": [\"foo\", \"ham\", \"spam\", \"egg\", None],\n",
    "        \"random\": np.random.rand(5),\n",
    "        \"groups\": [\"A\", \"A\", \"B\", \"C\", \"B\"],\n",
    "    }\n",
    ")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 表达式"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算唯一值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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",
       "unique_names_1\n",
       "</th>\n",
       "<th>\n",
       "unique_names_2\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (1, 2)\n",
       "┌────────────────┬────────────────┐\n",
       "│ unique_names_1 ┆ unique_names_2 │\n",
       "│ ---            ┆ ---            │\n",
       "│ u32            ┆ u32            │\n",
       "╞════════════════╪════════════════╡\n",
       "│ 5              ┆ 5              │\n",
       "└────────────────┴────────────────┘"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df.select(\n",
    "    [\n",
    "        pl.col(\"names\").n_unique().alias(\"unique_names_1\"),\n",
    "        # 计算name列中的唯一值，并把结果存为名为unique_names_1的列中\n",
    "        pl.col(\"names\").unique().count().alias(\"unique_names_2\"),\n",
    "    ]\n",
    ")\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 各种聚合"
   ]
  },
  {
   "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",
       "sum\n",
       "</th>\n",
       "<th>\n",
       "min\n",
       "</th>\n",
       "<th>\n",
       "max\n",
       "</th>\n",
       "<th>\n",
       "other_max\n",
       "</th>\n",
       "<th>\n",
       "std dev\n",
       "</th>\n",
       "<th>\n",
       "variance\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "f64\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",
       "1.705842\n",
       "</td>\n",
       "<td>\n",
       "0.014575\n",
       "</td>\n",
       "<td>\n",
       "0.74\n",
       "</td>\n",
       "<td>\n",
       "0.74\n",
       "</td>\n",
       "<td>\n",
       "0.293209\n",
       "</td>\n",
       "<td>\n",
       "0.085971\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (1, 6)\n",
       "┌──────────┬──────────┬──────┬───────────┬──────────┬──────────┐\n",
       "│ sum      ┆ min      ┆ max  ┆ other_max ┆ std dev  ┆ variance │\n",
       "│ ---      ┆ ---      ┆ ---  ┆ ---       ┆ ---      ┆ ---      │\n",
       "│ f64      ┆ f64      ┆ f64  ┆ f64       ┆ f64      ┆ f64      │\n",
       "╞══════════╪══════════╪══════╪═══════════╪══════════╪══════════╡\n",
       "│ 1.705842 ┆ 0.014575 ┆ 0.74 ┆ 0.74      ┆ 0.293209 ┆ 0.085971 │\n",
       "└──────────┴──────────┴──────┴───────────┴──────────┴──────────┘"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df.select(\n",
    "    [\n",
    "        pl.sum(\"random\").alias(\"sum\"), #对random列求和，并将结果存在sum列中\n",
    "        pl.min(\"random\").alias(\"min\"),\n",
    "        pl.max(\"random\").alias(\"max\"),\n",
    "        pl.col(\"random\").max().alias(\"other_max\"),\n",
    "        pl.std(\"random\").alias(\"std dev\"),\n",
    "        pl.var(\"random\").alias(\"variance\"),\n",
    "    ]\n",
    ")\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 过滤器和条件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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",
       "names\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (1, 1)\n",
       "┌───────┐\n",
       "│ names │\n",
       "│ ---   │\n",
       "│ u32   │\n",
       "╞═══════╡\n",
       "│ 2     │\n",
       "└───────┘"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df.select(\n",
    "    [\n",
    "        pl.col(\"names\").filter( #选出names列，然后按条件筛选\n",
    "            pl.col(\"names\").str.contains(r\"am$\")  # 条件为该列的值包含am字符\n",
    "        ).count(),\n",
    "    ]\n",
    ")\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 二进制函数和修改"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the example below   \n",
    "we use a conditional to create a new expression in the following  \n",
    " `when -> then -> otherwise` construct.  \n",
    "The `when` function requires a predicate expression(断言，可推导表达式) (and thus leads to a boolean Series).   \n",
    "The `then` function expects an expression that will be used in case the predicate evaluates to true,  \n",
    "and the `otherwise` function expects an expression that will be used in case the predicate evaluates to false."
   ]
  },
  {
   "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",
       "    }\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",
       "f64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "1.695791\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2.896465\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0.0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "0.160325\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 1)\n",
       "┌──────────┐\n",
       "│ literal  │\n",
       "│ ---      │\n",
       "│ f64      │\n",
       "╞══════════╡\n",
       "│ 1.695791 │\n",
       "├╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 0.0      │\n",
       "├╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2.896465 │\n",
       "├╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 0.0      │\n",
       "├╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 0.160325 │\n",
       "└──────────┘"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df.select(\n",
    "    [\n",
    "        pl.when(\n",
    "            pl.col(\"random\") > 0.5\n",
    "        ).then(0).otherwise( pl.col(\"random\") ) * pl.sum(\"nrs\"),\n",
    "        #如果random的值大于0.5，则取0\n",
    "        #否则，令值为random的值\n",
    "        #所有的结果乘以pl.sum(\"nrs\") = 11\n",
    "    ]\n",
    ")\n",
    "out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 注意，直接打印pl.sum(\"nrs\")是没用的\n",
    "df.select(\n",
    "    pl.sum(\"nrs\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 窗口表达式"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A polars expression can also do an implicit GROUPBY, AGGREGATION, and JOIN in a single expression.   \n",
    "In the examples below we do a GROUPBY OVER \"groups\" and AGGREGATE SUM of \"random\",   \n",
    "按groups列分组，然后对random列进行组内求和  \n",
    "and in the next expression we GROUPBY OVER \"names\" and AGGREGATE a LIST of \"random\".   \n",
    "按name列分组，然后对random列转为list  \n",
    "These window functions can be combined with other expressions and are an efficient way to determine group statistics.   \n",
    "See more on those group statistics here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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",
       "nrs\n",
       "</th>\n",
       "<th>\n",
       "names\n",
       "</th>\n",
       "<th>\n",
       "random\n",
       "</th>\n",
       "<th>\n",
       "groups\n",
       "</th>\n",
       "<th>\n",
       "sum[random]/groups\n",
       "</th>\n",
       "<th>\n",
       "random/name\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "f64\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",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "0.154163\n",
       "</td>\n",
       "<td>\n",
       "\"A\"\n",
       "</td>\n",
       "<td>\n",
       "0.894213\n",
       "</td>\n",
       "<td>\n",
       "[0.154163]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"ham\"\n",
       "</td>\n",
       "<td>\n",
       "0.74\n",
       "</td>\n",
       "<td>\n",
       "\"A\"\n",
       "</td>\n",
       "<td>\n",
       "0.894213\n",
       "</td>\n",
       "<td>\n",
       "[0.74]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"spam\"\n",
       "</td>\n",
       "<td>\n",
       "0.263315\n",
       "</td>\n",
       "<td>\n",
       "\"B\"\n",
       "</td>\n",
       "<td>\n",
       "0.2778\n",
       "</td>\n",
       "<td>\n",
       "[0.263315]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"egg\"\n",
       "</td>\n",
       "<td>\n",
       "0.533739\n",
       "</td>\n",
       "<td>\n",
       "\"C\"\n",
       "</td>\n",
       "<td>\n",
       "0.533739\n",
       "</td>\n",
       "<td>\n",
       "[0.533739]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "0.014575\n",
       "</td>\n",
       "<td>\n",
       "\"B\"\n",
       "</td>\n",
       "<td>\n",
       "0.2778\n",
       "</td>\n",
       "<td>\n",
       "[0.014575]\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 6)\n",
       "┌──────┬───────┬──────────┬────────┬────────────────────┬─────────────┐\n",
       "│ nrs  ┆ names ┆ random   ┆ groups ┆ sum[random]/groups ┆ random/name │\n",
       "│ ---  ┆ ---   ┆ ---      ┆ ---    ┆ ---                ┆ ---         │\n",
       "│ i64  ┆ str   ┆ f64      ┆ str    ┆ f64                ┆ list [f64]  │\n",
       "╞══════╪═══════╪══════════╪════════╪════════════════════╪═════════════╡\n",
       "│ 1    ┆ foo   ┆ 0.154163 ┆ A      ┆ 0.894213           ┆ [0.154163]  │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2    ┆ ham   ┆ 0.74     ┆ A      ┆ 0.894213           ┆ [0.74]      │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 3    ┆ spam  ┆ 0.263315 ┆ B      ┆ 0.2778             ┆ [0.263315]  │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ null ┆ egg   ┆ 0.533739 ┆ C      ┆ 0.533739           ┆ [0.533739]  │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 5    ┆ null  ┆ 0.014575 ┆ B      ┆ 0.2778             ┆ [0.014575]  │\n",
       "└──────┴───────┴──────────┴────────┴────────────────────┴─────────────┘"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df[\n",
    "    [\n",
    "        pl.col(\"*\"),  # select all，即输出结果的前4列\n",
    "        pl.col(\"random\").sum().over(\"groups\").alias(\"sum[random]/groups\"),\n",
    "        # \n",
    "        pl.col(\"random\").list().over(\"names\").alias(\"random/name\"),\n",
    "    ]\n",
    "]\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Expression contexts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 选择context"
   ]
  },
  {
   "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",
       "nrs\n",
       "</th>\n",
       "<th>\n",
       "names\n",
       "</th>\n",
       "<th>\n",
       "first name\n",
       "</th>\n",
       "<th>\n",
       "10xnrs\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",
       "<td>\n",
       "f64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "27.5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "\"egg\"\n",
       "</td>\n",
       "<td>\n",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "27.5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "27.5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "\"ham\"\n",
       "</td>\n",
       "<td>\n",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "27.5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "\"spam\"\n",
       "</td>\n",
       "<td>\n",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "27.5\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 4)\n",
       "┌─────┬───────┬────────────┬────────┐\n",
       "│ nrs ┆ names ┆ first name ┆ 10xnrs │\n",
       "│ --- ┆ ---   ┆ ---        ┆ ---    │\n",
       "│ i64 ┆ str   ┆ str        ┆ f64    │\n",
       "╞═════╪═══════╪════════════╪════════╡\n",
       "│ 11  ┆ null  ┆ foo        ┆ 27.5   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 11  ┆ egg   ┆ foo        ┆ 27.5   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 11  ┆ foo   ┆ foo        ┆ 27.5   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 11  ┆ ham   ┆ foo        ┆ 27.5   │\n",
       "├╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ 11  ┆ spam  ┆ foo        ┆ 27.5   │\n",
       "└─────┴───────┴────────────┴────────┘"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df.select(\n",
    "    [\n",
    "        pl.sum(\"nrs\"), #求和，被自动扩充\n",
    "        pl.col(\"names\").sort(),\n",
    "        pl.col(\"names\").first().alias(\"first name\"), # first()得到第一个元素\n",
    "        (pl.mean(\"nrs\") * 10).alias(\"10xnrs\"),\n",
    "    ]\n",
    ")\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 添加列df.with_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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",
       "nrs\n",
       "</th>\n",
       "<th>\n",
       "names\n",
       "</th>\n",
       "<th>\n",
       "random\n",
       "</th>\n",
       "<th>\n",
       "groups\n",
       "</th>\n",
       "<th>\n",
       "nrs_sum\n",
       "</th>\n",
       "<th>\n",
       "count\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "f64\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",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"foo\"\n",
       "</td>\n",
       "<td>\n",
       "0.154163\n",
       "</td>\n",
       "<td>\n",
       "\"A\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "\"ham\"\n",
       "</td>\n",
       "<td>\n",
       "0.74\n",
       "</td>\n",
       "<td>\n",
       "\"A\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "\"spam\"\n",
       "</td>\n",
       "<td>\n",
       "0.263315\n",
       "</td>\n",
       "<td>\n",
       "\"B\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"egg\"\n",
       "</td>\n",
       "<td>\n",
       "0.533739\n",
       "</td>\n",
       "<td>\n",
       "\"C\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "0.014575\n",
       "</td>\n",
       "<td>\n",
       "\"B\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 6)\n",
       "┌──────┬───────┬──────────┬────────┬─────────┬───────┐\n",
       "│ nrs  ┆ names ┆ random   ┆ groups ┆ nrs_sum ┆ count │\n",
       "│ ---  ┆ ---   ┆ ---      ┆ ---    ┆ ---     ┆ ---   │\n",
       "│ i64  ┆ str   ┆ f64      ┆ str    ┆ i64     ┆ u32   │\n",
       "╞══════╪═══════╪══════════╪════════╪═════════╪═══════╡\n",
       "│ 1    ┆ foo   ┆ 0.154163 ┆ A      ┆ 11      ┆ 5     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 2    ┆ ham   ┆ 0.74     ┆ A      ┆ 11      ┆ 5     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 3    ┆ spam  ┆ 0.263315 ┆ B      ┆ 11      ┆ 5     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ null ┆ egg   ┆ 0.533739 ┆ C      ┆ 11      ┆ 5     │\n",
       "├╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 5    ┆ null  ┆ 0.014575 ┆ B      ┆ 11      ┆ 5     │\n",
       "└──────┴───────┴──────────┴────────┴─────────┴───────┘"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df.with_columns(\n",
    "    [\n",
    "        pl.sum(\"nrs\").alias(\"nrs_sum\"),\n",
    "        pl.col(\"random\").count().alias(\"count\"),\n",
    "    ]\n",
    ")\n",
    "out\n",
    "# 示例代码有误"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分组上下文df.groupby().agg()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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",
       "nrs\n",
       "</th>\n",
       "<th>\n",
       "count\n",
       "</th>\n",
       "<th>\n",
       "random_sum\n",
       "</th>\n",
       "<th>\n",
       "reversed names\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "<td>\n",
       "f64\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",
       "8\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "0.263315\n",
       "</td>\n",
       "<td>\n",
       "[null, \"spam\"]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"A\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "0.894213\n",
       "</td>\n",
       "<td>\n",
       "[\"ham\", \"foo\"]\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"C\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "0.533739\n",
       "</td>\n",
       "<td>\n",
       "[\"egg\"]\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 5)\n",
       "┌────────┬──────┬───────┬────────────┬────────────────┐\n",
       "│ groups ┆ nrs  ┆ count ┆ random_sum ┆ reversed names │\n",
       "│ ---    ┆ ---  ┆ ---   ┆ ---        ┆ ---            │\n",
       "│ str    ┆ i64  ┆ u32   ┆ f64        ┆ list [str]     │\n",
       "╞════════╪══════╪═══════╪════════════╪════════════════╡\n",
       "│ B      ┆ 8    ┆ 2     ┆ 0.263315   ┆ [null, \"spam\"] │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ A      ┆ 3    ┆ 2     ┆ 0.894213   ┆ [\"ham\", \"foo\"] │\n",
       "├╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ C      ┆ null ┆ 1     ┆ 0.533739   ┆ [\"egg\"]        │\n",
       "└────────┴──────┴───────┴────────────┴────────────────┘"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = df.groupby(\"groups\").agg(\n",
    "    [\n",
    "        pl.sum(\"nrs\"),  # sum nrs by groups，对nrs分组求和\n",
    "        pl.col(\"random\").count().alias(\"count\"),  \n",
    "        # count group members\n",
    "        # 对random分组计数\n",
    "\n",
    "        pl.col(\"random\").filter(\n",
    "            pl.col(\"names\").is_not_null()\n",
    "        ).sum().suffix(\"_sum\"),\n",
    "        # sum random where name != null\n",
    "        # 如果name值不为空，就选出random的值，然后求和，并添加后缀名\n",
    "        \n",
    "        pl.col(\"names\").reverse().alias((\"reversed names\")),\n",
    "        # 反向排序\n",
    "    ]\n",
    ")\n",
    "out"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分组"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 导入数据\n",
    "说明，数据来自于 https://github.com/unitedstates/congress-legislators  \n",
    "但是直接下载整个包没啥数据\n",
    "我是在页面中选择\n",
    "|File|Download|Description|\n",
    "|:----|:----|:----|\n",
    "|legislators-current|YAML JSON CSV|Currently serving Members of Congress.|\n",
    "\n",
    "\n",
    "然后下载了其中的CSV文件\n",
    "\n",
    "用这个工具\n",
    "https://markdown-convert.com/zh/tool/table\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import polars as pl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "null\n",
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       "\"Benjamin\"\n",
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       "</td>\n",
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       "\"202-224-4524\"\n",
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       "<td>\n",
       "\"https://www.cardin.senate.gov/contact/\"\n",
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       "</td>\n",
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       "</td>\n",
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       "\"https://www.carper.senate.gov/public\"\n",
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       "\"202-224-2441\"\n",
       "</td>\n",
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       "\"https://www.carper.senate.gov/public/index.cfm/email-senator-carper\"\n",
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       "<td>\n",
       "300019\n",
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       "\"Tom Carper\"\n",
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       "<td>\n",
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       "<td>\n",
       "\"Tom Carper\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Casey\"\n",
       "</td>\n",
       "<td>\n",
       "\"Robert\"\n",
       "</td>\n",
       "<td>\n",
       "\"P.\"\n",
       "</td>\n",
       "<td>\n",
       "\"Jr.\"\n",
       "</td>\n",
       "<td>\n",
       "\"Bob\"\n",
       "</td>\n",
       "<td>\n",
       "\"Robert P. Casey, Jr.\"\n",
       "</td>\n",
       "<td>\n",
       "\"1960-04-13\"\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"PA\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.casey.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"393 Russell Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-6324\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.casey.senate.gov/contact\"\n",
       "</td>\n",
       "<td>\n",
       "\"http://www.casey.senate.gov/rss/feeds/?all\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenBobCasey\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorBobCasey\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorBobCasey\"\n",
       "</td>\n",
       "<td>\n",
       "\"UCtVssXhx-KuZa-hSvnsnJ0A\"\n",
       "</td>\n",
       "<td>\n",
       "\"C001070\"\n",
       "</td>\n",
       "<td>\n",
       "1828\n",
       "</td>\n",
       "<td>\n",
       "\"N00027503\"\n",
       "</td>\n",
       "<td>\n",
       "\"S309\"\n",
       "</td>\n",
       "<td>\n",
       "\"S6PA00217\"\n",
       "</td>\n",
       "<td>\n",
       "47036\n",
       "</td>\n",
       "<td>\n",
       "412246\n",
       "</td>\n",
       "<td>\n",
       "2541\n",
       "</td>\n",
       "<td>\n",
       "\"Bob Casey, Jr.\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "40703\n",
       "</td>\n",
       "<td>\n",
       "\"Bob Casey Jr.\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Feinstein\"\n",
       "</td>\n",
       "<td>\n",
       "\"Dianne\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"Dianne Feinstein\"\n",
       "</td>\n",
       "<td>\n",
       "\"1933-06-22\"\n",
       "</td>\n",
       "<td>\n",
       "\"F\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"CA\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.feinstein.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"331 Hart Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-3841\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.feinstein.senate.gov/public/index.cfm/e-mail-me\"\n",
       "</td>\n",
       "<td>\n",
       "\"http://www.feinstein.senate.gov/public/?a=rss.feed\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenFeinstein\"\n",
       "</td>\n",
       "<td>\n",
       "\"senatorfeinstein\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorFeinstein\"\n",
       "</td>\n",
       "<td>\n",
       "\"UCtVC--6LR0ff2aOP8THpuEw\"\n",
       "</td>\n",
       "<td>\n",
       "\"F000062\"\n",
       "</td>\n",
       "<td>\n",
       "1332\n",
       "</td>\n",
       "<td>\n",
       "\"N00007364\"\n",
       "</td>\n",
       "<td>\n",
       "\"S221\"\n",
       "</td>\n",
       "<td>\n",
       "\"S0CA00199\"\n",
       "</td>\n",
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       "13061\n",
       "</td>\n",
       "<td>\n",
       "300043\n",
       "</td>\n",
       "<td>\n",
       "53273\n",
       "</td>\n",
       "<td>\n",
       "\"Dianne Feinstein\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "49300\n",
       "</td>\n",
       "<td>\n",
       "\"Dianne Feinstein\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Klobuchar\"\n",
       "</td>\n",
       "<td>\n",
       "\"Amy\"\n",
       "</td>\n",
       "<td>\n",
       "\"Jean\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"Amy Klobuchar\"\n",
       "</td>\n",
       "<td>\n",
       "\"1960-05-25\"\n",
       "</td>\n",
       "<td>\n",
       "\"F\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"MN\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.klobuchar.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"425 Dirksen Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-3244\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.klobuchar.senate.gov/public/index.cfm/contact\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"SenAmyKlobuchar\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"senatorklobuchar\"\n",
       "</td>\n",
       "<td>\n",
       "\"UCvdeJsDsV51tFb_hVqvtYGA\"\n",
       "</td>\n",
       "<td>\n",
       "\"K000367\"\n",
       "</td>\n",
       "<td>\n",
       "1826\n",
       "</td>\n",
       "<td>\n",
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       "</td>\n",
       "<td>\n",
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       "</td>\n",
       "<td>\n",
       "412242\n",
       "</td>\n",
       "<td>\n",
       "65092\n",
       "</td>\n",
       "<td>\n",
       "\"Amy Klobuchar\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "40700\n",
       "</td>\n",
       "<td>\n",
       "\"Amy Klobuchar\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Menendez\"\n",
       "</td>\n",
       "<td>\n",
       "\"Robert\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"Bob\"\n",
       "</td>\n",
       "<td>\n",
       "\"Robert Menendez\"\n",
       "</td>\n",
       "<td>\n",
       "\"1954-01-01\"\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"NJ\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.menendez.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"528 Hart Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-4744\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.menendez.senate.gov/contact\"\n",
       "</td>\n",
       "<td>\n",
       "\"http://www.menendez.senate.gov/rss/feeds/index.cfm?type=news\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorMenendez\"\n",
       "</td>\n",
       "<td>\n",
       "\"senatormenendez\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorMenendezNJ\"\n",
       "</td>\n",
       "<td>\n",
       "\"UC0PV0K9Z5a9p3D5917KF5fw\"\n",
       "</td>\n",
       "<td>\n",
       "\"M000639\"\n",
       "</td>\n",
       "<td>\n",
       "791\n",
       "</td>\n",
       "<td>\n",
       "\"N00000699\"\n",
       "</td>\n",
       "<td>\n",
       "\"S306\"\n",
       "</td>\n",
       "<td>\n",
       "\"H2NJ13075,S6NJ00289\"\n",
       "</td>\n",
       "<td>\n",
       "29608\n",
       "</td>\n",
       "<td>\n",
       "400272\n",
       "</td>\n",
       "<td>\n",
       "26961\n",
       "</td>\n",
       "<td>\n",
       "\"Bob Menendez\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "29373\n",
       "</td>\n",
       "<td>\n",
       "\"Bob Menendez\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Sanders\"\n",
       "</td>\n",
       "<td>\n",
       "\"Bernard\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"Bernie\"\n",
       "</td>\n",
       "<td>\n",
       "\"Bernard Sanders\"\n",
       "</td>\n",
       "<td>\n",
       "\"1941-09-08\"\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"VT\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Independent\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.sanders.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"332 Dirksen Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-5141\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.sanders.senate.gov/contact/\"\n",
       "</td>\n",
       "<td>\n",
       "\"http://www.sanders.senate.gov/rss/\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenSanders\"\n",
       "</td>\n",
       "<td>\n",
       "\"senatorsanders\"\n",
       "</td>\n",
       "<td>\n",
       "\"senatorsanders\"\n",
       "</td>\n",
       "<td>\n",
       "\"UCD_DaKNac0Ta-2PeHuoQ1uA\"\n",
       "</td>\n",
       "<td>\n",
       "\"S000033\"\n",
       "</td>\n",
       "<td>\n",
       "1010\n",
       "</td>\n",
       "<td>\n",
       "\"N00000528\"\n",
       "</td>\n",
       "<td>\n",
       "\"S313\"\n",
       "</td>\n",
       "<td>\n",
       "\"H8VT01016,S4VT00033\"\n",
       "</td>\n",
       "<td>\n",
       "994\n",
       "</td>\n",
       "<td>\n",
       "400357\n",
       "</td>\n",
       "<td>\n",
       "27110\n",
       "</td>\n",
       "<td>\n",
       "\"Bernie Sanders\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "29147\n",
       "</td>\n",
       "<td>\n",
       "\"Bernie Sanders\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Stabenow\"\n",
       "</td>\n",
       "<td>\n",
       "\"Debbie\"\n",
       "</td>\n",
       "<td>\n",
       "\"Ann\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"Debbie Stabenow\"\n",
       "</td>\n",
       "<td>\n",
       "\"1950-04-29\"\n",
       "</td>\n",
       "<td>\n",
       "\"F\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"MI\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.stabenow.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"731 Hart Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-4822\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.stabenow.senate.gov/contact\"\n",
       "</td>\n",
       "<td>\n",
       "\"http://stabenow.senate.gov/rss/?p=news\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenStabenow\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorStabenow\"\n",
       "</td>\n",
       "<td>\n",
       "\"senatorstabenow\"\n",
       "</td>\n",
       "<td>\n",
       "\"UCFoDKCvxSwCUfDv-4Eg4K5A\"\n",
       "</td>\n",
       "<td>\n",
       "\"S000770\"\n",
       "</td>\n",
       "<td>\n",
       "1531\n",
       "</td>\n",
       "<td>\n",
       "\"N00004118\"\n",
       "</td>\n",
       "<td>\n",
       "\"S284\"\n",
       "</td>\n",
       "<td>\n",
       "\"S8MI00281,H6MI08163\"\n",
       "</td>\n",
       "<td>\n",
       "45451\n",
       "</td>\n",
       "<td>\n",
       "300093\n",
       "</td>\n",
       "<td>\n",
       "515\n",
       "</td>\n",
       "<td>\n",
       "\"Debbie Stabenow\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "29732\n",
       "</td>\n",
       "<td>\n",
       "\"Debbie Stabenow\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (10, 34)\n",
       "┌──────────┬──────────┬───────────┬────────┬─────┬────────────┬────────────┬──────────┬────────────┐\n",
       "│ last_nam ┆ first_na ┆ middle_na ┆ suffix ┆ ... ┆ ballotpedi ┆ washington ┆ icpsr_id ┆ wikipedia_ │\n",
       "│ e        ┆ me       ┆ me        ┆ ---    ┆     ┆ a_id       ┆ _post_id   ┆ ---      ┆ id         │\n",
       "│ ---      ┆ ---      ┆ ---       ┆ str    ┆     ┆ ---        ┆ ---        ┆ i64      ┆ ---        │\n",
       "│ str      ┆ str      ┆ str       ┆        ┆     ┆ str        ┆ str        ┆          ┆ str        │\n",
       "╞══════════╪══════════╪═══════════╪════════╪═════╪════════════╪════════════╪══════════╪════════════╡\n",
       "│ Brown    ┆ Sherrod  ┆ null      ┆ null   ┆ ... ┆ Sherrod    ┆ null       ┆ 29389    ┆ Sherrod    │\n",
       "│          ┆          ┆           ┆        ┆     ┆ Brown      ┆            ┆          ┆ Brown      │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Cantwell ┆ Maria    ┆ null      ┆ null   ┆ ... ┆ Maria      ┆ null       ┆ 39310    ┆ Maria      │\n",
       "│          ┆          ┆           ┆        ┆     ┆ Cantwell   ┆            ┆          ┆ Cantwell   │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Cardin   ┆ Benjamin ┆ L.        ┆ null   ┆ ... ┆ Ben Cardin ┆ null       ┆ 15408    ┆ Ben Cardin │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Carper   ┆ Thomas   ┆ Richard   ┆ null   ┆ ... ┆ Tom Carper ┆ null       ┆ 15015    ┆ Tom Carper │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ...      ┆ ...      ┆ ...       ┆ ...    ┆ ... ┆ ...        ┆ ...        ┆ ...      ┆ ...        │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Klobucha ┆ Amy      ┆ Jean      ┆ null   ┆ ... ┆ Amy        ┆ null       ┆ 40700    ┆ Amy        │\n",
       "│ r        ┆          ┆           ┆        ┆     ┆ Klobuchar  ┆            ┆          ┆ Klobuchar  │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Menendez ┆ Robert   ┆ null      ┆ null   ┆ ... ┆ Bob        ┆ null       ┆ 29373    ┆ Bob        │\n",
       "│          ┆          ┆           ┆        ┆     ┆ Menendez   ┆            ┆          ┆ Menendez   │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Sanders  ┆ Bernard  ┆ null      ┆ null   ┆ ... ┆ Bernie     ┆ null       ┆ 29147    ┆ Bernie     │\n",
       "│          ┆          ┆           ┆        ┆     ┆ Sanders    ┆            ┆          ┆ Sanders    │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Stabenow ┆ Debbie   ┆ Ann       ┆ null   ┆ ... ┆ Debbie     ┆ null       ┆ 29732    ┆ Debbie     │\n",
       "│          ┆          ┆           ┆        ┆     ┆ Stabenow   ┆            ┆          ┆ Stabenow   │\n",
       "└──────────┴──────────┴───────────┴────────┴─────┴────────────┴────────────┴──────────┴────────────┘"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = pl.read_csv('./dataset/legislators-current.csv')\n",
    "dataset.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['last_name',\n",
       " 'first_name',\n",
       " 'middle_name',\n",
       " 'suffix',\n",
       " 'nickname',\n",
       " 'full_name',\n",
       " 'birthday',\n",
       " 'gender',\n",
       " 'type',\n",
       " 'state',\n",
       " 'district',\n",
       " 'senate_class',\n",
       " 'party',\n",
       " 'url',\n",
       " 'address',\n",
       " 'phone',\n",
       " 'contact_form',\n",
       " 'rss_url',\n",
       " 'twitter',\n",
       " 'facebook',\n",
       " 'youtube',\n",
       " 'youtube_id',\n",
       " 'bioguide_id',\n",
       " 'thomas_id',\n",
       " 'opensecrets_id',\n",
       " 'lis_id',\n",
       " 'fec_ids',\n",
       " 'cspan_id',\n",
       " 'govtrack_id',\n",
       " 'votesmart_id',\n",
       " 'ballotpedia_id',\n",
       " 'washington_post_id',\n",
       " 'icpsr_id',\n",
       " 'wikipedia_id']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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",
       "first_name\n",
       "</th>\n",
       "<th>\n",
       "count\n",
       "</th>\n",
       "<th>\n",
       "gender\n",
       "</th>\n",
       "<th>\n",
       "last_name\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "<td>\n",
       "list\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"John\"\n",
       "</td>\n",
       "<td>\n",
       "19\n",
       "</td>\n",
       "<td>\n",
       "[\"M\", \"M\", ... \"M\"]\n",
       "</td>\n",
       "<td>\n",
       "\"Barrasso\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Mike\"\n",
       "</td>\n",
       "<td>\n",
       "13\n",
       "</td>\n",
       "<td>\n",
       "[\"M\", \"M\", ... \"M\"]\n",
       "</td>\n",
       "<td>\n",
       "\"Kelly\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Michael\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "[\"M\", \"M\", ... \"M\"]\n",
       "</td>\n",
       "<td>\n",
       "\"Bennet\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"David\"\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "<td>\n",
       "[\"M\", \"M\", ... \"M\"]\n",
       "</td>\n",
       "<td>\n",
       "\"Cicilline\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"James\"\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "[\"M\", \"M\", ... \"M\"]\n",
       "</td>\n",
       "<td>\n",
       "\"Inhofe\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 4)\n",
       "┌────────────┬───────┬─────────────────────┬───────────┐\n",
       "│ first_name ┆ count ┆ gender              ┆ last_name │\n",
       "│ ---        ┆ ---   ┆ ---                 ┆ ---       │\n",
       "│ str        ┆ u32   ┆ list [str]          ┆ str       │\n",
       "╞════════════╪═══════╪═════════════════════╪═══════════╡\n",
       "│ John       ┆ 19    ┆ [\"M\", \"M\", ... \"M\"] ┆ Barrasso  │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Mike       ┆ 13    ┆ [\"M\", \"M\", ... \"M\"] ┆ Kelly     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Michael    ┆ 11    ┆ [\"M\", \"M\", ... \"M\"] ┆ Bennet    │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ David      ┆ 10    ┆ [\"M\", \"M\", ... \"M\"] ┆ Cicilline │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ James      ┆ 9     ┆ [\"M\", \"M\", ... \"M\"] ┆ Inhofe    │\n",
       "└────────────┴───────┴─────────────────────┴───────────┘"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = (\n",
    "    dataset.lazy()\n",
    "    .groupby(\"first_name\") #按first_name列分组，即第2列\n",
    "    .agg(\n",
    "        [\n",
    "            pl.count(),               #组内计数\n",
    "            pl.col(\"gender\"),         #组内值列表化 .list()有没有都一样\n",
    "            pl.first(\"last_name\"),    #last_name列组内的第一个值\n",
    "        ]\n",
    "    )\n",
    "    .sort(\"count\", reverse=True)      #按上面聚合得到的count函数排序\n",
    "    .limit(5)                         #只取结果的前5行\n",
    ")\n",
    "# type(q)\n",
    "# polars.internals.lazy_frame.LazyFrame\n",
    "# 所以通过collect函数得到\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 条件句"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "假设我们想知道一个“州”有多少代表是民主党或共和党。  \n",
    "然后按Republican降序排序"
   ]
  },
  {
   "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",
       "state\n",
       "</th>\n",
       "<th>\n",
       "Democrat\n",
       "</th>\n",
       "<th>\n",
       "Republican\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"TX\"\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "<td>\n",
       "25\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"FL\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "<td>\n",
       "18\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"OH\"\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "13\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"PA\"\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"NC\"\n",
       "</td>\n",
       "<td>\n",
       "5\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"CA\"\n",
       "</td>\n",
       "<td>\n",
       "44\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"TN\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"IN\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"MO\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"SC\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (10, 3)\n",
       "┌───────┬──────────┬────────────┐\n",
       "│ state ┆ Democrat ┆ Republican │\n",
       "│ ---   ┆ ---      ┆ ---        │\n",
       "│ str   ┆ u32      ┆ u32        │\n",
       "╞═══════╪══════════╪════════════╡\n",
       "│ TX    ┆ 12       ┆ 25         │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ FL    ┆ 11       ┆ 18         │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ OH    ┆ 5        ┆ 13         │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ PA    ┆ 10       ┆ 10         │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ...   ┆ ...      ┆ ...        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ TN    ┆ 2        ┆ 9          │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ IN    ┆ 2        ┆ 9          │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ MO    ┆ 2        ┆ 8          │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ SC    ┆ 1        ┆ 8          │\n",
       "└───────┴──────────┴────────────┘"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = (\n",
    "    dataset.lazy()\n",
    "    .groupby(\"state\")\n",
    "    .agg(\n",
    "        [\n",
    "            (\n",
    "                pl.col(\"party\") == \"Democrat\"\n",
    "            ).sum().alias(\"Democrat\"),\n",
    "            (\n",
    "                pl.col(\"party\") == \"Republican\"\n",
    "            ).sum().alias(\"Republican\"),\n",
    "        ]\n",
    "    )\n",
    "    .sort(\"Republican\", reverse=True)\n",
    "    .limit(10)\n",
    ")\n",
    "\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上述代码的另一种实现方式：嵌套分组  \n",
    "这个逻辑我不是很喜欢"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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",
       "state\n",
       "</th>\n",
       "<th>\n",
       "party\n",
       "</th>\n",
       "<th>\n",
       "count\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"CA\"\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "44\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"TX\"\n",
       "</td>\n",
       "<td>\n",
       "\"Republican\"\n",
       "</td>\n",
       "<td>\n",
       "25\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"NY\"\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "21\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"FL\"\n",
       "</td>\n",
       "<td>\n",
       "\"Republican\"\n",
       "</td>\n",
       "<td>\n",
       "18\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"IL\"\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "15\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"OH\"\n",
       "</td>\n",
       "<td>\n",
       "\"Republican\"\n",
       "</td>\n",
       "<td>\n",
       "13\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"NJ\"\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"TX\"\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"MA\"\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"FL\"\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "11\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (10, 3)\n",
       "┌───────┬────────────┬───────┐\n",
       "│ state ┆ party      ┆ count │\n",
       "│ ---   ┆ ---        ┆ ---   │\n",
       "│ str   ┆ str        ┆ u32   │\n",
       "╞═══════╪════════════╪═══════╡\n",
       "│ CA    ┆ Democrat   ┆ 44    │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ TX    ┆ Republican ┆ 25    │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ NY    ┆ Democrat   ┆ 21    │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ FL    ┆ Republican ┆ 18    │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ ...   ┆ ...        ┆ ...   │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ NJ    ┆ Democrat   ┆ 12    │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ TX    ┆ Democrat   ┆ 12    │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ MA    ┆ Democrat   ┆ 11    │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ FL    ┆ Democrat   ┆ 11    │\n",
       "└───────┴────────────┴───────┘"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = (\n",
    "    dataset.lazy()\n",
    "    .groupby([\"state\", \"party\"])\n",
    "    .agg( \n",
    "            [pl.count(\"party\").alias(\"count\")]\n",
    "        )    # 至此已经完成分组，并设定要求为计数\n",
    "    .filter( # 设定在上面的基础上的计数对象\n",
    "        (pl.col(\"party\") == \"Democrat\") | \n",
    "            (pl.col(\"party\") == \"Republican\")\n",
    "    )\n",
    "    .sort(\"count\", reverse=True)\n",
    "    .limit(10)\n",
    ")\n",
    "\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 过滤"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在解决问题之前，学下时间处理的知识  \n",
    "否则代码会报错  \n",
    "下面的代码，我们将date列转换为时间格式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1 \"class=\"dataframe \">\n",
       "<thead>\n",
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       "<th>\n",
       "date\n",
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       "b_squared\n",
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       "str\n",
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       "<td>\n",
       "i64\n",
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       "</td>\n",
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       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"2020-01-02\"\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "2020-01-02\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"2020-01-03\"\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "2020-01-03\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"2020-01-04\"\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "2020-01-04\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 3)\n",
       "┌────────────┬───────┬────────────┐\n",
       "│ date       ┆ index ┆ b_squared  │\n",
       "│ ---        ┆ ---   ┆ ---        │\n",
       "│ str        ┆ i64   ┆ date       │\n",
       "╞════════════╪═══════╪════════════╡\n",
       "│ 2020-01-02 ┆ 1     ┆ 2020-01-02 │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2020-01-03 ┆ 2     ┆ 2020-01-03 │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ 2020-01-04 ┆ 3     ┆ 2020-01-04 │\n",
       "└────────────┴───────┴────────────┘"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import polars as pl\n",
    "\n",
    "dated = pl.DataFrame(\n",
    "    {\n",
    "        \"date\": [\"2020-01-02\", \"2020-01-03\", \"2020-01-04\"], \n",
    "        \"index\": [1, 2, 3]\n",
    "    }\n",
    ")\n",
    "\n",
    "# 注意，这里with_column比较好用\n",
    "# 本来是新增一列的，但是，如果我们没有使用alias，则会是替换掉原来的同名列\n",
    "q = dated.lazy().with_column(\n",
    "        pl.col(\"date\").str.strptime(pl.Date, \"%Y-%m-%d\").alias(\"b_squared\")\n",
    "    )\n",
    "\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果使用select，则应书写如下"
   ]
  },
  {
   "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",
       "date\n",
       "</th>\n",
       "<th>\n",
       "index\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",
       "2020-01-02\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2020-01-03\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2020-01-04\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 2)\n",
       "┌────────────┬───────┐\n",
       "│ date       ┆ index │\n",
       "│ ---        ┆ ---   │\n",
       "│ date       ┆ i64   │\n",
       "╞════════════╪═══════╡\n",
       "│ 2020-01-02 ┆ 1     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 2020-01-03 ┆ 2     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 2020-01-04 ┆ 3     │\n",
       "└────────────┴───────┘"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = dated.lazy().select(\n",
    "        [\n",
    "        pl.col(\"date\").str.strptime(pl.Date, \"%Y-%m-%d\"),\n",
    "        pl.col('index'),\n",
    "        ]\n",
    "    )\n",
    "\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[polars.datatypes.Date, polars.datatypes.Int64]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes\n",
    "# polars.datatypes.Date"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下面就是年月日时分秒的形式  \n",
    "其中format可以查看datetime的api或者rust的api"
   ]
  },
  {
   "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",
       "index\n",
       "</th>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "datetime\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "2020-01-02 01:11:11\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2020-01-03 02:22:22\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "2020-01-04 03:33:33\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 2)\n",
       "┌─────────────────────┬───────┐\n",
       "│ date                ┆ index │\n",
       "│ ---                 ┆ ---   │\n",
       "│ datetime[μs]        ┆ i64   │\n",
       "╞═════════════════════╪═══════╡\n",
       "│ 2020-01-02 01:11:11 ┆ 1     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 2020-01-03 02:22:22 ┆ 2     │\n",
       "├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌┤\n",
       "│ 2020-01-04 03:33:33 ┆ 3     │\n",
       "└─────────────────────┴───────┘"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import polars as pl\n",
    "\n",
    "dated = pl.DataFrame(\n",
    "    {\n",
    "        \"date\": [\"2020-01-02 01:11:11\", \"2020-01-03 02:22:22\", \"2020-01-04 03:33:33\"], \n",
    "        \"index\": [1, 2, 3]\n",
    "    }\n",
    ")\n",
    "\n",
    "q = dated.lazy().with_column(\n",
    "        pl.col(\"date\").str.strptime(pl.Datetime, \"%Y-%m-%d %H:%M:%S\")\n",
    "    )\n",
    "\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "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",
       "last_name\n",
       "</th>\n",
       "<th>\n",
       "first_name\n",
       "</th>\n",
       "<th>\n",
       "middle_name\n",
       "</th>\n",
       "<th>\n",
       "suffix\n",
       "</th>\n",
       "<th>\n",
       "nickname\n",
       "</th>\n",
       "<th>\n",
       "full_name\n",
       "</th>\n",
       "<th>\n",
       "birthday\n",
       "</th>\n",
       "<th>\n",
       "gender\n",
       "</th>\n",
       "<th>\n",
       "type\n",
       "</th>\n",
       "<th>\n",
       "state\n",
       "</th>\n",
       "<th>\n",
       "district\n",
       "</th>\n",
       "<th>\n",
       "senate_class\n",
       "</th>\n",
       "<th>\n",
       "party\n",
       "</th>\n",
       "<th>\n",
       "url\n",
       "</th>\n",
       "<th>\n",
       "address\n",
       "</th>\n",
       "<th>\n",
       "phone\n",
       "</th>\n",
       "<th>\n",
       "contact_form\n",
       "</th>\n",
       "<th>\n",
       "rss_url\n",
       "</th>\n",
       "<th>\n",
       "twitter\n",
       "</th>\n",
       "<th>\n",
       "facebook\n",
       "</th>\n",
       "<th>\n",
       "youtube\n",
       "</th>\n",
       "<th>\n",
       "youtube_id\n",
       "</th>\n",
       "<th>\n",
       "bioguide_id\n",
       "</th>\n",
       "<th>\n",
       "thomas_id\n",
       "</th>\n",
       "<th>\n",
       "opensecrets_id\n",
       "</th>\n",
       "<th>\n",
       "lis_id\n",
       "</th>\n",
       "<th>\n",
       "fec_ids\n",
       "</th>\n",
       "<th>\n",
       "cspan_id\n",
       "</th>\n",
       "<th>\n",
       "govtrack_id\n",
       "</th>\n",
       "<th>\n",
       "votesmart_id\n",
       "</th>\n",
       "<th>\n",
       "ballotpedia_id\n",
       "</th>\n",
       "<th>\n",
       "washington_post_id\n",
       "</th>\n",
       "<th>\n",
       "icpsr_id\n",
       "</th>\n",
       "<th>\n",
       "wikipedia_id\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",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "date\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\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",
       "<td>\n",
       "str\n",
       "</td>\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",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "<td>\n",
       "i64\n",
       "</td>\n",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"Brown\"\n",
       "</td>\n",
       "<td>\n",
       "\"Sherrod\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"Sherrod Brown\"\n",
       "</td>\n",
       "<td>\n",
       "1952-11-09\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"OH\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.brown.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"503 Hart Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-2315\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.brown.senate.gov/contact/\"\n",
       "</td>\n",
       "<td>\n",
       "\"http://www.brown.senate.gov/rss/feeds/?type=all&amp;\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenSherrodBrown\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorSherrodBrown\"\n",
       "</td>\n",
       "<td>\n",
       "\"SherrodBrownOhio\"\n",
       "</td>\n",
       "<td>\n",
       "\"UCgy8jfERh-t_ixkKKoCmglQ\"\n",
       "</td>\n",
       "<td>\n",
       "\"B000944\"\n",
       "</td>\n",
       "<td>\n",
       "136\n",
       "</td>\n",
       "<td>\n",
       "\"N00003535\"\n",
       "</td>\n",
       "<td>\n",
       "\"S307\"\n",
       "</td>\n",
       "<td>\n",
       "\"H2OH13033,S6OH00163\"\n",
       "</td>\n",
       "<td>\n",
       "5051\n",
       "</td>\n",
       "<td>\n",
       "400050\n",
       "</td>\n",
       "<td>\n",
       "27018\n",
       "</td>\n",
       "<td>\n",
       "\"Sherrod Brown\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "29389\n",
       "</td>\n",
       "<td>\n",
       "\"Sherrod Brown\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Cantwell\"\n",
       "</td>\n",
       "<td>\n",
       "\"Maria\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"Maria Cantwell\"\n",
       "</td>\n",
       "<td>\n",
       "1958-10-13\n",
       "</td>\n",
       "<td>\n",
       "\"F\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"WA\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.cantwell.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"511 Hart Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-3441\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.cantwell.senate.gov/public/index.cfm/email-maria\"\n",
       "</td>\n",
       "<td>\n",
       "\"http://www.cantwell.senate.gov/public/index.cfm/rss/feed\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorCantwell\"\n",
       "</td>\n",
       "<td>\n",
       "\"senatorcantwell\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorCantwell\"\n",
       "</td>\n",
       "<td>\n",
       "\"UCN52UDqKgvHRk39ncySrIMw\"\n",
       "</td>\n",
       "<td>\n",
       "\"C000127\"\n",
       "</td>\n",
       "<td>\n",
       "172\n",
       "</td>\n",
       "<td>\n",
       "\"N00007836\"\n",
       "</td>\n",
       "<td>\n",
       "\"S275\"\n",
       "</td>\n",
       "<td>\n",
       "\"S8WA00194,H2WA01054\"\n",
       "</td>\n",
       "<td>\n",
       "26137\n",
       "</td>\n",
       "<td>\n",
       "300018\n",
       "</td>\n",
       "<td>\n",
       "27122\n",
       "</td>\n",
       "<td>\n",
       "\"Maria Cantwell\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "39310\n",
       "</td>\n",
       "<td>\n",
       "\"Maria Cantwell\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"Cardin\"\n",
       "</td>\n",
       "<td>\n",
       "\"Benjamin\"\n",
       "</td>\n",
       "<td>\n",
       "\"L.\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "\"Benjamin L. Cardin\"\n",
       "</td>\n",
       "<td>\n",
       "1943-10-05\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "<td>\n",
       "\"sen\"\n",
       "</td>\n",
       "<td>\n",
       "\"MD\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "\"Democrat\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.cardin.senate.gov\"\n",
       "</td>\n",
       "<td>\n",
       "\"509 Hart Senate Office Building Washington DC 20510\"\n",
       "</td>\n",
       "<td>\n",
       "\"202-224-4524\"\n",
       "</td>\n",
       "<td>\n",
       "\"https://www.cardin.senate.gov/contact/\"\n",
       "</td>\n",
       "<td>\n",
       "\"http://www.cardin.senate.gov/rss/feeds/?type=all\"\n",
       "</td>\n",
       "<td>\n",
       "\"SenatorCardin\"\n",
       "</td>\n",
       "<td>\n",
       "\"senatorbencardin\"\n",
       "</td>\n",
       "<td>\n",
       "\"senatorcardin\"\n",
       "</td>\n",
       "<td>\n",
       "\"UCiQaJnMzlfzzG3VESgyZChA\"\n",
       "</td>\n",
       "<td>\n",
       "\"C000141\"\n",
       "</td>\n",
       "<td>\n",
       "174\n",
       "</td>\n",
       "<td>\n",
       "\"N00001955\"\n",
       "</td>\n",
       "<td>\n",
       "\"S308\"\n",
       "</td>\n",
       "<td>\n",
       "\"H6MD03177,S6MD03177\"\n",
       "</td>\n",
       "<td>\n",
       "4004\n",
       "</td>\n",
       "<td>\n",
       "400064\n",
       "</td>\n",
       "<td>\n",
       "26888\n",
       "</td>\n",
       "<td>\n",
       "\"Ben Cardin\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "15408\n",
       "</td>\n",
       "<td>\n",
       "\"Ben Cardin\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (3, 34)\n",
       "┌──────────┬──────────┬───────────┬────────┬─────┬────────────┬────────────┬──────────┬────────────┐\n",
       "│ last_nam ┆ first_na ┆ middle_na ┆ suffix ┆ ... ┆ ballotpedi ┆ washington ┆ icpsr_id ┆ wikipedia_ │\n",
       "│ e        ┆ me       ┆ me        ┆ ---    ┆     ┆ a_id       ┆ _post_id   ┆ ---      ┆ id         │\n",
       "│ ---      ┆ ---      ┆ ---       ┆ str    ┆     ┆ ---        ┆ ---        ┆ i64      ┆ ---        │\n",
       "│ str      ┆ str      ┆ str       ┆        ┆     ┆ str        ┆ str        ┆          ┆ str        │\n",
       "╞══════════╪══════════╪═══════════╪════════╪═════╪════════════╪════════════╪══════════╪════════════╡\n",
       "│ Brown    ┆ Sherrod  ┆ null      ┆ null   ┆ ... ┆ Sherrod    ┆ null       ┆ 29389    ┆ Sherrod    │\n",
       "│          ┆          ┆           ┆        ┆     ┆ Brown      ┆            ┆          ┆ Brown      │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Cantwell ┆ Maria    ┆ null      ┆ null   ┆ ... ┆ Maria      ┆ null       ┆ 39310    ┆ Maria      │\n",
       "│          ┆          ┆           ┆        ┆     ┆ Cantwell   ┆            ┆          ┆ Cantwell   │\n",
       "├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ Cardin   ┆ Benjamin ┆ L.        ┆ null   ┆ ... ┆ Ben Cardin ┆ null       ┆ 15408    ┆ Ben Cardin │\n",
       "└──────────┴──────────┴───────────┴────────┴─────┴────────────┴────────────┴──────────┴────────────┘"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = dataset.lazy().with_column(\n",
    "        pl.col(\"birthday\").str.strptime(pl.Date, \"%Y-%m-%d\")\n",
    "    )\n",
    "\n",
    "datasetn = q.collect()\n",
    "datasetn.head(3)"
   ]
  },
  {
   "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",
       "state\n",
       "</th>\n",
       "<th>\n",
       "avg M birthday\n",
       "</th>\n",
       "<th>\n",
       "avg F birthday\n",
       "</th>\n",
       "<th>\n",
       "# male\n",
       "</th>\n",
       "<th>\n",
       "# female\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",
       "u32\n",
       "</td>\n",
       "<td>\n",
       "u32\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"OH\"\n",
       "</td>\n",
       "<td>\n",
       "59.466667\n",
       "</td>\n",
       "<td>\n",
       "64.0\n",
       "</td>\n",
       "<td>\n",
       "18\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"WA\"\n",
       "</td>\n",
       "<td>\n",
       "56.25\n",
       "</td>\n",
       "<td>\n",
       "57.0\n",
       "</td>\n",
       "<td>\n",
       "12\n",
       "</td>\n",
       "<td>\n",
       "8\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"MD\"\n",
       "</td>\n",
       "<td>\n",
       "67.8\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "10\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"DE\"\n",
       "</td>\n",
       "<td>\n",
       "66.0\n",
       "</td>\n",
       "<td>\n",
       "59.0\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"PA\"\n",
       "</td>\n",
       "<td>\n",
       "56.9375\n",
       "</td>\n",
       "<td>\n",
       "60.5\n",
       "</td>\n",
       "<td>\n",
       "20\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"CA\"\n",
       "</td>\n",
       "<td>\n",
       "57.323529\n",
       "</td>\n",
       "<td>\n",
       "67.75\n",
       "</td>\n",
       "<td>\n",
       "54\n",
       "</td>\n",
       "<td>\n",
       "20\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"MN\"\n",
       "</td>\n",
       "<td>\n",
       "55.666667\n",
       "</td>\n",
       "<td>\n",
       "56.0\n",
       "</td>\n",
       "<td>\n",
       "9\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"NJ\"\n",
       "</td>\n",
       "<td>\n",
       "62.166667\n",
       "</td>\n",
       "<td>\n",
       "62.5\n",
       "</td>\n",
       "<td>\n",
       "14\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"VT\"\n",
       "</td>\n",
       "<td>\n",
       "78.333333\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"MI\"\n",
       "</td>\n",
       "<td>\n",
       "60.444444\n",
       "</td>\n",
       "<td>\n",
       "55.571429\n",
       "</td>\n",
       "<td>\n",
       "16\n",
       "</td>\n",
       "<td>\n",
       "7\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"MT\"\n",
       "</td>\n",
       "<td>\n",
       "61.666667\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"RI\"\n",
       "</td>\n",
       "<td>\n",
       "63.75\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "<td>\n",
       "...\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"UT\"\n",
       "</td>\n",
       "<td>\n",
       "59.5\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"KS\"\n",
       "</td>\n",
       "<td>\n",
       "54.2\n",
       "</td>\n",
       "<td>\n",
       "41.0\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"AK\"\n",
       "</td>\n",
       "<td>\n",
       "57.0\n",
       "</td>\n",
       "<td>\n",
       "64.0\n",
       "</td>\n",
       "<td>\n",
       "2\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"DC\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "84.0\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"MP\"\n",
       "</td>\n",
       "<td>\n",
       "66.0\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"NE\"\n",
       "</td>\n",
       "<td>\n",
       "52.666667\n",
       "</td>\n",
       "<td>\n",
       "70.0\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"SD\"\n",
       "</td>\n",
       "<td>\n",
       "57.333333\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "3\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"NV\"\n",
       "</td>\n",
       "<td>\n",
       "55.5\n",
       "</td>\n",
       "<td>\n",
       "61.75\n",
       "</td>\n",
       "<td>\n",
       "6\n",
       "</td>\n",
       "<td>\n",
       "4\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"VI\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "55.0\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"AS\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "74.0\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"PR\"\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "45.0\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"GU\"\n",
       "</td>\n",
       "<td>\n",
       "40.0\n",
       "</td>\n",
       "<td>\n",
       "null\n",
       "</td>\n",
       "<td>\n",
       "1\n",
       "</td>\n",
       "<td>\n",
       "0\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (56, 5)\n",
       "┌───────┬────────────────┬────────────────┬────────┬──────────┐\n",
       "│ state ┆ avg M birthday ┆ avg F birthday ┆ # male ┆ # female │\n",
       "│ ---   ┆ ---            ┆ ---            ┆ ---    ┆ ---      │\n",
       "│ str   ┆ f64            ┆ f64            ┆ u32    ┆ u32      │\n",
       "╞═══════╪════════════════╪════════════════╪════════╪══════════╡\n",
       "│ OH    ┆ 59.466667      ┆ 64.0           ┆ 18     ┆ 3        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ WA    ┆ 56.25          ┆ 57.0           ┆ 12     ┆ 8        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ MD    ┆ 67.8           ┆ null           ┆ 10     ┆ 0        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ DE    ┆ 66.0           ┆ 59.0           ┆ 3      ┆ 1        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ...   ┆ ...            ┆ ...            ┆ ...    ┆ ...      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ VI    ┆ null           ┆ 55.0           ┆ 1      ┆ 1        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ AS    ┆ null           ┆ 74.0           ┆ 1      ┆ 1        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ PR    ┆ null           ┆ 45.0           ┆ 1      ┆ 1        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ GU    ┆ 40.0           ┆ null           ┆ 1      ┆ 0        │\n",
       "└───────┴────────────────┴────────────────┴────────┴──────────┘"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import date\n",
    "\n",
    "# 计算截止到2021.1.1的年龄\n",
    "def compute_age() -> pl.Expr:\n",
    "    # 函数后面跟着的-> pl.Expr是函数返回值的类型建议符，\n",
    "    # 用来说明该函数返回的值是什么类型。\n",
    "    # 返回出生日期距离2021,。1.1的天数\n",
    "    return date(2021, 1, 1).year - pl.col(\"birthday\").dt.year()\n",
    "\n",
    "# 计算性别=gender的组内均值\n",
    "def avg_birthday(gender: str) -> pl.Expr:\n",
    "    return compute_age().filter(\n",
    "            pl.col(\"gender\") == gender\n",
    "        ).mean().alias(f\"avg {gender} birthday\")\n",
    "\n",
    "\n",
    "q = (\n",
    "    datasetn.lazy()\n",
    "    .groupby([\"state\"],maintain_order=True)\n",
    "    .agg(\n",
    "        [\n",
    "            avg_birthday(\"M\"), #女性年龄均值\n",
    "            avg_birthday(\"F\"),\n",
    "            (pl.col(\"gender\") == \"M\").count().alias(\"# male\"), #女性的数量\n",
    "            (pl.col(\"gender\") == \"F\").sum().alias(\"# female\"),\n",
    "        ]\n",
    "    )\n",
    ")\n",
    "# 卡住我了。\n",
    "# 1 为啥要对lpsum\n",
    "# 2 为啥每次输出的结果在随机变化，是因为并行了吧\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于并行的原因，结果每次都不通  \n",
    "所以如果需要每次结果都相同，则要使用下面的语句\n",
    "> \n",
    "> ```python\n",
    "> .groupby([\"state\"],maintain_order=True)\n",
    "> ```\n",
    "\n",
    "但是这会增加计算时间的开销"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 排序"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "假设我们想得到每个州最年长和最年轻的政治家的名字。"
   ]
  },
  {
   "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",
       "state\n",
       "</th>\n",
       "<th>\n",
       "youngest\n",
       "</th>\n",
       "<th>\n",
       "oldest\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",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"CA\"\n",
       "</td>\n",
       "<td>\n",
       "\"Dianne Feinstein\"\n",
       "</td>\n",
       "<td>\n",
       "\"Sara Jacobs\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"NM\"\n",
       "</td>\n",
       "<td>\n",
       "\"Teresa Leger Fernandez\"\n",
       "</td>\n",
       "<td>\n",
       "\"Melanie Stansbury\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"ID\"\n",
       "</td>\n",
       "<td>\n",
       "\"James Risch\"\n",
       "</td>\n",
       "<td>\n",
       "\"Russ Fulcher\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"VT\"\n",
       "</td>\n",
       "<td>\n",
       "\"Patrick Leahy\"\n",
       "</td>\n",
       "<td>\n",
       "\"Peter Welch\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"GA\"\n",
       "</td>\n",
       "<td>\n",
       "\"David Scott\"\n",
       "</td>\n",
       "<td>\n",
       "\"Jon Ossoff\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 3)\n",
       "┌───────┬────────────────────────┬───────────────────┐\n",
       "│ state ┆ youngest               ┆ oldest            │\n",
       "│ ---   ┆ ---                    ┆ ---               │\n",
       "│ str   ┆ str                    ┆ str               │\n",
       "╞═══════╪════════════════════════╪═══════════════════╡\n",
       "│ CA    ┆ Dianne Feinstein       ┆ Sara Jacobs       │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ NM    ┆ Teresa Leger Fernandez ┆ Melanie Stansbury │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ ID    ┆ James Risch            ┆ Russ Fulcher      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ VT    ┆ Patrick Leahy          ┆ Peter Welch       │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ GA    ┆ David Scott            ┆ Jon Ossoff        │\n",
       "└───────┴────────────────────────┴───────────────────┘"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_person() -> pl.Expr:\n",
    "    return pl.col(\"first_name\") + pl.lit(\" \") + pl.col(\"last_name\")\n",
    "\n",
    "#\n",
    "q = (\n",
    "    dataset.lazy()\n",
    "    .sort(\"birthday\")\n",
    "    .groupby([\"state\"])\n",
    "    .agg(\n",
    "        [\n",
    "            get_person().first().alias(\"youngest\"),\n",
    "            get_person().last().alias(\"oldest\"),\n",
    "        ]\n",
    "    )\n",
    "    .limit(5)\n",
    ")\n",
    "\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果我们还想按字母顺序对名称进行排序"
   ]
  },
  {
   "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",
       "    }\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",
       "state\n",
       "</th>\n",
       "<th>\n",
       "youngest\n",
       "</th>\n",
       "<th>\n",
       "oldest\n",
       "</th>\n",
       "<th>\n",
       "alphabetical_first\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",
       "\"VT\"\n",
       "</td>\n",
       "<td>\n",
       "\"Patrick Leahy\"\n",
       "</td>\n",
       "<td>\n",
       "\"Peter Welch\"\n",
       "</td>\n",
       "<td>\n",
       "\"Bernard Sanders\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"TX\"\n",
       "</td>\n",
       "<td>\n",
       "\"Eddie Johnson\"\n",
       "</td>\n",
       "<td>\n",
       "\"Dan Crenshaw\"\n",
       "</td>\n",
       "<td>\n",
       "\"Al Green\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"GA\"\n",
       "</td>\n",
       "<td>\n",
       "\"David Scott\"\n",
       "</td>\n",
       "<td>\n",
       "\"Jon Ossoff\"\n",
       "</td>\n",
       "<td>\n",
       "\"A. Ferguson\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"LA\"\n",
       "</td>\n",
       "<td>\n",
       "\"John Kennedy\"\n",
       "</td>\n",
       "<td>\n",
       "\"Julia Letlow\"\n",
       "</td>\n",
       "<td>\n",
       "\"Bill Cassidy\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"SC\"\n",
       "</td>\n",
       "<td>\n",
       "\"James Clyburn\"\n",
       "</td>\n",
       "<td>\n",
       "\"William Timmons\"\n",
       "</td>\n",
       "<td>\n",
       "\"James Clyburn\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 4)\n",
       "┌───────┬───────────────┬─────────────────┬────────────────────┐\n",
       "│ state ┆ youngest      ┆ oldest          ┆ alphabetical_first │\n",
       "│ ---   ┆ ---           ┆ ---             ┆ ---                │\n",
       "│ str   ┆ str           ┆ str             ┆ str                │\n",
       "╞═══════╪═══════════════╪═════════════════╪════════════════════╡\n",
       "│ VT    ┆ Patrick Leahy ┆ Peter Welch     ┆ Bernard Sanders    │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ TX    ┆ Eddie Johnson ┆ Dan Crenshaw    ┆ Al Green           │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ GA    ┆ David Scott   ┆ Jon Ossoff      ┆ A. Ferguson        │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ LA    ┆ John Kennedy  ┆ Julia Letlow    ┆ Bill Cassidy       │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤\n",
       "│ SC    ┆ James Clyburn ┆ William Timmons ┆ James Clyburn      │\n",
       "└───────┴───────────────┴─────────────────┴────────────────────┘"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_person() -> pl.Expr:\n",
    "    return pl.col(\"first_name\") + pl.lit(\" \") + pl.col(\"last_name\")\n",
    "\n",
    "\n",
    "q = (\n",
    "    dataset.lazy()\n",
    "    .sort(\"birthday\")\n",
    "    .groupby([\"state\"])\n",
    "    .agg(\n",
    "        [\n",
    "            get_person().first().alias(\"youngest\"),\n",
    "            get_person().last().alias(\"oldest\"),\n",
    "            get_person().sort().first().alias(\"alphabetical_first\"),\n",
    "        ]\n",
    "    )\n",
    "    .limit(5)\n",
    ")\n",
    "\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们甚至可以按groupby上下文中的另一列进行排序。 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果我们还想知道按字母顺序排列的第一个名字名字对应的人是男性还是女性"
   ]
  },
  {
   "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",
       "state\n",
       "</th>\n",
       "<th>\n",
       "youngest\n",
       "</th>\n",
       "<th>\n",
       "oldest\n",
       "</th>\n",
       "<th>\n",
       "alphabetical_first\n",
       "</th>\n",
       "<th>\n",
       "gender\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",
       "<td>\n",
       "str\n",
       "</td>\n",
       "</tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr>\n",
       "<td>\n",
       "\"AK\"\n",
       "</td>\n",
       "<td>\n",
       "\"Lisa Murkowski\"\n",
       "</td>\n",
       "<td>\n",
       "\"Dan Sullivan\"\n",
       "</td>\n",
       "<td>\n",
       "\"Dan Sullivan\"\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"AL\"\n",
       "</td>\n",
       "<td>\n",
       "\"Richard Shelby\"\n",
       "</td>\n",
       "<td>\n",
       "\"Barry Moore\"\n",
       "</td>\n",
       "<td>\n",
       "\"Barry Moore\"\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"AR\"\n",
       "</td>\n",
       "<td>\n",
       "\"John Boozman\"\n",
       "</td>\n",
       "<td>\n",
       "\"Tom Cotton\"\n",
       "</td>\n",
       "<td>\n",
       "\"Bruce Westerman\"\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"AS\"\n",
       "</td>\n",
       "<td>\n",
       "\"Aumua Amata Radewagen\"\n",
       "</td>\n",
       "<td>\n",
       "\"Aumua Amata Radewagen\"\n",
       "</td>\n",
       "<td>\n",
       "\"Aumua Amata Radewagen\"\n",
       "</td>\n",
       "<td>\n",
       "\"F\"\n",
       "</td>\n",
       "</tr>\n",
       "<tr>\n",
       "<td>\n",
       "\"AZ\"\n",
       "</td>\n",
       "<td>\n",
       "\"Tom O’Halleran\"\n",
       "</td>\n",
       "<td>\n",
       "\"Ruben Gallego\"\n",
       "</td>\n",
       "<td>\n",
       "\"Andy Biggs\"\n",
       "</td>\n",
       "<td>\n",
       "\"M\"\n",
       "</td>\n",
       "</tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "shape: (5, 5)\n",
       "┌───────┬───────────────────────┬───────────────────────┬───────────────────────┬────────┐\n",
       "│ state ┆ youngest              ┆ oldest                ┆ alphabetical_first    ┆ gender │\n",
       "│ ---   ┆ ---                   ┆ ---                   ┆ ---                   ┆ ---    │\n",
       "│ str   ┆ str                   ┆ str                   ┆ str                   ┆ str    │\n",
       "╞═══════╪═══════════════════════╪═══════════════════════╪═══════════════════════╪════════╡\n",
       "│ AK    ┆ Lisa Murkowski        ┆ Dan Sullivan          ┆ Dan Sullivan          ┆ M      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ AL    ┆ Richard Shelby        ┆ Barry Moore           ┆ Barry Moore           ┆ M      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ AR    ┆ John Boozman          ┆ Tom Cotton            ┆ Bruce Westerman       ┆ M      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ AS    ┆ Aumua Amata Radewagen ┆ Aumua Amata Radewagen ┆ Aumua Amata Radewagen ┆ F      │\n",
       "├╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌┤\n",
       "│ AZ    ┆ Tom O’Halleran        ┆ Ruben Gallego         ┆ Andy Biggs            ┆ M      │\n",
       "└───────┴───────────────────────┴───────────────────────┴───────────────────────┴────────┘"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_person() -> pl.Expr:\n",
    "    return pl.col(\"first_name\") + pl.lit(\" \") + pl.col(\"last_name\")\n",
    "\n",
    "\n",
    "q = (\n",
    "    dataset.lazy()\n",
    "    .sort(\"birthday\")\n",
    "    .groupby([\"state\"])\n",
    "    .agg(\n",
    "        [\n",
    "            get_person().first().alias(\"youngest\"),\n",
    "            get_person().last().alias(\"oldest\"),\n",
    "            get_person().sort().first().alias(\"alphabetical_first\"),\n",
    "            pl.col(\"gender\").sort_by(\"first_name\").first().alias(\"gender\"),\n",
    "        ]\n",
    "    )\n",
    "    .sort(\"state\")\n",
    "    .limit(5)\n",
    ")\n",
    "\n",
    "df = q.collect()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "注意：  \n",
    "sort是对DataFrame操作的  \n",
    "而sort_by是对column操作的，其实也是联动排序"
   ]
  }
 ],
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