Baby Names!

Fun with the Social Security Administration's baby name data.

v0.1.2

Setup

This is a Node.js script, so you should consider downloading Node before attempting to run it.

To download the repo, simply clone it:

git clone https://github.com/TimeMagazineLabs/babynames.git
cd babynames

Then install the dependencies:

npm install

Data

The Social Security Administration organizes the baby name data, somewhat inconveniently, as year-by-year text files named yob[year].txt, beginning in 1880 for national data and 1910 for state data. The data for the previous calendar year is usually released around Mother's Day.

As of the 2018 data, there are 109,174 names, constituting any name-gender combination that appeared in at least one year a minimum of five times. The scripts in this repo download this raw data and provide tools for aggregating specific (or all) names in specific (or all) spans of years will the ability to exclude uncommon names.

Getting the Data

The raw data is not included in the repo. Instead, you need to download it from the Social Security Administration with a simple command or function. This script will download and unzip it for you into the data/national directory, and then delete the .zip file.

# CLI
./index.js download 

# Node
const babynames = require("babynames");
babynames.download({ [opts] }, function() {
	// further commands to aggregate the flat files you just downloaded
});

You can also get the state-by-state data, which extracts to the data/states directory

# CLI
./index.js download --states

# Node
const babynames = require("babynames");
babynames.download({ states: true }, function() { ... });

Total babies born each year

There is also a file called extra/totals.json with data on the total number of babies born (or at least, those issued a SSN) each year, per the SSA, which is used for calculating frequencies as percentages. This is necessary because the totals are higher than the sum of each name in the name files, which don't include names that occur fewer than five times.

If you want to re-download this data--maybe it's a new year or you suspect there has been a revision--just run ./scripts/total_births.js, which will scrape the page on the SSA website and overwrite the file in the repo.

Let's get started!

Now that you've downloaded the raw data, the fun begins!

Extracting names

Once you've downloaded the data, you can aggregate it on a per-name basis and store it in a variety of formats:

./index.js store --format=json --names=Edward,Nancy,Christopher

Options

These options are either passed as --format, e.g. from the command-line, or as key values in Node (see test/test.js)

option	default	purpose
names	null: Every name!	A comma-separated list of names to extract. If you don't append a name with -f or -m, it will search for both genders.
start	1880	The first year of data to extract. The default, 1880, is the first available year of data.
end	Most recent year	The last year of data to extract. The default is the previous calendar year starting in June, otherwise the year before that.
min	1	Don't include names that don't show up at least this many times in at least one year. The default is functionally 5 in the data.
cutoff	1	Don't include names that don't show up in at least this many individual years.
format	Must be provided	Format out output. Options are json, csv, jsonp, csvs, mongodb. See following explanation.

Formats

• json: Each name is stored as an individual JSON file in the /flat_files/individual/ directory.
• jsonp: Each name is stored as an individual JSON-P file in the /flat_files/individual/ directory. It is wrapped in a callback function named name_callback by default, which you can override with opts.callback or --callback.
• csv: All names are packaged into one CSV file and stored in /flat_files/names_[year_start]_[year_end].csv/. This file will be able 30MB if you don't include limiting specifications above (start, end, min, cutoff).
• csvs: Each name is stored as an individual CSV file in the /flat_files/individual/ directory.
• mongodb: All names are inserted into a MongoDB instance, using the slug [name]-[m|f] as the _id. Note: Because this is optional, the mongodb Node module is not included as a dependency, so you'll need to install it yourself as well as running a mongo server: npm install mongodb. You can pass a --mongo_uri argument, which defaults to mongodb://localhost:27017, as well as a db_name argument, which defaults to babynames.

How it Works

First, the script reads every raw file from the SSA and stores the data on a per-name basis in memory. For each name, it records both the absolute number of babies with that name in a given year and the percentage of all babies of the same gender with that name. The denominator in that calculation is the gender-specific total number of babies as reported on SSA.gov, NOT the calculated sum of all baby name frequencies (which will be lower than the actual number of children born in the United States, given that the data only counts names that appear at least five times). For JSON, the years are stored as keys in an object for fast retrieval. Here is the output of ./index.js store --name=Clifford-m --format=json --start=1960 --end=1980, which would be writting to flat_files/individuals/clifford-m.json:

{
  "id": "clifford-m",
  "name": "Clifford",
  "gender": "M",
  "values": {
    "1960": 2465,
    "1961": 2336,
    "1962": 2183,
    "1963": 2198,
    "1964": 2021,
    "1965": 1822,
    "1966": 1612,
    "1967": 1514,
    "1968": 1608,
    "1969": 1507,
    "1970": 1581,
    "1971": 1382,
    "1972": 1268,
    "1973": 1175,
    "1974": 1148,
    "1975": 1124,
    "1976": 1065,
    "1977": 973,
    "1978": 1002,
    "1979": 1046,
    "1980": 1218
  },
  "percents": {
    "1960": 0.00113831417748373,
    "1961": 0.0010835080428208315,
    "1962": 0.001038538187329834,
    "1963": 0.0010643861620113896,
    "1964": 0.0009969135634998424,
    "1965": 0.0009614400281994266,
    "1966": 0.0008867579315876157,
    "1967": 0.0008507089990852349,
    "1968": 0.0009054069348090115,
    "1969": 0.0008235737746129422,
    "1970": 0.0008297069733171276,
    "1971": 0.0007600414008079977,
    "1972": 0.0007571952960735124,
    "1973": 0.0007279201679110487,
    "1974": 0.0007039861066992741,
    "1975": 0.0006925348562528072,
    "1976": 0.0006520884587077995,
    "1977": 0.0005690371283567635,
    "1978": 0.0005862398622043789,
    "1979": 0.0005837441214009189,
    "1980": 0.0006565602388628679
  }
}

Formats

Your choices are:

• json: Each name is stored as an individual JSON file in the /flat/individual/ directory.
• jsonp: Each name is stored as an individual JSON-P file in the /flat/individual/ directory. It is wrapped in a callback function named ticallback by default, which you can override with opts.callback.
• csvs: Each name is stored as an individual CSV file in the /flat/individual/ directory.
• csv: All names are packaged into one CSV file and stored in /flat/names.csv/. This file will be able 30MB if you don't include limiting specifications (below). This preprocessed file is included in this repo.
• mongodb: All names are inserted into a MongoDB instance. You are responsible for running a Mongo server at localhost:27017 or updating the source to point to your instance. Note: Because this is optional, the mongodb Node module is not listed as a dependency, you you'll need to install it yourself.

Reducing the size

As of 2020, there are 111,473 names (double counting those used for male and female babies) that show up in at least one year at least five times. Many users will not be interested in this volume of data. There are several ways to reduce the scope with command line options.

Limit the years

Using --start and --end can narrow the window of time:

./index.js store --format=csv --start=1960 --end=1980

Exclude uncommon names

• min: Don't include names that don't show up at least this many time in at least one year. Ex: --min=25. Default is 0.

• cutoff: Don't include names that don't show up in at least this many individual years. Ex: --cutoff=50. Default is 0.

  ./index.js store --format=json --min=25 --cutoff=10

Analysis

This is still in the works

The script comes with several options for basic analysis:

• normalize: Add a third property to each name that is the normalized value for the percentage figures, such that the peak percentage year is 1.
• peak: Find the peak value and year for both raw values and percents
• maxima: Identify all the local maxima -- points where every value 5 years before and after is lower. Only counts maxima that are at least 25 percent of peak value.
• dense: If a name does not appear in a year in the range specified between start and end, list that year in the data as 0. Otherwise it is not included at all (a "sparse" format).

Types

For csv outputs, you can get the data back as either raw numbers of new babies each year with a given name (--type=values, which is the default) or as a percent (--type=values). JSON formats return both percents and values.

Phonemes

You can also pass a special type, --type=phonemes, to get back a JSON document of phoneme percents for each year for all names. By default, the script examines the first phoneme in each name. You can use --N==TK to aggregate around the TKth phonemes in the name. Use a negative value to start from the end.

Extras

We've now got British baby names going back to 1996, accessed on Oct. 5, 2016 from the U.K. Office for National Statistics. The total number of live births was downloaded here from the same source.

License

This script is provided free and open-source by Time under the MIT license. If you use it, you are politely encouraged to acknowledge Time and link to this page.

<<<<<<< HEAD The dictionary file dict/2of12.txt is from the 12 Dicts project, which is in the public domain.

The dictionary file dict/2of12.txt is from the 12 Dicts project, which is in the public domain.

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