Skip to main content
Donate to the Python Software Foundation or Purchase a PyCharm License to Benefit the PSF! Donate Now

A Python package to scrape the NBA api and return a play by play file

Project description

License: GPL v3 Maintenance PyPI version Downloads Build Status codecov

nba_scraper

This is a package written in Python to scrape the NBA's api and produce the play by play of games either in a csv file or a pandas dataframe. This package has two main functions scrape_game which scrapes an individual game or a list of specific games, and scrape_season which scrapes an entire season of regular season games.

As of right now the package only scrapes as far back as the 2016 season. Plans are in place to be able to scrape older seasons, however these older seasons won't have x/y locations for all events as the more recent seasons do.

Installation

To install this package just type this at the command line:

pip install nba_scraper

Usage

scrape_game

The default data format is a pandas dataframe you can change this to csv with the data_format parameter. The default file path is the users home directory you can change this with the data_dir parameter

import nba_scraper.nba_scraper as ns

# if you want to return a dataframe
# you can pass the function a list of strings or integers
# all nba game ids have two leading zeros but you can omit these
# to make it easier to create lists of game ids as I add them on
nba_df = ns.scrape_game([21800001, 21800002])

# if you want a csv if you don't pass a file path the default is home
# directory
ns.scrape_game([21800001, 21800002], data_format='csv', data_dir='file/path')

scrape_season

The data_format and data_dir key words are used the excat same way as scrape_game. Instead of game ids though, you would pass the season you want scraped to the function. This season is a four digit year that must be an integer.

import nba_scraper.nba_scraper as ns

#scrape a season
nba_df = ns.scrape_season(2019)

# if you want a csv if you don't pass a file path the default is home
# directory
ns.scrape_season(2019, data_format='csv', data_dir='file/path')

scrape_date_range

This allows you to scrape all regular season games in the date range passed to the function. As of right now it will not scrape playoff games. Date format must be passed in the format YYYY-MM-DD.

import nba_scraper.nba_scraper as ns

#scrape a season
nba_df = ns.scrape_date_range('2019-01-01', 2019-01-03')

# if you want a csv if you don't pass a file path the default is home
# directory
ns.scrape_date_range('2019-01-01', 2019-01-03', data_format='csv', data_dir='file/path')

Contact

If you have any troubles or bugs please open an issue/bug report. If you have any improvements/suggestions please submit a pull request. If it falls outside those two areas please feel free to email me at matt@barloweanalytics.com.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
nba_scraper-0.2.9.3.tar.gz (14.5 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page