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Python scraper for ATP Ranking Singles tennis data

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ATP Ranking Singles

The ATP Rankings are the Association of Tennis Professionals' (ATP) merit-based method for determining the rankings in men's tennis. The top-ranked player is the player who, over the previous 52 weeks, has garnered the most ranking points on the ATP Tour. Points are awarded based on how far a player advances in tournaments and the category of those tournaments. (based on: Wikipedia)

ATP Ranking is updated every Monday.

Data

CSV file contains rankings for each tennis player since 1973/08/23 till 2021/08/02 (ordered by the ranking's week descending).

File contains the following columns:

['Date', 'Ranking', 'Move', 'Country', 'Player', 'Age', 'Points', 'Tourn Played', 'Points Dropping', 'Next Best']

The data comes from the ATP website

Get the data

For Python or R you can use the code snippets below:

R:

df <- readr::read_csv('https://media.githubusercontent.com/media/jpawlata/ATP_Ranking/main/data/atp_ranking.csv')

Python:

import pandas as pd
df = pd.read_csv('https://media.githubusercontent.com/media/jpawlata/ATP_Ranking/main/data/atp_ranking.csv')

Update

If you need an up to date data file, feel free to run the script. It takes some time to finish so... you need to be patient :)

Run the script

To run the script I use Google Colab. gdrive.ipynb file allows to mount your Google Drive into the Colab environment.

If you want to run the script using Google Colab - just copy all the cells from the gdrive.ipynb at the top of the atp.ipynb file and add your project folder's name instead of 'YOUR-FOLDER' placeholder.

Disclaimer

Downloads and copies of atp_ranking.csv as well as working with the data are only permitted if they are to be used for private, non-commercial purposes.

License

MIT

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