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A Python library for tennis data analysis.

Project description

Pytennis

Install

pip install pytennis

How to use

Data

path = untar_data(URLs.ATP_2019_AUSTRALIAN_OPEN_SINGLES_FINAL)
path
Path('/Users/robertseidl/.pytennis/data/ATP_2019_AustralianOpen_Singles_Final')
path.ls()
(#4) [Path('/Users/robertseidl/.pytennis/data/ATP_2019_AustralianOpen_Singles_Final/rallies.csv'),Path('/Users/robertseidl/.pytennis/data/ATP_2019_AustralianOpen_Singles_Final/points.csv'),Path('/Users/robertseidl/.pytennis/data/ATP_2019_AustralianOpen_Singles_Final/events.csv'),Path('/Users/robertseidl/.pytennis/data/ATP_2019_AustralianOpen_Singles_Final/serves.csv')]
pd.read_csv(path/'rallies.csv', index_col=0).head()
<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; }
.dataframe tbody tr th {
    vertical-align: top;
}

.dataframe thead th {
    text-align: right;
}
</style>
rallyid server returner winner reason serve strokes totaltime x y
0 1 Djokovic Nadal Djokovic winner first 3 0.92 1.92 21.96
1 2 Djokovic Nadal __undefined__ second_serve first 1 0.00 7.42 12.10
2 3 Djokovic Nadal Djokovic out second 4 4.16 3.33 -0.39
3 4 Djokovic Nadal __undefined__ second_serve first 1 0.00 4.64 17.69
4 5 Djokovic Nadal Djokovic ace second 2 0.40 1.62 17.18

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