pklshop

A library for accessing and analyizing Pickleball data from pklmart

A library for accessing and analyzing Pickleball data from pklmart. You can find the full documentation here.

Install

Install using:

pip install pklshop

How to use

This package includes the latest pickleball data from pklmart already convieniently loaded into pandas dataframes. You can access this data by importing the pklshop.data module using:

from pklshop.data import *

(Note that since this package is writen using nbdev it is safe to wildcard import because the __all__ variable is automatically generated for each module.)

Available dataframes are:

table_names

['tournament',
 'match',
 'game',
 'rally',
 'shot_type_ref',
 'shot',
 'player',
 'team']

print(type(team))
team.columns

<class 'pandas.core.frame.DataFrame'>

Index(['team_id', 'player_id', 'player_seq_nbr', 'team_nm', 'maint_dtm',
       'maint_app', 'create_dtm', 'create_app'],
      dtype='object')

There are also built-in classes to help you analyze the data. For example, you can use the Player class to get a player’s stats or attributes:

p = Player("P1")
p2 = Player("P2")
head_to_head(p,p2)

Jesse Irvine has played against Catherine Parenteau in 1 matches and has won 1 times

And likewise for Games, Teams, Matches, and Rallys. e.g.:

g = Game("G1")
g.summarize_game()

Anna Leigh Waters & Leigh Waters beat Jesse Irvine & Catherine Parenteau 12-10 in game G1
             Player  Error %  Winner %
       Jesse Irvine    17.46      9.52
Catherine Parenteau     1.59      0.00
  Anna Leigh Waters     1.59      3.17
       Leigh Waters     9.52      4.76

g.plot_impact_flow()

To see a more complete analysis in action, check out the examples. For more details, look at the source notebooks in the nbs directory. Also check out Connor and this analysis by conner-mcnicholas on timeout momentum!

r = Rally(“R1020”) r.animate_rally()