pklshop 0.0.4

A library for accessing and analyzing Pickleball data from pklmart

pklshop

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 a pandas dataframe. 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.)

Once that’s done, this lib provides a function get_tab_as_df you can use to create and display tables within the database

Available tables are:

table_names

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

match.head()

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	match_id	tourn_id	consol_ind	team_id_1	team_id_2	maint_dtm	maint_app	create_dtm	create_app
0	M1	T1	N	T1	T2	2022-04-09 03:19:33.840951+00:00	postgres	2022-04-09 03:19:33.840951+00:00	postgres
1	M2	T2	N	T2	T3	2022-05-26 00:45:11.301752+00:00	postgres	2022-05-26 00:45:11.301752+00:00	postgres
2	M5	T5	N	T6	T5	2022-06-28 00:40:22.948360+00:00	postgres	2022-06-28 00:40:22.948360+00:00	postgres
3	M6	T6	N	T5	T7	2022-07-07 23:01:45.921540+00:00	postgres	2022-07-07 23:01:45.921540+00:00	postgres
4	M7	T7	N	T8	T9	2022-07-11 02:40:50.597016+00:00	postgres	2022-07-11 02:40:50.597016+00:00	postgres

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. Also check out Connor and this analysis by conner-mcnicholas on timeout momentum!

r = Rally(“R1020”) r.animate_rally()