A library for accessing and analyzing Pickleball data from pklmart. You can find the full documentation here.
Install using:
pip install pklshop
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!