cricsummary is built for performing cricket analysis on data provided by cricsheet.org. by converting the data in DataFrames or csv files that are better suited for analysis.
- Convert json file to csv.
- Creates DataFrames team-wise.
- Vizualise or Perform your own transformations/analysis on the DataFrames.
- Save the converted file (json to csv)
- Plot Manhattan and Worm charts
This is a useful tool to get started with cricket analysis.
cricsummary requires python 3.5+ to run.
$ pip install cricsummary
Download the data from cricsheet Use the txt file in downloaded folder to check name of the match you want to analyse
>>> from cricsummary import Duranz
>>> match = Duranz('12345.json')
### BUILT IN METHODS FOR ANAYSIS
# team parameter represent innings, team=1 for data of team batted in 1st inning
>>> match.scorecard(team=1)
>>> match.plot_worm()
>>> match.plot_manhattan(team=2)
>>> match.match_info()
>>> match.extras(team=1)
>>> match.fall_of_wickets(team=2)
- Access separate DataFrames of teams and do your Operations/Analysis
# returns dict of dataframe where keys are team name with _<innings> suffix
match = Duranz('123.json')
>>> df_dict = match.teams_df
### CONVERT JSON TO CSV
>>> from cricsummary import json_to_csv
# this will save the files of the innings <teamname>_<innings>.csv
>>> json_to_csv('123.json', output_file=True)
Want to contribute? Great! pull request on https://github.com/KunalDuran/cricsummary
MIT