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A grammar of data manipulation for pandas inspired by tidyverse

Project description

tidypandas

A grammar of data manipulation for pandas inspired by tidyverse

tidypandas python package provides minimal, pythonic API for common data manipulation tasks:

  • tidyframe class (wrapper over pandas dataframe) provides a dataframe with simplified index structure (no more resetting indexes and multi indexes)
  • Consistent ‘verbs’ (select, arrange, distinct, …) as methods to tidyframe class which mostly return a tidyframe
  • Unified interface for summarizing (aggregation) and mutate (assign) operations across groups
  • Utilites for pandas dataframes and series
  • Uses of simple python data structures, No esoteric classes, No pipes, No Non-standard evaluation
  • No copy data conversion between tidyframe and pandas dataframes
  • An accessor to apply tidyframe verbs to simple pandas datarames

Example

  • tidypandas code:
df.filter(lambda x: x['col_1'] > x['col_1'].mean(), by = 'col_2')
  • equivalent pandas code:
(df.groupby('col2')
   .apply(lambda x: x.loc(lambda y: y['col_1'] > y['col_1'].mean()))
   .reset_index(drop = True)
   )

Why use tidypandas

tidypandas is for you if:

  • you frequently write data manipulation code using pandas
  • you prefer to have stay in pandas ecosystem (see accessor)
  • you prefer to remember a limited set of methods
  • you do not want to write (or be surprised by) reset_index, rename_axis often
  • you prefer writing free flowing, expressive code in dplyr style

tidypandas relies on the amazing pandas library and offers a consistent API with a different philosophy.

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