A grammar of data manipulation for pandas inspired by tidyverse
tidypandas python package provides minimal, pythonic API for common
data manipulation tasks:
tidyframeclass (wrapper over pandas dataframe) provides a dataframe with simplified index structure (no more resetting indexes and multi indexes)
- Consistent ‘verbs’ (
distinct, …) as methods to
tidyframeclass which mostly return a
- Unified interface for summarizing (aggregation) and mutate (assign) operations across groups
- Utilites for pandas dataframes and series
- Uses simple python data structures, No esoteric classes, No pipes, No Non-standard evaluation
- No copy data conversion between
tidyframeand pandas dataframes
- An accessor to apply
tidyframeverbs to simple pandas datarames
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[x['col_1'] > x['col_1'].mean(), :]) .reset_index(drop = True) )
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)
- you prefer writing free flowing, expressive code in dplyr style
tidypandasrelies on the amazing
pandaslibrary and offers a consistent API with a different philosophy.
Install release version from Pypi using pip:
pip install tidypandas
For offline installation, use whl/tar file from the releases page on github.
Open an issue/suggestion/bugfix on the github issues page.
Use the master branch from github repo to submit your PR.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Hashes for tidypandas-0.2.2-py3-none-any.whl