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 totidyframe
class which mostly return atidyframe
- 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
tidyframe
and pandas dataframes - An accessor to apply
tidyframe
verbs to simple pandas datarames - …
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[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)
reset_index
,rename_axis
often - you prefer writing free flowing, expressive code in dplyr style
tidypandas
relies on the amazingpandas
library 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.