[](https://badge.fury.io/py/tidypandas)
# `tidypandas`
> A **grammar of data manipulation** for
> [pandas](https://pandas.pydata.org/docs/index.html) inspired by
> [tidyverse](https://tidyverse.tidyverse.org/)
`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 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](https://medium.com/dunder-data/minimally-sufficient-pandas-a8e67f2a2428)
- you do not want to write (or be surprised by)
[`reset_index`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.reset_index.html),
[`rename_axis`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.rename_axis.html)
often
- you prefer writing free flowing, expressive code in
[dplyr](https://dplyr.tidyverse.org/) style
> `tidypandas` relies on the amazing `pandas` library and offers a
> consistent API with a different
> [philosophy](https://tidyverse.tidyverse.org/articles/manifesto.html).
## Installation
1. Install release version from Pypi using pip:
pip install tidypandas
2. For offline installation, use whl/tar file from the [releases
page](https://github.com/talegari/tidypandas/releases) on github.
## Contribution/bug fixes/Issues:
1. Open an issue/suggestion/bugfix on the github
[issues](https://github.com/talegari/tidypandas/issues) page.
2. Use the master branch from
[github](https://github.com/talegari/tidypandas) repo tp submit your
PR.
------------------------------------------------------------------------
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"description": "[](https://badge.fury.io/py/tidypandas)\n\n# `tidypandas`\n\n> A **grammar of data manipulation** for\n> [pandas](https://pandas.pydata.org/docs/index.html) inspired by\n> [tidyverse](https://tidyverse.tidyverse.org/)\n\n`tidypandas` python package provides *minimal, pythonic* API for common\ndata manipulation tasks:\n\n- `tidyframe` class (wrapper over pandas dataframe) provides a\n dataframe with simplified index structure (no more resetting indexes\n and multi indexes)\n- Consistent \u2018verbs\u2019 (`select`, `arrange`, `distinct`, \u2026) as methods\n to `tidyframe` class which mostly return a `tidyframe`\n- Unified interface for summarizing (aggregation) and mutate (assign)\n operations across groups\n- Utilites for pandas dataframes and series\n- Uses simple python data structures, No esoteric classes, No pipes,\n No Non-standard evaluation\n- No copy data conversion between `tidyframe` and pandas dataframes\n- An accessor to apply `tidyframe` verbs to simple pandas datarames\n- \u2026\n\n## Example\n\n- `tidypandas` code:\n\n<!-- -->\n\n df.filter(lambda x: x['col_1'] > x['col_1'].mean(), by = 'col_2')\n\n- equivalent pandas code:\n\n<!-- -->\n\n (df.groupby('col2')\n .apply(lambda x: x.loc[lambda y: y['col_1'] > y['col_1'].mean(), :])\n .reset_index(drop = True)\n )\n\n## Why use `tidypandas`\n\n`tidypandas` is for you if:\n\n- you *frequently* write data manipulation code using pandas\n- you prefer to have stay in pandas ecosystem (see accessor)\n- you *prefer* to remember a [limited set of\n methods](https://medium.com/dunder-data/minimally-sufficient-pandas-a8e67f2a2428)\n- you do not want to write (or be surprised by)\n [`reset_index`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.reset_index.html),\n [`rename_axis`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.rename_axis.html)\n often\n- you prefer writing free flowing, expressive code in\n [dplyr](https://dplyr.tidyverse.org/) style\n\n> `tidypandas` relies on the amazing `pandas` library and offers a\n> consistent API with a different\n> [philosophy](https://tidyverse.tidyverse.org/articles/manifesto.html).\n\n## Installation\n\n1. Install release version from Pypi using pip:\n\n pip install tidypandas\n\n2. For offline installation, use whl/tar file from the [releases\n page](https://github.com/talegari/tidypandas/releases) on github.\n\n## Contribution/bug fixes/Issues:\n\n1. Open an issue/suggestion/bugfix on the github\n [issues](https://github.com/talegari/tidypandas/issues) page.\n\n2. Use the master branch from\n [github](https://github.com/talegari/tidypandas) repo tp submit your\n PR.\n\n------------------------------------------------------------------------\n",
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