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📝🛠️ refactor sphinx document config
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ZenithClown committed Jul 27, 2024
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10 changes: 10 additions & 0 deletions docs/functions.md
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# User Defined Functions

<div align = "justify">

```{eval-rst}
.. automodule:: pandaswizard.functions.collate
:members:
```

</div>
22 changes: 20 additions & 2 deletions docs/index.md
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<h1 align = "center">pandas-wizard</h1>
<div align = "center">

# pandas-wizard

</div>

<div align = "justify">

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The above function calculates the 50th percentile, i.e., the median of the feature "A" based on the grouped column "group" from the data frame.

## Brief Overview of Capailities

```{eval-rst}
.. automodule:: pandaswizard
```

### User Defined Functions

```{eval-rst}
.. automodule:: pandaswizard.functions
```

```{toctree}
:hidden:
modules.md
aggregate.md
wrappers.md
functions.md
```

---
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15 changes: 0 additions & 15 deletions docs/modules.md

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14 changes: 7 additions & 7 deletions pandaswizard/__init__.py
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# -*- encoding: utf-8 -*-

"""
Utility Functions, Wrappers for pandas Library
Utility Functions and/or Wrappers for pandas Library
The :mod:`pdwizard` module includes functions, wrappers and other
The :mod:`pandaswizard` module includes functions, wrappers and other
utility functions for `pandas` module. The package is kept simple and
minimalistic such that external dependencies are reduced. The working
of the module is divided into the following sections:
* **`pandaswizard.aggregate`**: a set of aggregate functions that
can be used along with `pd.groupby().agg()` method without
comprimising functionality.
* **`pandaswizard.wrappers`**: a set of decorators/wrappers that
can be used along side a function.
* :mod:`pandaswizard.aggregate`: a set of aggregate functions
that can be used along with ``pd.groupby().agg({...})`` method
without comprimising functionality.
* :mod:`pandaswizard.wrappers`: a set of decorators/wrappers
that can be used along side a function.
"""

# ? package follows https://peps.python.org/pep-0440/
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3 changes: 2 additions & 1 deletion pandaswizard/wrappers.py
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Expand Up @@ -104,8 +104,9 @@ def timeit(func : callable) -> callable:
executed time of a function, or like the one from command line:
.. code-block:: shell
python -m timeit "function()"
The function is built specifically to handle functions which
returns a :attr:`pd.DataFrame` object, thus it prints more
information like the number of records fetched, shape and other
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