.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/01_basic_usage.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_01_basic_usage.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_01_basic_usage.py:


Basic usage
===========

A simple example demonstrating how to use `pandera_utils`.

.. GENERATED FROM PYTHON SOURCE LINES 8-17

.. code-block:: Python

    import inspect

    import pandas as pd
    from pathlib import Path
    import yaml
    from elphick.pandera_utils.pandera_utils import load_schema_from_yaml, DataFrameMetaProcessor

    __file__ = Path(inspect.getfile(inspect.currentframe())).resolve()








.. GENERATED FROM PYTHON SOURCE LINES 18-21

Load Schema
-----------
Load the schema from the YAML file

.. GENERATED FROM PYTHON SOURCE LINES 21-29

.. code-block:: Python

    yaml_path = __file__.parents[1] / "assets/example_schema.yaml"
    schema = load_schema_from_yaml(yaml_path)

    # Print the YAML file in a nicely formatted way
    with open(yaml_path, "r", encoding="utf-8") as f:
        schema_yaml = yaml.safe_load(f)
        print(yaml.dump(schema_yaml, sort_keys=False, indent=2))





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    columns:
      column1:
        dtype: int
        checks:
          greater_than: 0
        required: false
        coerce: true
        metadata:
          pandera_utils:
            unit_of_measure: m
            aliases:
            - col1
      column2:
        dtype: float
        checks:
          greater_than_or_equal_to: 0.0
        required: false
        metadata:
          pandera_utils:
            decimals: 1
      column3:
        dtype: float
        checks:
          less_than: 100.0
        required: false
        metadata:
          pandera_utils:
            calculation: column1 + column2
            inputs:
            - column1
            - column2
            decimals: 2





.. GENERATED FROM PYTHON SOURCE LINES 30-32

Create a sample DataFrame
-------------------------

.. GENERATED FROM PYTHON SOURCE LINES 32-41

.. code-block:: Python

    dataframe = pd.DataFrame({
        "col1": [1, 2, 3],
        "column2": [0.546, 1.568, 2.578],
    })

    # preserve a copy for comparison later
    dataframe_copy = dataframe.copy(deep=True)

    dataframe





.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>col1</th>
          <th>column2</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1</td>
          <td>0.546</td>
        </tr>
        <tr>
          <th>1</th>
          <td>2</td>
          <td>1.568</td>
        </tr>
        <tr>
          <th>2</th>
          <td>3</td>
          <td>2.578</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 42-45

Initialize
----------
Initialize the DataFrameMetaProcessor with the schema

.. GENERATED FROM PYTHON SOURCE LINES 45-47

.. code-block:: Python

    processor = DataFrameMetaProcessor(schema)








.. GENERATED FROM PYTHON SOURCE LINES 48-50

Rename Aliases
--------------

.. GENERATED FROM PYTHON SOURCE LINES 50-53

.. code-block:: Python

    df_with_alias = processor.apply_rename_from_alias(dataframe)
    df_with_alias






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>column1</th>
          <th>column2</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1</td>
          <td>0.546</td>
        </tr>
        <tr>
          <th>1</th>
          <td>2</td>
          <td>1.568</td>
        </tr>
        <tr>
          <th>2</th>
          <td>3</td>
          <td>2.578</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 54-56

Apply calculations
------------------

.. GENERATED FROM PYTHON SOURCE LINES 56-59

.. code-block:: Python

    df_with_calculations = processor.apply_calculations(df_with_alias)
    df_with_calculations






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>column1</th>
          <th>column2</th>
          <th>column3</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1</td>
          <td>0.546</td>
          <td>1.546</td>
        </tr>
        <tr>
          <th>1</th>
          <td>2</td>
          <td>1.568</td>
          <td>3.568</td>
        </tr>
        <tr>
          <th>2</th>
          <td>3</td>
          <td>2.578</td>
          <td>5.578</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 60-62

Apply rounding
--------------

.. GENERATED FROM PYTHON SOURCE LINES 62-65

.. code-block:: Python

    df_with_decimals = processor.apply_rounding(df_with_calculations)
    df_with_decimals






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>column1</th>
          <th>column2</th>
          <th>column3</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1</td>
          <td>0.5</td>
          <td>1.55</td>
        </tr>
        <tr>
          <th>1</th>
          <td>2</td>
          <td>1.6</td>
          <td>3.57</td>
        </tr>
        <tr>
          <th>2</th>
          <td>3</td>
          <td>2.6</td>
          <td>5.58</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 66-73

One Step Preprocessing
----------------------
Preprocess the DataFrame, with alias renaming, rounding, and calculations.
If metadata: decimals is not null, the column will be rounded to that number of decimal places after the other
preprocessing steps.
When set to True, the round_before_calc argument will round the DataFrame before applying calculations,
as well as after.

.. GENERATED FROM PYTHON SOURCE LINES 73-76

.. code-block:: Python

    processed_df = processor.preprocess(dataframe_copy, round_before_calc=False)
    processed_df






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>column1</th>
          <th>column2</th>
          <th>column3</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1</td>
          <td>0.5</td>
          <td>1.55</td>
        </tr>
        <tr>
          <th>1</th>
          <td>2</td>
          <td>1.6</td>
          <td>3.57</td>
        </tr>
        <tr>
          <th>2</th>
          <td>3</td>
          <td>2.6</td>
          <td>5.58</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 77-78

We can check that the individual steps are equivalent to the one-step preprocessing

.. GENERATED FROM PYTHON SOURCE LINES 78-80

.. code-block:: Python

    assert processed_df.equals(df_with_decimals)








.. GENERATED FROM PYTHON SOURCE LINES 81-84

Validate
--------
Validate the DataFrame using Pandera

.. GENERATED FROM PYTHON SOURCE LINES 84-86

.. code-block:: Python

    validated_df = processor.validate(processed_df)
    validated_df





.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>column1</th>
          <th>column2</th>
          <th>column3</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1</td>
          <td>0.5</td>
          <td>1.55</td>
        </tr>
        <tr>
          <th>1</th>
          <td>2</td>
          <td>1.6</td>
          <td>3.57</td>
        </tr>
        <tr>
          <th>2</th>
          <td>3</td>
          <td>2.6</td>
          <td>5.58</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.069 seconds)


.. _sphx_glr_download_auto_examples_01_basic_usage.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: 01_basic_usage.ipynb <01_basic_usage.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: 01_basic_usage.py <01_basic_usage.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_