plot_bivariate_numeric_categorical_summary.rst

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

        Click :ref:`here <sphx_glr_download_auto_examples_bivariate_summaries_plot_bivariate_numeric_categorical_summary.py>`
        to download the full example code

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

Bivariate Numeric-Categorical Summary

Example of bivariate eda summary for a numeric independent variable and a categorical dependent variable.

The summary computes the following:

• Lineplot with fractions for each level of the categorical variable against quantiles of the numeric variable

import pandas as pd
import plotly

import intedact

Here we look at how diamond cut quality changes with carats.

data = pd.read_csv(
    "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/diamonds.csv"
)
fig = intedact.numeric_categorical_summary(
    data, "carat", "cut", num_intervals=5, fig_width=700
)
plotly.io.show(fig)

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   **Total running time of the script:** ( 0 minutes  0.692 seconds)

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     :download:`Download Python source code: plot_bivariate_numeric_categorical_summary.py <plot_bivariate_numeric_categorical_summary.py>`



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     :download:`Download Jupyter notebook: plot_bivariate_numeric_categorical_summary.ipynb <plot_bivariate_numeric_categorical_summary.ipynb>`

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