linear-fits.md

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jupytext kernelspec language_info plotly notebook_metadata_filter text_representation all extension format_name format_version jupytext_version .md markdown 1.1 1.1.1 display_name language name Python 3 python python3 codemirror_mode file_extension mimetype name nbconvert_exporter pygments_lexer version name version ipython 3 .py text/x-python python python ipython3 3.6.8 description display_as language layout name order page_type permalink thumbnail Add linear Ordinary Least Squares (OLS) regression trendlines or non-linear Locally Weighted Scatterplot Smoothing (LOEWSS) trendlines to scatterplots in Python. statistical python base Linear and Non-Linear Trendlines 12 u-guide python/linear-fits/ thumbnail/linear_fit.jpg

Linear fit trendlines with Plotly Express

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.

Plotly Express allows you to add Ordinary Least Squares regression trendline to scatterplots with the trendline argument. In order to do so, you will need to install statsmodels and its dependencies. Hovering over the trendline will show the equation of the line and its R-squared value.

import plotly.express as px

df = px.data.tips()
fig = px.scatter(df, x="total_bill", y="tip", trendline="ols")
fig.show()

Fitting multiple lines and retrieving the model parameters

Plotly Express will fit a trendline per trace, and allows you to access the underlying model parameters for all the models.

import plotly.express as px

df = px.data.tips()
fig = px.scatter(df, x="total_bill", y="tip", facet_col="smoker", color="sex", trendline="ols")
fig.show()

results = px.get_trendline_results(fig)
print(results)

results.query("sex == 'Male' and smoker == 'Yes'").px_fit_results.iloc[0].summary()

Non-Linear Trendlines

Plotly Express also supports non-linear LOWESS trendlines.

import plotly.express as px

df = px.data.gapminder().query("year == 2007")
fig = px.scatter(df, x="gdpPercap", y="lifeExp", color="continent", trendline="lowess")
fig.show()