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Displot

As explained in Pandas Workout: 200 exercises to make you a stronger data analyst

displot is a Seaborn function for visualizing the distribution of observations.

displot visualizes the distribution of observations with Seaborn. For a weather DataFrame, it can show how maximum temperatures are distributed across all cities. section 11.16

Use the function to compare distributions in progressively more informative ways:

  • Plot a histogram with max_temp on the x-axis. section 11.16
  • Add hue='city' to distinguish each city's distribution by color. section 11.16
  • Add row='city' to place each city's histogram in a separate plot. section 11.16

Compare city temperatures

sns.displot(x='max_temp', data=df, hue='city', row='city') produces city-specific histograms, using color and separate rows to make the distributions easier to compare. section 11.16

sns.displot(x='max_temp', data=df)

Start with the simplest distribution plot before adding categorical color or faceting. section 11.16

How Pandas Workout: 200 exercises to make you a stronger data analyst covers it

How deep it goes
Demonstrates basic histograms, categorical coloring, and separate plots, without discussing distribution internals.
Examples
Uses maximum-temperature histograms for all cities, colored by city and optionally separated into city-specific plots.
What you can do after
Apply it via Seaborn to inspect and compare numeric distributions in a pandas DataFrame.
How it connects
Connects distribution visualization with relplot, catplot, and regplot.
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