How to Make Heatmap Square in Seaborn FacetGrid

Seaborn is a powerful Python visualization library based on Matplotlib that provides a high-level interface for drawing attractive and informative statistical graphics. One of the common visualizations used in data analysis is the heatmap, which shows data in a matrix form where each cell is colored according to its value. Sometimes, when using FacetGrid to create multiple heatmaps, ensuring each heatmap is square can enhance visual consistency and interpretability. This article guides you through making heatmaps square within Seaborn's FacetGrid.

Step-by-Step Guide - Heatmap Square in Seaborn FacetGrid

1. Import Libraries

First, import the necessary libraries.

import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

2. Create Sample Data

For demonstration, let's create a sample dataset.

# Create a sample dataset
np.random.seed(0)
data = np.random.rand(10, 10)
df = pd.DataFrame(data, columns=[f'col_{i}' for i in range(10)])
df['Category'] = np.random.choice(['A', 'B'], size=10)

3. Create a FacetGrid

Use Seaborn's FacetGrid to create multiple heatmaps based on the 'Category' column.

g = sns.FacetGrid(df, col='Category', margin_titles=True)

4. Define Heatmap Function

Define a function to plot a heatmap. This function ensures the heatmap cells are square by setting the aspect ratio.

def draw_heatmap(data, **kwargs):
    data = data.drop('Category', axis=1)
    sns.heatmap(data, square=True, cbar=False, **kwargs)

5. Map Data to FacetGrid

Use the map_dataframe method to map the dataset to the FacetGrid using the heatmap function defined.

g.map_dataframe(draw_heatmap)

<seaborn.axisgrid.FacetGrid at 0x7b3348813790>

6. Adjust Layout

To ensure the heatmaps are perfectly square, adjust the layout using Matplotlib's tight_layout method.

plt.tight_layout()
plt.show()

Conclusion

Making heatmaps square within a Seaborn FacetGrid involves creating a custom function to plot the heatmap with square cells and mapping this function to the grid. This ensures that all heatmaps have a consistent aspect ratio, enhancing the visual appeal and interpretability of your data visualization. With these steps, you can effectively create and customize square heatmaps in Seaborn FacetGrid.