How to add a legend on Seaborn facetgrid bar plot using Matplotlib?

Adding a legend to a Seaborn FacetGrid bar plot requires using map_dataframe() with the plotting function and then calling add_legend(). This approach works with various plot types including bar plots, scatter plots, and line plots.

Basic FacetGrid with Legend

Let's start with a simple example using sample data ?

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

# Set figure parameters
plt.rcParams["figure.figsize"] = [10, 4]
plt.rcParams["figure.autolayout"] = True

# Create sample data
df = pd.DataFrame({
    'category': ['A', 'B', 'C', 'A', 'B', 'C'],
    'value': [3, 7, 8, 5, 6, 4],
    'group': ['X', 'X', 'X', 'Y', 'Y', 'Y']
})

# Create FacetGrid
g = sns.FacetGrid(df, col="group", hue="category", height=4)
g.map_dataframe(sns.barplot, x="category", y="value")
g.add_legend(title="Category")

plt.show()

FacetGrid with Scatter Plot and Legend

Here's the original example with proper data structure ?

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

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# Create more meaningful data
df = pd.DataFrame({
    'col1': ['Group1', 'Group2', 'Group3'],
    'x_val': [1, 2, 3],
    'y_val': [3, 7, 8]
})

g = sns.FacetGrid(df, col="col1", hue="col1")
g.map_dataframe(sns.scatterplot, x="x_val", y="y_val")
g.set_axis_labels("X", "Y")
g.add_legend()

plt.show()

Advanced Example with Bar Plot

For a more practical bar plot example with multiple categories ?

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

# Create realistic dataset
data = pd.DataFrame({
    'region': ['North', 'South', 'East', 'West'] * 3,
    'quarter': ['Q1', 'Q1', 'Q1', 'Q1', 'Q2', 'Q2', 'Q2', 'Q2', 'Q3', 'Q3', 'Q3', 'Q3'],
    'sales': [100, 120, 80, 95, 110, 130, 85, 100, 105, 125, 90, 110],
    'product': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'C', 'C', 'C', 'C']
})

# Create FacetGrid with bar plot
g = sns.FacetGrid(data, col="quarter", hue="product", height=4, aspect=0.8)
g.map_dataframe(sns.barplot, x="region", y="sales")
g.add_legend(title="Product", loc='upper right')
g.set_axis_labels("Region", "Sales")

plt.show()

Key Points

• map_dataframe() − Use this method to apply plotting functions to the FacetGrid
• add_legend() − Adds a legend based on the hue parameter
• hue parameter − Defines which column to use for color coding and legend
• Legend positioning − Use loc parameter in add_legend() to control placement

Legend Customization Options

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

# Sample data
df = pd.DataFrame({
    'x': [1, 2, 3, 1, 2, 3],
    'y': [2, 4, 6, 3, 5, 7],
    'category': ['A', 'A', 'A', 'B', 'B', 'B'],
    'group': ['Type1', 'Type1', 'Type1', 'Type2', 'Type2', 'Type2']
})

g = sns.FacetGrid(df, col="group", hue="category", height=4)
g.map_dataframe(sns.barplot, x="category", y="y")

# Customize legend
g.add_legend(title="Categories", bbox_to_anchor=(1.25, 0.5), loc='center left')

plt.show()

Conclusion

Use map_dataframe() with your desired plotting function and add_legend() to add legends to FacetGrid plots. The hue parameter determines what gets color-coded and included in the legend.