In Seaborn, catplot is a function mainly for visualizing categorical data. It combines a categorical plot with a FacetGrid, allowing us to explore relationships between variables across different categories. While catplot provides informative visualizations by default, adding grid lines can further improve the readability and interpretation. In this article, we will know about how to add grid lines to a catplot in seaborn.

Adding Grid Lines to the Catplot

A catplot (categorical plot) in Seaborn is a figure-level interface for drawing categorical plots onto a FacetGrid. While Seaborn’s catplot function doesn’t directly support adding grid lines, we can achieve this by accessing the underlying Matplotlib axes object.

Grid lines can help in:

• Improving readability: They make it easier to see the values corresponding to data points.
• Enhancing analysis: They help in comparing data points across different categories.
• Aesthetic appeal: They can make the plot look more structured and professional.

Methods to Add Grid Lines in CatPlot

Below are the methods we can use:

Method 1: Using the ax.grid() Method

This method is a direct way to add grid lines to the plot. We can customize the appearance of the grid lines using parameters like axis, color, linestyle, linewidth, etc.

Steps:

1. Import necessary libraries:

import seaborn as sns
import matplotlib.pyplot as plt

2. Load the dataset:

tips = sns.load_dataset("tips")

3. Create the catplot:

g = sns.catplot(x="day", y="total_bill", kind="bar", data=tips)

4. Access the axes object and add grid lines:

ax = g.ax  # Access the axes object
ax.grid(True)  # Add grid lines
plt.show()

Method 2: Using the FacetGrid and map Methods

This approach is useful when we want to add grid lines to multiple plots created by FacetGrid. The map function applies the plot function to each subplot in the grid, effectively adding grid lines to all of them.

Steps:

1. Create a FacetGrid:

g = sns.FacetGrid(tips, col="time")

2. Map the plot function to the grid and add grid lines within the mapping function:

def add_grid(x, y, **kwargs):
    sns.barplot(x=x, y=y, **kwargs)
    plt.grid(True)

g.map(add_grid, "day", "total_bill")
plt.show()

Adding Grid Lines to a Catplot : Practical Examples

Example 1: Visualizing Distribution with Grid Lines

import seaborn as sns
import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

# Create the catplot
g = sns.catplot(x="day", y="total_bill", kind="boxen", data=tips)

# Access the axes object
ax = g.ax

# Add horizontal grid lines
ax.grid(True, axis="y", linestyle="--")
plt.show()

Output:

Visualizing Distribution with Grid Lines

This example adds horizontal grid lines to a boxen plot, making it easier to compare the distribution of total bill amounts across different days.

Example 2: Comparing Categories with Grid Lines

import seaborn as sns
import matplotlib.pyplot as plt

titanic = sns.load_dataset("titanic")

# Create the catplot
g = sns.catplot(x="sex", y="survived", hue="class", kind="bar", data=titanic)

# Access the axes object
ax = g.ax

# Add light gray grid lines
ax.grid(True, axis="y", color="gray", alpha=0.5)
plt.show()

Output:

Comparing Categories with Grid Lines

In this example, grid lines are added to a bar plot comparing the survival rates of different passenger classes across genders. The grid lines help in visually assessing the differences in survival rates.

Customizing Grid Lines

You can further customize the appearance of the grid lines using Matplotlib’s grid() function. For example, you can change the color, linestyle, and linewidth of the grid lines.

import seaborn as sns
import matplotlib.pyplot as plt

exercise = sns.load_dataset("exercise")
g = sns.catplot(x="time", y="pulse", hue="kind", col="diet", data=exercise)

# Customize grid lines
for ax in g.axes.flat:
    ax.grid(True, color='r', linestyle='--', linewidth=0.5)
plt.show()

Output:

Customizing Grid Lines

Conclusion

In conclusion, adding grid lines to Seaborn catplots can significantly improve the clarity and interpretability of our visualizations. By using the ax.grid() and FacetGrid & map method, we can easily customize the appearance of the grid lines to suit our specific needs.