In Python, we can normally plot barcharts for numerical variables. But when it comes to the case of categorical variables then we cannot normally plot the count for each category. Here comes Seaborn Catplot in the picture. It allows you to plot the count of each category for non-numerical/categorical variables.
Creating the CountplotĀ
Countplot gives a graphical visual for the count of observations in each category using bars. This cannot be used for quantitative variables. It can be created by passing the count value to the kind parameter.
Example: Letās take an example of a titanic dataset.
Python3
# import libraries import matplotlib.pyplot as plt import seaborn as sns Ā Ā # setting background style sns.set_style('darkgrid') Ā Ā # import dataset data = sns.load_dataset('titanic') data.head() |
Output:
Example 1: Creating the countplot
Python3
# plot for count of passengers belonging # to each gender sns.catplot(x='sex', kind='count', data=data) plt.xlabel("Gender") plt.ylabel("Count") |
Output:
Example 2: Creating the grouped countplot
Python3
# Grouped Countplot/Barplot # Count of passengers who survived # or didn't of each gender sns.catplot(x='sex', hue='survived', Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā kind='count', data=data) Ā Ā plt.xlabel("Gender") plt.ylabel("Count") |
Output:
Example 3: Creating the horizontal countplot
Python3
# Plotting horizontally sns.catplot(y='sex', hue='survived',Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā kind='count', data=data) Ā Ā plt.xlabel("Count") plt.ylabel("Gender") |
Output:
