Bar Plot in Seaborn is used to show point estimates and confidence intervals as rectangular bars. The seaborn.barplot() is used for this. Plotting vertical bar plots grouped by a categorical variable, by passing categorical variables using x, y or hue parameter.
Let’s say the following is our dataset in the form of a CSV file − Cricketers2.csv
At first, import the required libraries −
import seaborn as sb import pandas as pd import matplotlib.pyplot as plt
Load data from a CSV file into a Pandas DataFrame −
dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\Cricketers2.csv")
Plotting vertical bar plots grouped by two categorical variables. The hue parameter also set
sb.barplot(x = dataFrame["Role"], y = dataFrame["Matches"], hue = "Academy", data= dataFrame)
Example
Following is the code −
import seaborn as sb import pandas as pd import matplotlib.pyplot as plt # Load data from a CSV file into a Pandas DataFrame dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\Cricketers2.csv") # plotting vertical bar plots grouped by two categorical variables # hue parameter also set sb.barplot(x = dataFrame["Role"], y = dataFrame["Matches"], hue = "Academy", data= dataFrame) # display plt.show()
Output
This will produce the following output −