Bar Plot in Seaborn is used to show point estimates and confidence intervals as rectangular bars. The seaborn.barplot() is used for this. Plotting horizontal bar plots with dataset columns as x and y values. Use the estimator parameter to set median as the estimate of central tendency.
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 from numpy import median
Load data from a CSV file into a Pandas DataFrame −
dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\Cricketers2.csv")
Plotting horizontal bar plots with Matches and Academy using the estimator parameter to set median as the estimate of central tendency −
sb.barplot(x = dataFrame["Academy"], y = dataFrame["Matches"], estimator = median)
Example
Following is the code −
import seaborn as sb
import pandas as pd
import matplotlib.pyplot as plt
from numpy import median
# Load data from a CSV file into a Pandas DataFrame
dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\Cricketers2.csv")
# plotting horizontal bar plots with Matches and Academy
# using the estimator parameter to set median as the estimate of central tendency
sb.barplot(x = dataFrame["Academy"], y = dataFrame["Matches"], estimator = median)
# display
plt.show()Output
This will produce the following output −
