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Python Pandas - Draw a point plot and control order by passing an explicit order with Seaborn
Point Plot in Seaborn is used to show point estimates and confidence intervals using scatter plot glyphs. The seaborn.pointplot() is used for this. For explicit order, use the order parameter of the pointplot() method.
Let’s say the following is our dataset in the form of a CSV file − Cricketers.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\Cricketers.csv")
Plotting point plot with “Academy” and “Age”. Control order by passing an explicit order i.e. ordering on the basis of "Academy". Ordering using the order parameter −
sb.pointplot( x = 'Academy',y = 'Age', data = dataFrame, order=["Tasmania", "South Australia", "Victoria"] )
Example
Following is the complete 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\Cricketers.csv") sb.set_theme(style="darkgrid") # plotting point plot with Academy and Age # Control order by passing an explicit order i.e. ordering on the basis of "Academy" # ordering using the order parameter sb.pointplot( x = 'Academy',y = 'Age', data = dataFrame, order=["Tasmania", "South Australia", "Victoria"] ) # display plt.show()
Output
This will produce the following output −
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