Prerequisite: Seaborn, Barplot
In this article, we are going to see how to sort the bar in barplot using Seaborn in python.
Seaborn is an amazing visualization library for statistical graphics plotting in Python. It provides beautiful default styles and color palettes to make statistical plots more attractive. It is built on the top of matplotlib library and also closely integrated to the data structures from pandas.
Approach:
- Import module.
- Create a Dataframe.
- Create a barplot.
- Sort the Dataframe column with DataFrame.sort_values().
- Display the sort Dataframe into the barplot.
So, Let’s implement to sort bar in barplot using seaborn with steps based on the above approach.
Step 1: Import required packages.
Python3
# Import module import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns |
Step 2: Create a Dataframe to create a barplot.
Python3
# Initialize data State = [ "Rajasthan" , "Bihar" , "Madhya Pradesh" , "Gujarat" , "Maharashtra" ] growth = [ 342239 , 94163 , 308245 , 196024 , 307713 ] # Create a pandas dataframe df = pd.DataFrame({ "State" : State, "Growth" : growth}) # Display Dataframe df |
Output:
Step 3: Create a barplot with this Dataframe.
Python3
# make barplot sns.barplot(x = 'State' , y = "Growth" , data = df) |
Output:
Step 4: Let’s sort the Dataframe column(Growth column) with DataFrame.sort_values().
Python3
# sort dataframe df.sort_values( 'Growth' ) |
Output:
We can do this same technique in a barplot.
Python3
# make barplot and sort bars sns.barplot(x = 'State' , y = "Growth" , data = df, order = df.sort_values( 'Growth' ).State) |
Output:
Step 5: Let sort the bar with Descending order.
Python3
# make barplot and sort bars sns.barplot(x = 'State' , y = "Growth" , data = df, order = df.sort_values( 'Growth' ,ascending = False ).State) |
Output:
Note: Default value of ascending is always True, if we change this parameter with False then it means that its arrange in descending order.
Below are the complete examples:
Example 1
Python3
# import module import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns # Initialize data State = [ "Rajasthan" , "Bihar" , "Madhya Pradesh" , "Gujarat" , "Maharashtra" ] growth = [ 342239 , 94163 , 308245 , 196024 , 307713 ] # Create a pandas dataframe df = pd.DataFrame({ "State" : State, "Growth" : growth}) # sort dataframe df.sort_values( 'Growth' ) # make barplot and sort bars sns.barplot(x = 'State' , y = "Growth" , data = df, order = df.sort_values( 'Growth' ).State) |
Output:
Example 2
Python3
# import module import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns # Initialize data State = [ "Rajasthan" , "Bihar" , "Madhya Pradesh" , "Gujarat" , "Maharashtra" ] growth = [ 342239 , 94163 , 308245 , 196024 , 307713 ] # Create a pandas dataframe df = pd.DataFrame({ "State" : State, "Growth" : growth}) # sort dataframe df.sort_values( 'Growth' ) # make barplot and sort bars sns.barplot(x = 'State' , y = "Growth" , data = df, order = df.sort_values( 'Growth' ,ascending = False ).State) |
Output: