While working with data in Pandas, we perform a vast array of operations on the data to get the data in the desired form. One of these operations could be that we want to remap the values of a specific column in the DataFrame. Let’s discuss several ways in which we can do that.
Given a Dataframe containing data about an event, remap the values of a specific column to a new value.
Code #1: We can use DataFrame.replace() function to achieve this task. Let’s see how we can do that.
# importing pandas as pd import pandas as pd # Creating the DataFrame df = pd.DataFrame({'Date':['10/2/2011', '11/2/2011', '12/2/2011', '13/2/2011'], 'Event':['Music', 'Poetry', 'Theatre', 'Comedy'], 'Cost':[10000, 5000, 15000, 2000]}) # Print the dataframe print(df) |
Output :
Now we will remap the values of the ‘Event’ column by their respective codes.
# Create a dictionary using which we # will remap the values dict = {'Music' : 'M', 'Poetry' : 'P', 'Theatre' : 'T', 'Comedy' : 'C'} # Print the dictionary print(dict) # Remap the values of the dataframe df.replace({"Event": dict}) |
Output :
Code #2: We can use map() function to achieve this task.
# importing pandas as pd import pandas as pd # Creating the DataFrame df = pd.DataFrame({'Date':['10/2/2011', '11/2/2011', '12/2/2011', '13/2/2011'], 'Event':['Music', 'Poetry', 'Theatre', 'Comedy'], 'Cost':[10000, 5000, 15000, 2000]}) # Print the dataframe print(df) |
Output :
Now we will remap the values of the ‘Event’ column by their respective codes.
# Create a dictionary using which we # will remap the values dict = {'Music' : 'M', 'Poetry' : 'P', 'Theatre' : 'T', 'Comedy' : 'C'} # Print the dictionary print(dict) # Remap the values of the dataframe df['Event']= df['Event'].map(dict) # Print the DataFrame after modification print(df) |
Output :
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