Using dictionary to remap values in Pandas DataFrame columns

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While working with data in Pandas in Python, 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.

Creating Pandas DataFrame to remap values

Given a Dataframe containing data about an event, remap the values of a specific column to a new value.

Python3

# 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:

Remap values in Pandas columns using replace() function

Now we will remap the values of the ‘Event’ column by their respective codes using replace() function.

Python3

# 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 :

Remap values in Pandas DataFrame columns using map() function

Now we will remap the values of the ‘Event’ column by their respective codes using map() function.

Python3

# 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)