Remap values in Pandas DataFrame columns using map() function

Remap values in Pandas columns using replace() 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)

Output:

Using dictionary to remap values in Pandas DataFrame columns

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.

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#AI-ML-DS With Python #Python pandas-dataFrame #Python-pandas #Pandas #Python #python

Remap values in Pandas columns using replace() function

Remap values in Pandas DataFrame columns using map() function

Python3

Using dictionary to remap values in Pandas DataFrame columns

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