Python | Pandas dataframe.applymap()

Last Updated : 16 Nov, 2018

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Dataframe.applymap() method applies a function that accepts and returns a scalar to every element of a DataFrame.

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Syntax: DataFrame.applymap(func)

Parameters:
func: Python function, returns a single value from a single value.

Returns: Transformed DataFrame.

For link to CSV file Used in Code, click here

Example #1: Apply the applymap() function on the dataframe to find the no. of characters in all cells.

# importing pandas as pd
import pandas as pd
  
# Making data frame from the csv file
df = pd.read_csv("nba.csv")
  
# Printing the first 10 rows of 
# the data frame for visualization
df[:10]

# Using lambda function we first convert all 
# the cell to a string value and then find
# its length using len() function
df.applymap(lambda x: len(str(x)))

Output:

Notice how all nan value has been converted to string nan and their length is evaluated to be 3.

Example #2: Append _X in each cell using applymap() function.

In order to append _X in each cell, first convert each cell into a string.

# importing pandas as pd
import pandas as pd
  
# Making data frame from the csv file
df = pd.read_csv("nba.csv")
  
# Using applymap() to append '_X'
# in each cell of the dataframe
df.applymap(lambda x: str(x) + '_X')

Output:

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Python | Pandas dataframe.applymap()