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Apply Function in Panda

Apply function in pands is one of the commonly used functions for manipulating a pandas dataframe and creating new variables. Pandas Apply function returns some value after passing each row/column of a data frame with some function. The function can be both default or user-defined.

Applying a function to all rows in a Pandas DataFrame is one of the most common operations during data wrangling. Pandas DataFrame apply function is the most obvious choice for doing it. It takes a function as an argument and applies it along an axis of the DataFrame. However, it is not always the best choice.


Lets start with importing the panda

import pandas as pd

Now function to add,

def add(a, b, c):
    return a + b + c

Here is the main function for running the overall program

def main():
# create a dictionary with
# three fields each
data = {
    'A':[1, 2, 3],
    'B':[4, 5, 6],
    'C':[7, 8, 9] }
# Convert the dictionary into DataFrame
df = pd.DataFrame(data)
print("Original DataFrame:\n", df)
df['add'] = df.apply(lambda row : add(row['A'], row['B'], row['C']), axis = 1)
print('\nAfter Applying Function: '
# printing the new dataframe
print(df)

The Output for above code :



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