modify a dataframe row values from another row values using a function in python

You can use the .apply() function on a pandas dataframe to apply a function to each row of the dataframe. Within this function, you can modify the values of a row based on the values of another row.

Here's an example of how you can modify a row based on another row using .apply():

main.py
import pandas as pd

# create a sample dataframe
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})

# define a function to modify a row based on another row
def modify_row(row):
    row['A'] = row['B'] + row['C']  # modify column A
    return row

# apply the function to each row of the dataframe
df = df.apply(modify_row, axis=1)
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In this example, the modify_row() function modifies the value of column A based on the values in columns B and C. This function is applied to each row of the dataframe using .apply() with axis=1. The resulting dataframe df will have the modified values in column A.