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How to modify a subset of rows in a pandas DataFrame?

Given a Pandas DataFrame, we have to modify a subset of rows. By Pranit Sharma Last updated : September 22, 2023

Sometimes, we need to modify a column value based upon another column value. For example, if you have two columns 'A' and 'B', and you want the value of 'B' to be Nan whenever the value of 'A' becomes 0. This can be done with the help of the pandas.DataFrame.loc property.

import pandas as pd

Let us understand with the help of an example,

Create and print a pandas dataframe

# Importing pandas package
import pandas as pd

# Importing numpy package
import numpy as np

# Creating a dictionary
d = {
    'A':[10,20,30,40,0,0,0,50],
    'B':[1,1,1,1,0,0,0,1]
}

# Creating a DataFrame
df = pd.DataFrame(d)

# Display DataFrame
print("Created DataFrame:\n",df,"\n")

Output

The output of the above program is:

Modifying a subset of rows in a pandas DataFrame

Now, we will use the loc[] property for modifying a column value, suppose we want a value to be set for a column whenever a certain condition is met for another column, we can use the following concept:

df.loc[selection criteria, columns I want] = value

Let us observe the following code snippet,

Python code to modify a subset of rows

# Applying condition and modifying 
# the column value
df.loc[df.A==0, 'B'] = np.nan

# Display modified DataFrame
print("Modified DataFrame:\n",df)

Output

The output of the above program is:

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