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Iterating over a DataFrame to access and process each row

Mohamad Mahmood's photo
Mohamad Mahmood
·

1 min read

import pandas as pd

# Example DataFrame
df = pd.DataFrame({'Column1': [1, 2, 3], 'Column2': ['A', 'B', 'C']})

# Iterate over the DataFrame
for index, row in df.iterrows():
    column1_value = row['Column1']
    column2_value = row['Column2']
    print(f"Row {index}: Column1={column1_value}, Column2={column2_value}")

output:

To iterate over a DataFrame and add values to a specific column, you can use the iterrows() function in pandas.

import pandas as pd

# Example DataFrame
df = pd.DataFrame({'Column1': [1, 2, 3], 'Column2': ['A', 'B', 'C']})

# Iterate over the DataFrame and add values to a column
for index, row in df.iterrows():
    new_value = row['Column1'] + 10
    df.at[index, 'Column1'] = new_value

print(df)

output:

iterrowsPythonpandas