How to iterate over Elements of Row in Pandas DataFrame?

Pandas DataFrame - Iterate over Elements of Row

To iterate over the elements of a Row in Pandas DataFrame, you can use incremental index with DataFrame.at[] or get the row and use Series.items().

Examples

1. Iterate over elements of a row in DataFrame using Index

In this example, we will

• Initialize a DataFrame with some numbers.
• Get the specific row.
• Get the number of columns.
• Use for loop to iterate over the elements.

Python Program

import pandas as pd
import numpy as np

df = pd.DataFrame(
	[['a', 'b', 'c'],
	['d', 'e', 'f'],
	['g', 'h', 'i'],
	['j', 'k', 'l']])

row = df.iloc[1] #index=1 => second row
length = row.size
for i in range(length):
    print(row[i])

Output

d
e
f

2. Iterate over elements of a row in DataFrame using Series.items()

In this example, we will

• Initialize a DataFrame with some numbers.
• Get the specific row as Series using DataFrame.iloc property.
• Iterate over items of this row using Series.items()

Python Program

import pandas as pd
import numpy as np

df = pd.DataFrame(
	[['a', 'b', 'c'],
	['d', 'e', 'f'],
	['g', 'h', 'i'],
	['j', 'k', 'l']])

row = df.iloc[1] #index=1 => second row
for index, item in row.items():
    print(item)

Output

d
e
f

Summary

In this tutorial of Python Examples, we learned how to iterate over elements of a specific row in Pandas DataFrame, with the help of example programs.