# Loop & Iterate Over Rows of pandas DataFrame in Python (Example Code)

In this tutorial, I’ll demonstrate how to loop over the rows of a pandas DataFrame in the Python programming language.

## Setting up the Example

import pandas as pd # Load pandas library |

import pandas as pd # Load pandas library

my_df = pd.DataFrame({'A':range(10, 15), # Construct pandas DataFrame 'B':['x', 'y', 'y', 'x', 'x'], 'C':range(15, 10, - 1)}) print(my_df) # A B C # 0 10 x 15 # 1 11 y 14 # 2 12 y 13 # 3 13 x 12 # 4 14 x 11 |

my_df = pd.DataFrame({'A':range(10, 15), # Construct pandas DataFrame 'B':['x', 'y', 'y', 'x', 'x'], 'C':range(15, 10, - 1)}) print(my_df) # A B C # 0 10 x 15 # 1 11 y 14 # 2 12 y 13 # 3 13 x 12 # 4 14 x 11

## Example: Apply for Loop to Rows of pandas DataFrame Using iterrows() Function

for i, row in my_df.iterrows(): # Use iterrows to print output print('This is my row at index position', i, ': A =', row['A'], '-', 'B =', row['B'], '-', 'C =', row['C']) # This is my row at index position 0 : A = 10 - B = x - C = 15 # This is my row at index position 1 : A = 11 - B = y - C = 14 # This is my row at index position 2 : A = 12 - B = y - C = 13 # This is my row at index position 3 : A = 13 - B = x - C = 12 # This is my row at index position 4 : A = 14 - B = x - C = 11 |

for i, row in my_df.iterrows(): # Use iterrows to print output print('This is my row at index position', i, ': A =', row['A'], '-', 'B =', row['B'], '-', 'C =', row['C']) # This is my row at index position 0 : A = 10 - B = x - C = 15 # This is my row at index position 1 : A = 11 - B = y - C = 14 # This is my row at index position 2 : A = 12 - B = y - C = 13 # This is my row at index position 3 : A = 13 - B = x - C = 12 # This is my row at index position 4 : A = 14 - B = x - C = 11

## Related Articles

Furthermore, you may want to read the other tutorials on my homepage: