Iterate over rows in a dataframe in Pandas

import modules

import pandas as pd
import numpy as np

create dummy dataframe

raw_data = {'name': ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'],
		        'age': [20, 19, 22, 21],
		        'favorite_color': ['blue', 'red', 'yellow', "green"],
		        'grade': [88, 92, 95, 70]}
df = pd.DataFrame(raw_data, columns = ['name', 'age', 'favorite_color', 'grade'])
df
name age favorite_color grade
0 Willard Morris 20 blue 88
1 Al Jennings 19 red 92
2 Omar Mullins 22 yellow 95
3 Spencer McDaniel 21 green 70

Iterate over rows in Pandas dataframe

Using iterrows:

for index, row in df.iterrows():
    print (row["name"], row["age"])

Willard Morris 20
Al Jennings 19
Omar Mullins 22
Spencer McDaniel 21

Using itertuples:

for row in df.itertuples(index=True, name='Pandas'):
    print (getattr(row, "name"), getattr(row, "age"))
	
Willard Morris 20
Al Jennings 19
Omar Mullins 22
Spencer McDaniel 21

If you wish to modify the rows you're iterating over, then df.apply is preferred:

def valuation_formula(x):
    return x * 0.5

df['age_half'] = df.apply(lambda row: valuation_formula(row['age']), axis=1)

df.head()
name age favorite_color grade age_half
0 Willard Morris 20 blue 88 10.0
1 Al Jennings 19 red 92 9.5
2 Omar Mullins 22 yellow 95 11.0
3 Spencer McDaniel 21 green 70 10.5