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