How to iterate over rows in a DataFrame in Pandas

tl;dr

Using the DataFrame.iterrows() method, you can iterate over the rows of a DataFrame in Pandas. To do this, first create a DataFrame with the desired columns and values. Then, use the reset_index() method to ensure that the indexes of the DataFrame correspond to the number of rows. Finally, use the iterrows() method to iterate over the rows of the DataFrame. This method yields both the index and row (as a Series) of each row. For example, the following code will print the values of the columns c1 and c2 for each row of the DataFrame:

import pandas as pd

df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})
df = df.reset_index()  # make sure indexes pair with number of rows

for index, row in df.iterrows():
    print(row['c1'], row['c2'])

This will output the following:

10 100
11 110
12 120