iterrows for dataframes in Python

Let us consider this csv file:

HR_data

.csv

Download CSV • 3.76MB

We can read a csv file using pandas' read_csv function:

import pandas as pd

Let us firstly read and save our csv file and define index_col = 0, telling Python that 1st column is the row names.

hrdata = pd.read_csv("HR_data.csv",index_col = 0)

hrdata.head()

Let us firstly see what happens if we iterate over hrdata?

for i in hrdata:
    print(i)

It returns the column names:

To iterate over various rows and column entries in a data frame we use iterrows function

Here we have two iterator variables: row and col

and our iterable object is hrdata.iterrows( )

for row,col in hrdata.iterrows():
    print("For employee id:" + str(row))
    print(col)
    print('--')

Here row is taking the row name (our employee id)

while col is denoting the values for each row-col combination

Task: Fetch the row and column entries only for department column using iterrows

To achieve this we have filtered our iterator col by 'department'

for row,col in hrdata.iterrows():
    print("For employee id:" + str(row))
    print(col['department'])
    print('--')

Task: Fetch the row and column entries only for department and age columns using iterrows

To achieve this we have filtered our iterator col by providing a list ['department','age']

for row,col in hrdata.iterrows():
    print("For employee id:" + str(row))
    print(col[['department','age']])
    print('--')