Pandas DataFrame iterrows() Function:
Pandas dataframe iterrows: Iterate through the DataFrame rows with the iterrows() function of the Pandas DataFrame, which returns a tuple with the row index and the row data as a Series.
Syntax:
DataFrame.iterrows()
Parameters: This method doesn’t accept any parameters
Return Value:
Gives the following:
index: label or a tuple of label
This is required. The row’s index number. A tuple for a MultiIndex.
data: Series
This is required. It is the data of the row as a Series.
it: generator
This is required. A generator that loops across the rows of the frame.
Pandas DataFrame iterrows() Function in Python
Approach:
Below is the implementation:
Output:
# Import pandas module using the import keyword.
import pandas as pd
# Import NumPy module using the import keyword.
import numpy as np
# Pass some random key-value pair(dictionary), index list as arguments to the
# DataFrame() function of the pandas module to create a dataframe
# Store it in a variable.
data_frme = pd.DataFrame({
"emp_name": ["john", "nick" , "jessy", "mary"],
"emp_age": [25, 35, 38, 22],
"emp_salary": [25000, 40000, 22000, 80000]},
index= [1, 2, 3, 4]
)
print("The given DataFrame:")
print(data_frme)
print()
for label, data in data_frme.iterrows():
print(f'label: {label}')
print(f'data: \n{data}')
print()