Python Pandas DataFrame items() Function

Pandas DataFrame items() Function:

The items() function of the pandas dataframe iterates over the (column name, Series) pairs.

Iterate over the DataFrame columns with the items() method of the Pandas DataFrame, which returns a tuple containing the column name and the content as a Series.

Syntax:

DataFrame.items()

Parameters: This method doesn’t accept any parameters

Return Value:

Gives the following:

label: This is required. The type of this is an object. The names of the columns in the DataFrame being iterated over.

content: This is required. The type of this is a series. The column entries belonging to each label, as a Series.

Pandas DataFrame items() Function in Python

Approach:

Import pandas module using the import keyword.
Import NumPy module using the import keyword.
Pass some random key-value pair(dictionary), index list as arguments to the DataFrame() function of the pandas module to create a dataframe
Print the given dataframe
Loop in the label and data of the dataframe using the for loop and the items() functions and print the corresponding label and data.
The Exit of the Program.

Below is the implementation:

# 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
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("The given Dataframe:")
print(data_frme)
print()
# Loop in the label and data of the dataframe using the for loop and the items() functions
# and print the corresponding label and data
for label, data in data_frme.items():
  print(f'label: {label}')
  print(f'data: \n{data}')
  print()

Output:

The given Dataframe:
  emp_name  emp_age  emp_salary
1     john       25       25000
2     nick       35       40000
3    jessy       38       22000
4     mary       22       80000

label: emp_name
data: 
1     john
2     nick
3    jessy
4     mary
Name: emp_name, dtype: object

label: emp_age
data: 
1    25
2    35
3    38
4    22
Name: emp_age, dtype: int64

label: emp_salary
data: 
1    25000
2    40000
3    22000
4    80000
Name: emp_salary, dtype: int64

Pandas DataFrame items() Function in Python

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