Pandas DataFrame Items Method

Introduction

In this lab, we will learn how to use the items() method in the Pandas library to iterate over a DataFrame's columns. This method returns a generator object that contains tuples of column names and their corresponding Series.

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Import the necessary libraries

First, we need to import the pandas library:

import pandas as pd

Create a DataFrame

Next, let's create a DataFrame with some sample data:

df = pd.DataFrame({
    "Name": ["Navya", "Vindya"],
    "Age": [25, 24],
    "Education": ["M.Tech", "Ph.d"]
}, index=['id001', 'id002'])

Iterate over column names

To iterate over the column names of the DataFrame, we can use the items() method. This method returns a generator object. We can print it or iterate over it using a for loop:

print("Iterating over column names using items():")

for column_name, data in df.items():
    print('Column Name:', column_name)

Iterate over column values

To access the values of each column, we can use the items() method in combination with a for loop. Each iteration will return a tuple of the column name and the corresponding Series:

print("Iterating over column values using items():")

for column_name, data in df.items():
    print('Column Name:', column_name)
    print('Data:', data)

Iterate over a specific row

To iterate over a specific row, we can use the index number and access the row through the Series object:

print("Iterating over a specific row using items():")

for column_name, data in df.items():
    print('Column Name:', column_name)
    print('Data:', data[0])  ## Access the first item of the Series

Iterate over a specific column

To iterate over a specific column, we can use the column name as an index for the data object:

print("Iterating over a specific column using items():")

for column_name, data in df.items():
    print('Column Name:', column_name)
    print('Data:', data['id001'])  ## Access the value at 'id001' index

Summary

In this lab, we learned how to use the items() method in the Pandas library to iterate over a DataFrame's columns. We saw how to iterate over column names, column values, specific rows, and specific columns. The items() method provides a convenient way to explore and manipulate data within a DataFrame.