Gain insights into using Python Pandas for efficient data analysis and manipulation. Delve into detailed functions, parameters, and methods to elevate your data handling skills.

A Comprehensive Practical Guide to Python Pandas_ .png

There are several exercises that focus on how to use a particular function and method. The functions are covered in detail by explaining the important parameters and how to use them. By completing this course, you will be able to do data analysis and manipulation with Pandas easily and efficiently.

Mastering Data Analysis with Python Pandas

## Problem statement

The `staff` contains the `start_date` and `date_of_birth` columns. We’re asked to find the age of employees at the time they were hired in years. For instance, if an employee was born in 1991 and started working in 2021, then the answer should be 30.

# Problem statement

The `staff` contains the `start_date` and `date_of_birth` columns. We’re asked to find the age of employees at the time they were hired in years. For instance, if an employee was born in 1991 and started working in 2021, then the answer should be 30.

Learn how to find the difference between two dates with Pandas.

Course Introduction

Pandas Data Structures

Creating a Data Frame

Exploring a Data Frame

Filtering a Data Frame

String Manipulation with Pandas

Date Manipulation with Pandas

Handling Missing Values with Pandas

Data Analysis with Pandas

Data Visualization with Pandas

Combining DataFrames with Pandas

Final Challenge and Quiz

Challenge: The Age of Employees

Problem statement