Mastering Data Analysis with Python Pandas

Takeaway Skills

Hands-on experience with Python Pandas

Learn about data analysis and manipulation functions of Python Pandas

Hands-on experience with Python Pandas

Learn about data analysis and manipulation functions of Python Pandas

Course Overview

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... See More

How You'll Learn

Hands-on coding environments

You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.

Faster than videos

Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.

No set-up required

Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.

Progress you can show

Built in assessments let you test your skills. Completion certificates let you show them off.

Hands-on coding environments

You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.

Faster than videos

Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.

No set-up required

Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.

Progress you can show

Built in assessments let you test your skills. Completion certificates let you show them off.

Course Contents

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1. Course Introduction

Why Should You Take This Course?

What Will You Achieve by Completing This Course?

2. Pandas Data Structures

Pandas Series

Pandas DataFrame

3. Creating a Data Frame

Reading Data from a File

Create a DataFrame

4. Exploring a Data Frame

Size of a DataFrame

Data Types of Columns

Different Values in a Column

Measures of Central Tendency

Challenge: Find the Most Frequent Values in a Column

Quiz Yourself: Exploring a DataFrame

5. Filtering a Data Frame

Why Do We Need Filtering?

Filtering with "loc" and "iloc" Methods

Filtering by Selecting a Subset of Columns

Filtering by Condition

Filtering Rows with the Query Function

Challenge: Filter Out the Values Below Average

Quiz Yourself: Filtering a DataFrame

6. String Manipulation with Pandas

Slicing and Indexing on Strings

Splitting and Combining Strings

Converting Strings to Upper and Lower Case

Challenge: Create City and State Columns from the Address

Replacing Characters in a String

Chained Operations

Challenge: Make the Salary Column Proper

Quiz Yourself: String Manipulation with Pandas

7. Date Manipulation with Pandas

Pandas Date and Time Data Types

Extracting Information from Dates

The dt Accessor

Manipulating Dates by Adding Time Intervals

Challenge: The Age of Employees

Quiz Yourself: Date Manipulation

8. Handling Missing Values with Pandas

Missing Value Types and Representation

Finding the Missing Values

Dropping Rows and Columns with Missing Values

Replacing the Missing Values

Challenge: Filling the Missing Values

Quiz Yourself: Handling Missing Values

9. Data Analysis with Pandas

The groupby Function

Enhancing the groupby Function

Challenge: Find the Weekly Sales Quantities

The Pivot Table Function

The Cut and Qcut Functions

Challenge: Categorize Groceries Based on Price

The "where" Function

Quiz Yourself: Data Analysis with Pandas

10. Data Visualization with Pandas

Histogram

Line Plot

Scatter Plot

Quiz Yourself: Data Visualization with Pandas

11. Combining DataFrames with Pandas

The Concat Function

The Merge Function

Quiz Yourself: Combining DataFrames with Pandas

12. Final Challenge and Quiz

Final Challenge: Find the Day of Week with the Most Sales

Final Quiz