Interactive Pandas Practice

Name: Interactive Pandas Practice
Availability: InStock
Author: FreeAcademy

Intermediate

Assumes foundational knowledge. Builds on basics.

Master data analysis with Pandas through hands-on exercises. Learn to create, manipulate, filter, group, and transform DataFrames in your browser. Practice real-world data wrangling with live Python execution.

Course Content

8 modules • 32 lessons

Getting Started with Pandas

5 lessons

1.1

DataFrame Info & Stats

Selecting & Indexing Data

4 lessons

2.1

Selecting Columns

2.2

Selecting Rows with loc & iloc

2.3

Boolean Indexing

2.4

Setting & Resetting Index

Filtering & Sorting

4 lessons

3.1

Filtering Data

3.2

The query() Method

3.3

Sorting Data

3.4

Top N Values

Data Transformation

5 lessons

4.1

Adding & Modifying Columns

4.2

The apply() Function

4.3

String Methods

4.4

DateTime Handling

4.5

Type Conversion

Grouping & Aggregation

4 lessons

5.1

GroupBy Basics

5.2

Multiple Aggregations

5.3

Pivot Tables

5.4

Cross Tabulation

Handling Missing Data

3 lessons

6.1

Detecting Missing Values

6.2

Filling Missing Values

6.3

Dropping Missing Values

Combining DataFrames

3 lessons

7.1

Concatenating DataFrames

7.2

Merging DataFrames

7.3

Join Types

Advanced Operations

4 lessons

8.1

Handling Duplicates

8.2

Value Counts & Unique

8.3

Binning Data

8.4

Interactive Pandas Practice

Course Content

Getting Started with Pandas

Introduction to Pandas

Creating Series

Creating DataFrames

Reading Data

DataFrame Info & Stats

Selecting & Indexing Data

Selecting Columns

Selecting Rows with loc & iloc

Boolean Indexing

Setting & Resetting Index

Filtering & Sorting

Filtering Data

The query() Method

Sorting Data

Top N Values

Data Transformation

Adding & Modifying Columns

The apply() Function

String Methods

DateTime Handling

Type Conversion

Grouping & Aggregation

GroupBy Basics

Multiple Aggregations

Pivot Tables

Cross Tabulation

Handling Missing Data

Detecting Missing Values

Filling Missing Values

Dropping Missing Values

Combining DataFrames

Concatenating DataFrames

Merging DataFrames

Join Types

Advanced Operations

Handling Duplicates

Value Counts & Unique

Binning Data

Reshaping Data

Interactive Pandas Practice

Course Content

Getting Started with Pandas

Introduction to Pandas

Creating Series

Creating DataFrames

Reading Data

DataFrame Info & Stats

Selecting & Indexing Data

Selecting Columns

Selecting Rows with loc & iloc

Boolean Indexing

Setting & Resetting Index

Filtering & Sorting

Filtering Data

The query() Method

Sorting Data

Top N Values

Data Transformation

Adding & Modifying Columns

The apply() Function

String Methods

DateTime Handling

Type Conversion

Grouping & Aggregation

GroupBy Basics

Multiple Aggregations

Pivot Tables

Cross Tabulation

Handling Missing Data

Detecting Missing Values

Filling Missing Values

Dropping Missing Values

Combining DataFrames

Concatenating DataFrames

Merging DataFrames

Join Types

Advanced Operations