Books & Videos

Table of Contents

Chapter: Introduction

Introduction

02m 10s

Chapter: Lesson 1: Installing and Running Python

Learning objectives

00m 22s

1.1 Understand why Python/Pandas for data analytics

00m 56s

1.2 Install Python

03m 23s

1.3 Run Python

06m 23s

Chapter: Lesson 2: Pandas Basics

Learning objectives

00m 26s

2.1 Load your first data set

06m 29s

2.2 Look at your data

16m 20s

2.3 Analyze your first data set

06m 38s

Chapter: Lesson 3: Pandas Data Structures

Learning objectives

00m 32s

3.1 Create data structures

04m 24s

3.2 Use Pandas Series

09m 2s

3.3 Use Pandas DataFrame

08m 9s

3.4 Import and Export data

08m 9s

Chapter: Lesson 4: Introduction to Plotting

Learning objectives

00m 23s

4.1 Understand why data visualization is important

08m 2s

4.2 Create basic plots in matplotlib

10m 47s

4.3 Create basic plots in seaborn

27m 41s

4.4 Use plotting in Pandas

04m 36s

Chapter: Lesson 5: Data Assembly

Learning objectives

00m 26s

5.1 Concatenate data (stitch data)

12m 45s

5.2 Merge data (denormalization)

10m 12s

Chapter: Lesson 6: Missing Data

Learning objectives

00m 28s

6.1 Understand the concept of a NaN value

08m 44s

6.2 Work with missing data

10m 17s

Chapter: Lesson 7: Tidy Data

Learning objectives

00m 44s

7.1 Understand the concept of tidy data

01m 47s

7.2 Melt your data when columns contain values not variables (melt)

05m 28s

7.3 Melt and parse when columns contain multiple variables

08m 53s

7.4 Pivot data when variables are in both rows and columns

04m 8s

7.5 Normalize data by separating multiple observational units in a table

04m 59s

7.6 Denormalize and assemble data when observational units are across multiple tables

04m 54s

Chapter: Summary

Summary

00m 45s