# Data Visualization with Python

(DATA-VIS-PYTHON.AJ2)/ISBN:978-1-64459-434-6

This course includes
Lessons
TestPrep
LiveLab

#### Lessons

9+ Lessons | 55+ Quizzes | 36+ Flashcards | 36+ Glossary of terms

#### TestPrep

33+ Pre Assessment Questions | 34+ Post Assessment Questions |

#### Hand on lab

54+ LiveLab | 37+ Video tutorials | 45+ Minutes

#### Video Lessons

47+ Videos | 06:36+ Hours

# Here's what you will learn

### Lessons 2: Introduction to Visualization with Python – Basic and Customized Plotting

• Introduction
• Handling Data with pandas DataFrame
• Plotting with pandas and seaborn
• Tweaking Plot Parameters
• Summary

### Lessons 3: Static Visualization – Global Patterns and Summary Statistics

• Introduction
• Creating Plots that Present Global Patterns in Data
• Creating Plots That Present Summary Statistics of Your Data
• Summary

### Lessons 4: From Static to Interactive Visualization

• Introduction
• Static versus Interactive Visualization
• Applications of Interactive Data Visualizations
• Getting Started with Interactive Data Visualizations
• Summary

### Lessons 5: Interactive Visualization of Data across Strata

• Introduction
• Interactive Scatter Plots
• Other Interactive Plots in altair
• Summary

### Lessons 6: Interactive Visualization of Data across Time

• Introduction
• Temporal Data
• Types of Temporal Data
• Understanding the Relation between Temporal Data and Time-Series Data
• Examples of Domains That Use Temporal Data
• Visualization of Temporal Data
• Choosing the Right Aggregation Level for Temporal Data
• Resampling in Temporal Data
• Interactive Temporal Visualization
• Summary

### Lessons 7: Interactive Visualization of Geographical Data

• Introduction
• Choropleth Maps
• Plots on Geographical Maps
• Summary

### Lessons 8: Avoiding Common Pitfalls to Create Interactive Visualizations

• Introduction
• Data Formatting and Interpretation
• Data Visualization
• Cheat Sheet for the Visualization Process
• Summary

# Hands-on LAB Activities

### Introduction to Visualization with Python – Basic and Customized Plotting

• Creating a User-defined Function
• Applying the ceil() Function on a DataFrame Column
• Adding a Column to a DataFrame
• Applying the describe() Function
• Viewing Data from Dataset
• Deleting Columns from a DataFrame
• Reading Data from a File
• Creating a Bar Plot and Calculating the Mean Growth Rate Distribution
• Creating Bar Plot Grouped by a Specific Feature
• Plotting a Histogram
• Tweaking the Plot Parameters of a Grouped Bar Plot
• Annotating a Bar Chart

### Static Visualization – Global Patterns and Summary Statistics

• Presenting Data across Time with Multiple Line Plots
• Creating a Static Line Plot
• Creating a Static Hexagonal Binning Plot
• Creating a Static Scatter Chart
• Creating a Static Contour Plot
• Creating a Static Heatmap
• Creating a Linkage in a Static Heatmap
• Creating a Static Box Plot
• Creating a Static Violin Plot

### From Static to Interactive Visualization

• Creating the Base Static Plot for Interactive Data Visualization
• Adding a Slider to the Static Plot
• Adding a Hover Tool to a Scatter Plot Using bokeh
• Creating an Interactive Scatter Plot
• Using the merge() function

### Interactive Visualization of Data across Strata

• Adding Zoom-In and Zoom-Out to a Static Scatter Plot Using altair
• Adding Hover and Tooltip Functionality to a Scatter Plot Using altair
• Exploring Select and Highlight Functionality on a Scatter Plot Using altair
• Performing Selection across Multiple Plots
• Performing a Selection Based on the Values of a Feature
• Adding the Zoom Feature and Calculating the Mean on a Static Bar Plot
• Representing the Mean on a Bar Plot using a Shortcut
• Linking a Bar Plot and a Heatmap Dynamically
• Adding a Zoom Feature on a Static Heatmap
• Creating a Bar Plot and a Heatmap Next to Each Other

### Interactive Visualization of Data across Time

• Calculating zscore to Find Outliers in Temporal Data
• Performing Upsampling and Downsampling in Temporal Data
• Using shift and tshift to Shift Time in Data
• Adding Zoom-in and Zoom-out Functionality on a Line Plot Using Bokeh
• Adding Interactivity to Static Line Plots using Bokeh
• Changing the Line Color and Width on a Line Plot
• Adding Box Annotations to Find Anomalies in a Dataset

### Interactive Visualization of Geographical Data

• Creating a Worldwide Choropleth Map
• Tweaking a Worldwide Choropleth Map
• Adding Animation to a Choropleth Map
• Creating a Choropleth Map for the US Population across States
• Creating a Scatter Plot on a Geographical Map
• Creating a Bubble Plot on a Geographical Map
• Creating Line Plots on a Geographical Map

### Avoiding Common Pitfalls to Create Interactive Visualizations

• Visualizing Outliers in a Dataset with a Box Plot
• Dealing with Outliers
• Dealing with Missing Values
• Creating a Confusing Visualization