Data Wrangling with Python

: 6 Months
: Self Paced, AI Tutor
: Intermediate
: Available Immediately

R6200,00R7300,00

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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

Lessons 1: Introduction

  • About
  • About the Course

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

Appendix A: Data Structures, Strings, and Numpy

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

 

Training Method

Self paced, AI Tutor

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