Data Visualization with Python

(DATA-VIS-PYTHON.AJ1) / ISBN: 9781644592519
This course includes
Lessons
TestPrep
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Data Visualization with Python

Enroll yourself in the Data Visualization with Python course and lab to gain hands-on expertise on python data visualization. The course sharpens your data exploration skills and provides an excellent takeoff in your remarkable journey of creating interactive data visualizations with Python. You will begin by learning how to draw various plots with Matplotlib and Seaborn, the non-interactive data visualization libraries. You will also study different types of visualizations, learn the principles of intuitive and persuasive data visualization, and use Altair, Bokeh, and Plotly to transform your visuals into strong stories.
Here's what you will get

Lessons
  • 9+ Lessons
  • 55+ Quizzes
  • 36+ Flashcards
  • 36+ Glossary of terms
TestPrep
  • 33+ Pre Assessment Questions
  • 34+ Post Assessment Questions
Video Lessons
  • 78+ Videos
  • 12:16+ Hours
Here's what you will learn
Download Course Outline
  • About
  • About the Course
  • Introduction
  • Handling Data with pandas DataFrame
  • Plotting with pandas and seaborn
  • Tweaking Plot Parameters
  • Summary
  • Introduction
  • Creating Plots that Present Global Patterns in Data
  • Creating Plots That Present Summary Statistics of Your Data
  • Summary
  • Introduction
  • Static versus Interactive Visualization
  • Applications of Interactive Data Visualizations
  • Getting Started with Interactive Data Visualizations
  • Summary
  • Introduction
  • Interactive Scatter Plots
  • Other Interactive Plots in altair
  • Summary
  • 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
  • Introduction
  • Choropleth Maps
  • Plots on Geographical Maps
  • Summary
  • Introduction
  • Data Formatting and Interpretation
  • Data Visualization
  • Cheat Sheet for the Visualization Process
  • Summary
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