Skip to main content

Data Visualization Using Tableau and Python

Development Academy of the Philippines

Course Overview

Data visualization is important in data science and analytics since it is the way of communicating data and letting the audience understand its implications. Hence, it is imperative to utilize the available and appropriate tools in data analytics and visualization. This course demonstrates how to use Python and Tableau in making data visualization. It discusses the tools' algorithms and technicalities relevant to presenting and visualizing data, making it easier for participants to navigate and provide more effective visualization and storytelling.

What You Will Learn

Upon completion of this course, the learners are expected to:

  • apply data visualization libraries in Python, namely Matplotlib, Seaborn, Folium, and Bokeh for presenting data; and
  • utilize Tableau for data storytelling and connect Tableau with Python, and generate visualizations that would be used in analytics


You will need a computer or laptop with the folowing tools:

Course Instructor

Course Staff Image #1

Ruben Canlas Jr.

Subject Matter Expert

Course Content

Week 1: Install Tableau and Create Basic Charts

7 Videos | 3 Activities

3 Videos

  • Welcome to the course!
  • How to Install Tableau?
  • The Start Page UI
  • Creating your First Visualization
  • Measures and Dimensions
  • Other Visualizations in Tableau
  • Visually Exploring the Data

3 Activities

  • Recall Activities
  • Exit Assessment: Understanding Tableau

Week 2: Exploring Data with Dimensions

4 Videos | 3 Activities

4 Videos

  • Exploring Data using Visual Formatting
  • Exploring the Data using Dimensions
  • Enriching our Visual Analytics using the Profit Dimension (2 videos)

3 Activities

  • Recall Activities
  • Exit Assessment: Exploring Data with Dimensions

Week 3: Exploring the Spatial Dimension with Maps

5 Videos | 2 Activities

5 Videos

  • Exploring Location
  • Maps
  • Using Bar Charts to Find Negative Profit
  • Creating a Calculated Field
  • Finding Outliers and Doing Visual - What If Analysis

2 Activities

  • Recall Activity
  • Exit Assessment: Spatial Dimension with Maps

Week 4: Dashboards, Stories, and Sharing Views

3 Videos | 3 Activities

3 Videos

  • Steps in Creating Dashboards in Tableau
  • Creating Stories in Tableau
  • Ways to Share your Visualizations using Tableau

3 Activities

  • Recall Activities
  • Exit Assessment: Dashboards, Stories, and Sharing Views/li>

Week 5: Making a Philippine Map

5 Videos | 3 Activities

5 Videos

  • Creating a Philippine Map in Tableau
  • Doing Some Data Preparation
  • Ways in formatting the Map in Tableau
  • Adding Population Data to the PH Map
  • Exploring Population Data Through the Map

3 Activities

  • Recall Activities
  • Exit Assessment: Data Visualization Using Tableau

Week 6: Introduction to Jupyter Notebook and Python

9 Videos | 2 Activities

9 Videos

  • Overview
  • Steps in Installing Jupyter through Anaconda
  • The UI and Basic Commands
  • Jupyter and Markdown
  • Saving, Closing, and Shutting Down
  • Keyboard Shortcuts
  • Code Cells
  • Examining the Code Line by Line
  • Summary

2 Activities

  • Recall Activity
  • Exit Assessment: Jupyter Notebook and Python

Week 7: Doing More with Jupyter Visuals

13 Videos | 3 Activities

13 Videos

  • Basic Exploratory Data Analysis in Jupyter
  • Visual EDA: Box Plots
  • Understanding the Violin Shapes
  • Visual EDA: Violin Plots (2 videos)
  • Exploring Dimensions – Category Plots (2 videos)
  • Exploring More Visuals (2 videos)
  • Interactivity and Sharing (3 videos)
  • Key takeaways

3 Activities

  • Recall Activities
  • Exit Assessment: Jupyter Visuals
  • Final Exam
  1. Course Number

  2. Classes Start

  3. Classes End

  4. Estimated Effort

    1-2 hours/week (14 hours)
  5. Price