- Level Intermediate
- Duration 3 hours
- Course by Duke University
-
Offered by
About
Visualizing data is used by virtually every discipline these days. It is used for analyzing web traffic to determine peak server load, growth and death rate of populations for biological analysis, analyzing weather patterns over time, stock market trends, and so on. Simply put, Data Visualization brings meaning to numbers that help people understand it. Seeing the data change can draw attention to trends and spikes that may otherwise go unnoticed. Python is an open-source (free) programming language has libraries that can be used to read and make useful graphics to present the data. In this course, you will create an application that reads data from CSV files. You will learn how to visualize the data using various techniques using existing Python libraries. Note: This course works best for learners who are based in the North America region. We're currently working on providing the same experience in other regions.Modules
Getting Started with Data Visualization
1
Discussions
- Meet and Greet (optional)
1
Videos
- Getting Started with Data Visualization
3
Readings
- Course Structure
- Meet your Instructor: Matt Harrison
- Common Plots Refresher
Excel and Clean Charts
6
Videos
- Introduction to Excel for Visualization
- Creating a Line Plot in Excel
- Creating a Histogram in Excel
- Creating a Scatterplot in Excel
- Creating a Bar Plot in Excel
- Minimizing Clutter in Visualizations
2
Readings
- Getting Ready: Accessing Microsoft Excel
- Plotting Exercise: Excel
Google Sheets and Color
6
Videos
- Introduction to Sheets for Visualization
- Creating a Line Graph in Sheets
- Creating a Histogram in Sheets
- Creating a Scatterplot in Sheets
- Creating Bar Plot in Sheets
- Optimizing Color for Visualizations
2
Readings
- Getting Ready: Accessing Google Sheets
- Plotting Exercise: Google Sheets
Data Visualization Fundamentals with Excel and Sheets Wrap Up
1
Assignment
- Data Visualization Fundamentals with Excel and Sheets
1
Discussions
- Plotting Exercise Discussion
Plotting with Pandas and Chaining
9
Videos
- Exploring Basic Plots
- Cleaning your Data
- Creating a Line Plot with Pandas
- Creating a Bar Plot with Pandas
- Creating a Scatterplot with Pandas
- Creating More Complicated Plots with Pandas
- Creating a Heatmap with Pandas
- Creating a Slope Graph with Pandas
- Chaining Methods with Pandas
3
Readings
- Getting Ready: Accessing Python and Pandas
- Pandas Resample, Groupby, and Rolling (optional)
- Plotting Exercise: Pandas
Plotting with Seaborn
6
Videos
- Introduction to the Seaborn Library
- Creating a Line Plot with Seaborn
- Creating a Bar Plot with Seaborn
- Creating a Scatterplot with Seaborn
- Creating a Heatmap with Seaborn
- Creating a Slope Graph with Seaborn
2
Readings
- Getting Ready: Installing Seaborn
- Plotting Exercise: Seaborn
Customizing Matplotlib
4
Videos
- Introduction to Matplotlib in Python
- Customizing Text with Matplotlib
- Customizing Color with Matplotlib
- Customizing Axes with Matplotlib
2
Readings
- Getting Ready: Installing Matplotlib Libraries
- Plotting Exercise: MatPlotLib
Data Visualization with Pandas, Seaborn and Matplotlib Wrap Up
1
Assignment
- Data Visualization with Pandas, Seaborn and Matplotlib
1
Discussions
- Plotting Exercise Discussion
Plotting with Plotly
6
Videos
- Introduction to Plotly
- Creating a Line Plot with Plotly
- Creating a Bar Plot with Plotly
- Creating a Scatterplot with Plotly
- Creating a Heatmap with Plotly
- Creating a Slope Graph with Plotly
2
Readings
- Getting Ready: Accessing Plotly
- Plotting Exercise: Plotly
Dash
4
Videos
- Introduction to Dash
- Creating a Line Plot with Dash
- Creating a Bar Plot with Dash
- Creating a Scatterplot with Dash
2
Readings
- Getting Ready: Accessing Dash
- Plotting Exercise: Dash
Streamlit
5
Videos
- Introduction to Streamlit
- Creating a Line Plot with Streamlit
- Creating a Bar Plot with Streamlit
- Connecting a Widget to a Plot in Streamlit
- Creating a Scatterplot with Streamlit
2
Readings
- Getting Ready: Accessing Streamlit
- Plotting Exercise: Streamlit
Plotly, Dash and Streamlit Wrap Up
1
Assignment
- Data Visualization with Plotly, Dash and Streamlit
1
Discussions
- Plotting Exercise Discussion
Tableau
7
Videos
- Introduction to Tableau
- Creating a Line Plot with Tableau
- Creating a Histogram with Tableau
- Creating a Scatterplot with Tableau
- Creating a Bar Plot with Tableau
- Creating a Plot Dashboard in Tableau
- Tableau Summary
2
Readings
- Getting Ready: Accessing Tableau
- Plotting Exercise: Tableau
QuickSight
7
Videos
- Introduction to QuickSight
- Creating a New Dataset in QuickSight
- Creating a Line Plot with QuickSight
- Creating a Histogram with QuickSight
- Creating a Scatterplot with QuickSight
- Creating a Bar Plot with QuickSight
- Sharing your Plots with QuickSight
2
Readings
- Getting Ready: Accessing Amazon QuickSight
- Plotting Exercise: QuickSight
Tableau and Amazon Quicksight Wrap Up
1
Assignment
- Visualization with Cloud-Based Tools: Tableau and Amazon Quicksight
1
Discussions
- Plotting Exercise Discussion
1
Readings
- Next Steps
Auto Summary
Enhance your data storytelling skills with the "Data Visualization with Python" course offered by Coursera. Ideal for data analysts, business professionals, and aspiring data storytellers, this intermediate-level program focuses on creating impactful visualizations using Python, spreadsheets, and BI tools. Over 180 hours, you'll engage in practical exercises with a consistent dataset, ensuring a hands-on learning experience. Prior Python programming experience and familiarity with Pandas are recommended. The course is available for free, making it accessible to those eager to master the art of visual communication in the data-driven world.

Matt Harrison

Noah Gift

Kennedy Behrman