Advanced Visualizations & Dashboards: Visualization Using Python

Data Visualization    |    Intermediate
  • 12 videos | 37m 8s
  • Includes Assessment
  • Earns a Badge
Rating 3.9 of 40 users Rating 3.9 of 40 users (40)
In this course, learners explore approaches to building and implementing visualizations for data science, as well as plotting and graphing using Python libraries such as Matplotlib, ggplot, bokeh, and Pygal. Key concepts covered here include the importance and relevance of data visualization from the business perspective; libraries that can be used in Python to implement data visualization and how to set up a data visualization environment using Python tools and libraries; and prominent data visualization libraries that can be used with Matplotlib. Then see how to create bar charts by using ggplot in Python; how to create charts, using the bokeh and Pygal libraries in Python; and criteria that should be considered when selecting an appropriate data visualization library. Learners observe how to create interactive graphs and image files; how to plot graphs using line and markers; and how to plot multiple lines in a single graph with different line styles and markers. Finally, see how to create a line chart with Pygal, create an HTML directive to render the line chart, and render the line chart.

WHAT YOU WILL LEARN

  • Recognize the importance and relevance of data visualization from the business perspective
    List libraries that can be used in python to implement data visualization
    Set up a data visualization environment using python tools and libraries
    List the prominent data visualization libraries that can be used with matplotlib
    Create bar charts using ggplot in python
    Create charts using the bokeh and pygal libraries in python
  • Recognize criteria that should be considered when selecting an appropriate data visualization library
    Create interactive graphs and image files
    Plot graphs using line and markers
    Plot multiple lines in a single graph using different line styles and markers
    Create a line chart with pygal, create an html directive to render the line chart, and render the line chart

IN THIS COURSE

  • 1m 43s
  • 3m 42s
    Upon completion of this video, you will be able to recognize the importance and relevance of data visualization from a business perspective. FREE ACCESS
  • Locked
    3.  Libraries for Data Visualization in Python
    3m 13s
    Upon completion of this video, you will be able to list libraries that can be used in Python to implement data visualization. FREE ACCESS
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    4.  Python Data Visualization Environment Configuration
    3m 57s
    In this video, you will learn how to set up a data visualization environment using Python tools and libraries. FREE ACCESS
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    5.  Matplotlib Libraries for Visualization
    3m 22s
    Upon completion of this video, you will be able to list the prominent data visualization libraries that can be used with Matplotlib. FREE ACCESS
  • Locked
    6.  Bar Chart Using ggplot
    2m 16s
    In this video, you will learn how to create bar charts using ggplot in Python. FREE ACCESS
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    7.  Bokeh and Pygal
    4m 33s
    Find out how to create charts using the Bokeh and Pygal libraries in Python. FREE ACCESS
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    8.  Select Visualization Libraries
    3m 34s
    Upon completion of this video, you will be able to recognize criteria that should be considered when selecting an appropriate data visualization library. FREE ACCESS
  • Locked
    9.  Interactive Graphs and Image Files
    2m 24s
    During this video, you will learn how to create interactive graphs and image files. FREE ACCESS
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    10.  Plot Graphs
    3m 18s
    In this video, you will plot graphs using lines and markers. FREE ACCESS
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    11.  Multiple Lines in Graphs
    2m 32s
    In this video, you will learn how to plot multiple lines in a single graph using different line styles and markers. FREE ACCESS
  • Locked
    12.  Exercise: Create Line Charts with Pygal
    2m 34s
    During this video, you will learn how to create a line chart with Pygal, create an HTML directive to render the line chart, and render the line chart. FREE ACCESS

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