English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 2h 53m | 4.86 GB
Understand, explore, and effectively present data using the powerful data visualization techniques of Python.
You’ll begin with an introduction to data visualization and its importance. Then, you’ll learn about statistics by computing mean, median, and variance for some numbers, and observing the difference in their values. You’ll also learn about key NumPy and Pandas techniques, such as indexing, slicing, iterating, filtering, and grouping. You’ll study different types of visualizations, compare them, and find out how to select a particular type of visualization using this comparison. You’ll explore different plots, including custom creations. After you get a hang of the various visualization libraries, you’ll learn to work with Matplotlib and Seaborn to simplify the process of creating visualizations. You’ll also be introduced to advanced visualization techniques, such as geoplots and interactive plots. You’ll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful and insightful visualizations. You’ll study how to plot geospatial data on a map using Choropleth plot, and study the basics of Bokeh, extending plots by adding widgets and animating the display of information.
Learn
- Understand and use various plot types with Python
- Explore and work with different plotting libraries
- Understand and create effective visualizations
- Improve your Python data wrangling skills
- Work with industry-standard tools like Matplotlib, Seaborn, and Bokeh
- Understand different data formats and representations
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