What you would learn in Pandas Playbook: Visualization course?
If you work on a data set and you, need to make the data set's features visible visually. This is a fundamental capability for any researcher or engineer. In this course, Pandas Playbook Visualization, You'll be taught how to make a wide array of beautiful graphs using Pandas, one of the more sought-after analytical libraries for data in Python. In the beginning, you'll be taught the basics of plotting using pandas and learn the best way to prep your data to plot and also how to make basic plots, such as a line or line plot. In the next step, you'll learn about matplotlib and matplotlib, that Python library that creates the graphs and interacts with Pandas, and how to utilize it properly. In the next step, you'll go deeper into the various ways to modify your plots. This includes color styles, line styles, and themes, as well as customizing legends and axes, creating interactive plots, and more. Then, you'll see an overview of two different visualization tools which can be utilized in conjunction with Pandas: Seaborn, which is focused explicitly on statistical plotting, and Bokeh which can produce interactive images for the web. After this course, you'll have a thorough understanding of how you can utilize Pandas to display your data. You'll be able to write compelling and transparent code that can create beautiful plots using the guidelines. This course will make you more proficient at exploring data and sharing the results with others.
Course Content:
Course Overview
Course Introduction
Making Simple Plots
Navigating the API Jungle: Matplotlib, Pandas, and the Jupyter Notebook
Creating Advanced Plots with Pandas
Visualizing Statistical Properties with Seaborn
Creating Interactive Plots for the Web with Bokeh
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