
This course is for absolute beginners
Explore how to plot two graphs with lines and markers, and customize line colors and marker properties—shape, size, edge color, and fill color—using the plotting library.
Explore histogram as a frequency distribution to visualize how often values occur, generate 150 random numbers around a mean of 50 with standard deviation 5, plot them, and examine density.
Explore box plots to visualize quartiles, medians, and outliers using seeded random data, and learn how figure size and multiple plots convey distribution.
Welcome to this Data Visualization course for all. This course will teach you hands-on practice on generating visualizations in python and also intuitively use. matplotlib is the python library used in this lesson. This is a very useful library for creating interesting visualizations. The code syntax is straight forward and there is clear documentation on each and every method so that when you get stuck, you can quickly get support for your problem.
Matplotlib has interesting features that can help programmers generate nice visualizations.
Some examples are Bar charts, Line charts, Pie charts, scatter charts, 3D charts, and interesting interactive data visualizations.,
This basic course in data visualization can help you build your foundation in data visualization while you advance yourself through consistent practices and the use of various datasets.
matplotlib library is a very useful tool for marketers, business analysts, and data analysts to help people generate reports on their data
After taking this course, you should be able to create your own simple visuals that can help you gain insights from various data sources.
To summarize the power of matplotlib, matplot lib is powerful for visualizing and analyzing various datasets especially when you read about the documentation provide.