Advanced Matplotlib Plots & Customization | Applied Python #11
Raj Institute of Coding and Robotics (RICR)
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Advanced Matplotlib Plots & Customization | Applied Python #11
95 просмотров · 8 дн. назад
Raj Institute of Coding and Robotics (RICR)
460 подписчиков
95 просмотров · 8 дн. назад
In this video, we continue our Matplotlib series and explore different types of plots along with their customization options.
You will learn how to create and customize Histogram, Bar Plot, Box Plot, and Multiple Subplots, along with controlling axes, labels, colors, transparency, and layouts.
What We Will Learn Today:
Creating & customizing Histogram Plots
Understanding Bins and data distribution
Figure size, titles & labels
Colors, transparency (alpha) & grid
X-axis & Y-axis limits
Vertical & Horizontal Bar Plots
Bar width, colors & edge colors
Adding text to plots using plt.text()
Creating Box Plots
Displaying mean & outliers
Creating multiple Box Plots
Customizing X-axis ticks
Creating multiple plots using plt.subplots()
Working with different axes
Using plt.tight_layout() for better spacing
Displaying plots using plt.show()
Video Chapters / Timestamps:
00:00 - Introduction to Advanced Matplotlib Plots
00:35 - Creating Histogram Plots
02:29 - Figure Size, Titles & Labels
04:09 - Colors, Alpha & Grid Customization
06:16 - X & Y Axis Limits
07:12 - Histogram Orientation & Width
09:08 - Creating Bar Plots
11:17 - Bar Plot Customization
13:10 - Horizontal Bar Plots
13:43 - Adding Text to Plots
17:11 - Creating Box Plots
17:52 - Mean & Outlier Display
18:28 - Multiple Box Plots
20:44 - Creating Multiple Subplots
22:37 - Adding Different Plots to Subplots
25:07 - Tight Layout & Final Recap
Who Is This Video For?
Python Beginners
Data Science Students
Data Analysts
Machine Learning Beginners
Anyone learning Data Visualization with Python
Next Video
In the next video, we will use these Matplotlib concepts on a real dataset to create graphs and perform data analysis.
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