MATPLOTLIB in one video | Python # 10

Matplotlib is a popular data visualization library for creating static, animated, and interactive visualizations in Python. It is a comprehensive library that provides a variety of plotting tools for creating high-quality graphs, plots, and charts.

Matplotlib is widely used in the scientific community and is often used for visualizing data from scientific experiments, simulations, and data analysis. It provides a wide range of visualizations, including line plots, scatter plots, bar charts, histograms, and 3D plots.

Matplotlib is a flexible library that can be customized to fit specific needs. It allows users to adjust the size, color, and style of plots, add titles and labels, and create subplots. Additionally, it has support for mathematical symbols, making it easy to annotate plots with equations and formulas.

Matplotlib is open-source and is distributed under a BSD-style license, meaning it can be used freely and without restrictions in both commercial and non-commercial applications. It is a foundational tool in the Python data science ecosystem, and many other libraries, such as Pandas and Seaborn, build on top of it to provide more specialized functionality.

00:00:00 Introduction
00:00:58 What is MATPLOTLIB ?
00:01:56 Installing MATPLOTLIB
00:02:22 Pyplot
00:04:35 Plot Formatting
00:06:05 Multiple Plotting
00:08:43 Legend
00:11:43 Keyword String Plotting
00:16:34 Categorical Data Plotting
00:17:24 Bar Plot
00:17:52 Scatter Plot
00:18:38 Subplotting
00:20:27 Figure Size Adjustment
00:21:27 Control Line Properties
00:22:43 Multiple Figures & Axes
00:25:43 Text Manipulation
00:28:38 Gridding
00:28:56 Plot Limit
00:30:16 Text Annotation
00:35:38 Logarithmic & Nonlinear Scales
00:37:49 Log Scale
00:38:38 Symmetric Log scale
00:39:25 Logistic Scale
00:40:05 imread & imshow
00:42:10 Image Cropping
00:44:03 Barcodes
00:48:23 Layer Images
00:51:42 Alpha Blending
00:53:35 Fill Curves
00:53:59 Koch Snowflake
01:00:59 Rendering Equations with LaTeX
01:05:48 Polar Curves
01:09:59 Summary

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Credits :

Things to know about MATLPLOTLIB:
• Matplotlib was created by John D. Hunter in 2003 as part of his research work. It was originally designed to create publication-quality scientific plots in Python, and over time it has evolved into a comprehensive library for data visualization.

• Matplotlib is built on top of NumPy, which is a popular numerical computing library in Python. NumPy provides the data structures and functions that Matplotlib uses to create its plots.

• Matplotlib provides a wide range of plots, including line plots, scatter plots, bar plots, histograms, 3D plots, and more. These can be created with just a few lines of code, making it easy to get started with data visualization.

• Matplotlib is highly customizable. It provides a variety of options for adjusting the appearance of plots, such as changing colors, line styles, markers, and fonts. It also provides tools for creating subplots, adding titles and labels, and adjusting the axis limits and ticks.

• Matplotlib can create interactive visualizations using its pyplot interface or its object-oriented interface. These allow users to explore their data and interact with their plots in a variety of ways.

• Matplotlib has a large and active community of users and developers. It is open-source and distributed under a permissive license, which makes it easy for developers to contribute to its development and for users to incorporate it into their own projects.

• Matplotlib is widely used in the scientific community, but it is also used in many other fields, such as finance, business, and engineering. It is a foundational tool in the Python data science ecosystem and is often used in conjunction with other libraries, such as Pandas, Seaborn, and scikit-learn.

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FTC disclaimer: This video was sponsored by DataCamp
#PythonProgramming #Python #Matplotlib

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