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Introduction

with Terezija Semenski

Learn the skills you need to create your NumPy analytical modules successfully and build professional analytical applications.



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Introduction

52s
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What you should know

57s
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Why should you use Matplotlib?

2m 28s
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Matplotlib basics

5m 8s
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Understanding figures

4m 33s
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Matplotlib subplots functionality

2m 53s
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Understanding legends

3m
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Challenge: Implementing a figure

1m 8s
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Solution: Implementing a figure

2m 12s
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Colors and styles

4m 32s
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Advanced Matplotlib commands

5m 25s
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Adding annotations

3m 1s
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Creating pie charts and bar charts

3m 23s
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Advanced plots

3m 14s
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Universal functions

2m 58s
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Introducing strides

3m 23s
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Structured arrays

2m 14s
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Dates and time in NumPy

3m 29s
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Linear algebra capabilities in NumPy

5m 8s
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Decomposition

4m 32s
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Polynomial mathematics

3m 54s
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Application: Linear regression

3m 27s
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Next steps

55s