Author
Charles Kelly
Released
10/7/2016- Using Jupyter Notebook
- Creating NumPy arrays from Python structures
- Slicing arrays
- Using Boolean masking and broadcasting techniques
- Plotting in Jupyter notebooks
- Joining and splitting arrays
- Rearranging array elements
- Creating universal functions
- Finding patterns
- Building magic squares and magic cubes with NumPy and Python
Skill Level Intermediate
Duration
Views
- [Charles] My name's Charles Kelly. NumPy is a library that provides the foundations of mathematical, scientific, engineering and data science programming within the Python Echo system. I'll use interactive notebooks to explain the details of the NumPy library. Together we'll explore NumPy statements and NumPy snippets. Before we finish the course, I'll present a group of NumPy brainteasers to you. We'll complete the course with an extended example that uses NumPy and Python to generate magic queues.
I enjoy working with NumPy, and I want to convey my knowledge and enthusiasm to you. Let's get started.
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Introduction
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Welcome40s
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Install software1m 55s
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1. Notebooks
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Notebook basics8m 23s
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Markdown4m 33s
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Launch Jupyter Notebook2m 7s
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2. Create NumPy Arrays
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3. Index, Slice, and Iterate
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Slice arrays7m 35s
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Broadcasting11m 42s
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Structured and record arrays10m 59s
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4. Plots: Matplotlib and Pyplot
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Inline plotting2m 46s
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Figures and subplots5m 27s
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Multiple lines, single plot6m 16s
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Plot annotations5m 16s
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Beautiful plots, the gallery4m 22s
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5. Manipulate Arrays
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Views and copies8m 19s
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Array attributes1m 40s
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Add and remove elements8m 53s
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Join and split arrays6m 49s
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Array shape manipulation4m 24s
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Rearrange array elements5m 12s
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Transpose like operations4m 24s
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Tiling arrays3m 24s
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6. Short Examples
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Universal functions4m 47s
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Pythagorean triangles3m 28s
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Linear algebra8m 12s
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Finding patterns7m 48s
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Statistics8m 30s
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Brain teasers12m 2s
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7. Extended Examples
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Magic squares and NumPy6m 57s
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Adjacency matrix6m 19s
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Magic characteristics5m 41s
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Build magic cubes3m 48s
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Conclusion
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Next steps49s
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Video: Welcome