Learn how to use NumPy, Python, and Jupyter Notebook for numerical, scientific, and statistical programming as you build your analytics, machine learning, and data science skills.
- [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.
- 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
2. Create NumPy Arrays
3. Index, Slice, and Iterate
4. Plots: Matplotlib and Pyplot
5. Manipulate Arrays
6. Short Examples
7. Extended Examples
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