Learn to join or split arrays NumPy arrays in this video tutorial by Charles Kelly. These are explained in the context of computer science and data science to technologists and students in preparation for machine learning, applied statistics, neural netwo
- [Narrator] The Joining and Splitting Arrays file,…in your exercise file folders,…is pre-populated with an import statement.…Before you use this notebook, go to the Cell menu,…and click Run All.…You can create a new cell,…by going to This Cell, and simply pressing Shift Enter.…In this video, I'll explain NumPys, Concatenate,…Stat, and Split functions.…We'll begin by creating two sample arrays, A and B,…that we will then concatenate.…
This is the value for A, and this is the value for B.…Let's create a new array and call it "together."…And we'll assign it the value np.concatenate,…and the parameters, or arguments, will be,…first, a tuple, which contains the arrays that we want…to concatenate together.…The second parameter is the axis along which…we want the concatenation to take place.…
If we display the value for "together,"…we see that arrays one, two, three, four,…and five, six,…are now concatenated as 1-2-3-4-5-6.…Let's display "together's" shape attribute.…As we see, it's a three by two array,…not surprising since it has three rows and two columns.…
- 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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