Learn to intrinsically create NumPy variable using NumPy methods 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 st
- [Narrator] I'll open the intrinsic creation…using NumPy methods from your exercise files.…This will create a new tab in your browser.…We'll import NumPy and change the namespace name.…NumPy has built in intrinsic functions…that are useful for creating arrays.…One of these functions is the arange function.…If I execute this cell by pressing Shift + Enter,…I'll generate an error message.…
In particular, we're told that arange is not defined.…However, I know that arange is a NumPy function.…The reason is,…we're using NumPy as n-p.…Arange, as used here,…is trying to execute an arange function…in the Python namespace.…To make this work in the NumPy namespace,…I can precede the function name with "np.".…The arange function creates an array…with a range of integers.…
This range of integers starts with zero,…and goes up until but not including…the number in the parameter.…Documentation about the NumPy function…is available on the NumPy webpage.…In particular,…you can find information about arange at this URL.…The first line of the documentation…
- 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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