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https://github.com/reagentx/numpy_practice

Solutions to the lessons on Machine Learning Plus's 101 Numpy Exercises blog post
https://github.com/reagentx/numpy_practice

arrays data-manipulation data-science machine-learning

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Solutions to the lessons on Machine Learning Plus's 101 Numpy Exercises blog post

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# 101 NumPy Exercises for Data Analysis

These lessons are from the [Machine Learning Plus](https://www.machinelearningplus.com/101-numpy-exercises-python/) blog. The filenames in the `scripts` directory are the lesson numbers.

## Running these files

After setting up a [virtual environment](https://docs.python.org/3/library/venv.html) with `python3 -m venv /path/to/new/virtual/environment`, clone this repository and install [NumPy](http://www.numpy.org), [Pandas](https://pandas.pydata.org), and [Scikit](http://scikit-learn.org/stable/index.html) using `pip`. After that, each lesson should run without any modification. Make sure you activate the virtual environment before running any code.

## Notes

- All lessons are answered and commented. Some lessons include Pandas and Scikit examples as well.
- As of this writing, there were only 70 lessons of the 101 mentioned in the blog post's title.
- Lesson 49 seems especially silly, if a better solution exists please open an issue or pull request.
- Lesson 53 uses a very different solution than that given in the blog post.
- Lesson 58 uses a very different solution than that given in the blog post.
- Lesson 60 requires installation of `requests` and `image`, easily done through `pip`.
- Lesson 63 uses a very different solution than that given in the blog post.
- Lesson 67 uses a very different solution than that given in the blog post.
- Lesson 69 uses a very different solution than that given in the blog post.