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  1. Run and modify this Jupyter notebook to illustrate their usage (some explanation and 3 examples for each function). Use your imagination to come up with interesting and unique examples.
  2. Upload this notebook to your Jovian profile using jovian.commit and make a submission here: https://jovian.ml/learn/data-analysis-with-python-zero-to-pandas/assignment/assignment-2-numpy-array-operations
  3. (Optional) Share your notebook online (on Twitter, LinkedIn, Facebook) and on the community forum thread: https://jovian.ml/forum/t/assignment-2-numpy-array-operations-share-your-work/10575 .
  4. (Optional) Check out the notebooks shared by other participants and give feedback & appreciation.

Math is Life!

I wanted to highlight some of the important math functions that would be valuable for data analysis on a regular basis.

Since NumPy shines for being used with numerical data of the same type, I decided to choose the following functions:

  • exp - Calculate the exponential of all elements in the input array.
  • absolute - Calculate the absolute value element-wise.
  • sqrt - Return the non-negative square-root of an array, element-wise.
  • nan_to_num - Replace NaN with zero and infinity with large finite numbers (default behaviour) or with the numbers defined by the user using the nan, posinf and/or neginf keywords.
  • round - Round an array to the given number of decimals.
!pip install jovian --upgrade -q
import jovian
jovian.commit(project='numpy-array-operations')
[jovian] Attempting to save notebook..

Let's begin by importing Numpy and listing out the functions covered in this notebook.