5 Useful Numpy Functions

In this notebook, let has have a look at some most interesting things which can be done using numpy.

So we all know that Numpy can be used for handling numerical values, Numpy is a very intuitive library which provides us huge facilities to handle the data, not only it supports us in mathematical calculations but also provides us facilities to handle strings! Today let us have a look at 5 Useful functions in numpy which you need to know!

numpy.datetime_as_string() Date time Support function
numpy.apply_along_axis() This function applies any function to specified axis
numpy.apply_over_axes() This function applies any function repeatedly to all specified axes
numpy.extract() To apply certain condition on numpy array values and retrieving them
numpy.random.random_sample() Gives a sample of random numbers

The recommended way to run this notebook is to click the "Run" button at the top of this page, and select "Run on Binder". This will run the notebook on mybinder.org, a free online service for running Jupyter notebooks.

!pip install jovian --upgrade -q

import jovian

jovian.commit(project='numpy-array-operations')

[jovian] Attempting to save notebook..
[jovian] Updating notebook "abutahirism/numpy-array-operations" on https://jovian.ai
[jovian] Uploading notebook..
[jovian] Uploading additional files...
[jovian] Committed successfully! https://jovian.ai/abutahirism/numpy-array-operations

'https://jovian.ai/abutahirism/numpy-array-operations'

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