NumPy stands for Numerical Python, it provides all the functions you need to prepare and transform your data before using a machine learning algorithm. It can be compared to Python lists, but it offers more efficient storage and functionality for data operations. If you are new to data science, you should learn NumPy as your first Python library after completing the basics of Python. If you want to know some of the most important functions of NumPy for data science, this article is for you. In this article, I will introduce you to all the important NumPy functions that you need for data science.
Important NumPy Functions for Data Science
In introducing you to the important functions of NumPy for data science, I don’t mean that only these are the functions that you need for data science. All of the NumPy functions mentioned below are the functions that you need to practice a lot because you will need to use them in almost every data science task. So, here are all the important functions of NumPy for data science that you need to know:
- min and max: used to find the minimum and maximum value of a NumPy array
- mean: used to find the mean value of the NumPy array
- std: used to find the standard deviation of the NumPy array
- median: used to find the median of a NumPy array
- percentile: used to find the percentile in a NumPy array
- linspace: used to get evenly spaced numbers over a specified interval
- shape: used to get the shape of an array
- reshape: used to reshape an array
- copyto: copies the values of one array to another array
- transpose: used to reverse the axes of an array
- stack: used to join the sequence of an array along a new axis
- vstack: used to join the sequence of an array along a new axis vertically
- hstack: used to join the sequence of an array along a new axis horizontally
- sort: used to get a sorted array
These were the important functions of NumPy that you should know for data science. If you want to learn all the functions of NumPy then you can follow the official documentation of NumPy.
Summary
So these were all the necessary NumPy operations that you need to learn for data science, no matter what aspect of data science you are interested in. By introducing you to these functions, I didn’t mean to say that these are the only functions that you need to learn for data science. These are the NumPy operations that you will need to use most of the time, so you should know how to use them perfectly. I hope you liked this article on important NumPy functions for Data Science. Please feel free to ask your valuable questions in the comments section below.
