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Explained with examples, writes Soner Yıldırım, Junior Data Scientist at Invent Analytics.
Photo: Alexander Sinn on Unsplash
NumPy is the most widely-used scientific computing library for Python. It serves as a basis for many other libraries such as Pandas.
NumPy makes it very simple and fast to operate on large arrays of numbers. Since we are likely to have lots of data, having a super efficient tools like NumPy is of great importance.
In this article, we will go over 5 operations that are essential in the analysis of large arrays. These operations provide some statistics and characteristics of arrays...
We have covered only a part of the NumPy operations on arrays. However, these are the operations that you are likely to use in a typical data analysis and manipulation process.
NumPy proved to be a very flexible and efficient scientific computing library. It serves as a base for many Python libraries such as Pandas. Thus, it is a fundamental tool to learn for aspiring data scientists.
Source: Medium
