In this post, we will learn how to generate random integers using Random Generators in Numpy Python. Random Generator class in Numpy offers wide variety of random distributions including integers. To get started let us import Numpy To generate random numbers, we need a construcor of random number class Generator. In Numpy, default_rng() is the […]
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Computing Correlation with Numpy corrcoef()
In this post, we will learn how to use Numpy’s corrcoef() function to compute correlation between two datasets stored in a list or arrays. Numpy’s corrcoef function calculates pearson correlation coefficient, which is a measure of how two variables are related. The resulting correlation coefficient can range from 1 to -1. A correlation coefficient of […]
Numpy arange() function with examples
In this post, we will learn how to use arange(), one of the most useful functions in Numpy. With Numpy arange function we can create evenly spaced arrays. For example, If you need to create an array of numbers within a given range, you can use the arange function. To get started let us load […]
Numpy isclose() function with examples
This post covers numpy.isclose(), the standard function for comparing floating-point values in Python. Why not use ==? Floating-Point Inaccuracy: Computers cannot represent most decimal fractions exactly in binary, leading to small precision errors. A direct comparison with == will often fail when numbers are mathematically equal but have tiny representational differences. The Solution: numpy.isclose() circumvents […]
Difference between Pandas where() function and mask() function
Pandas mask() and where() functions are two related functions that are useful in Pandas to find if elements of Pandas dataframe satisfy a condition. They both preserve the shape of the dataframe. In this post, we will first see simple examples of using Pandas where() and mask() functions and then we will learn the key […]