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Missing values are common and occur either due to human error, instrument error, processing from another team, or otherwise just a lack of data for a certain observation. In this Byte, we'll take a look at how to fill NaNs in a DataFrame, if you choose to handle NaNs by...

David Landup

In this guide - we'll take a look at how to calculate the Euclidean distance between two points in Python, using Numpy. Euclidean distance is a fundamental distance metric pertaining to systems in Euclidean space. Euclidean space is the classical geometrical space you get familiar with in Math class, typically...

Bilal Hamada

Numpy is the most popular mathematical computing Python library. It offers a great number of mathematical tools including but not limited to multi-dimensional arrays and matrices, mathematical functions, number generators, and a lot more. One of the fundamental tools in NumPy is the ndarray - an N-dimensional array. Today, we're...

This guide is an in-depth introduction to an unsupervised dimensionality reduction technique called Random Projections. A Random Projection can be used to reduce the complexity and size of data, making the data easier to process and visualize. It is also a preprocessing technique for input preparation to a classifier or...

Mehreen Saeed

In this guide, we'll be taking a look at an unsupervised learning model, known as a Self-Organizing Map (SOM), as well as its implementation in Python. We'll be using an RGB Color example to train the SOM and demonstrate its performance and typical usage. Self-Organizing Maps: A General Introduction A...

This guide is an introduction to Spearman's rank correlation coefficient, its mathematical calculation, and its computation via Python's pandas library. We'll construct various examples to gain a basic understanding of this coefficient and demonstrate how to visualize the correlation matrix via heatmaps. What Is the Spearman Rank Correlation Coefficient? Spearman...

There are many data visualization libraries in Python, yet Matplotlib is the most popular library out of all of them. Matplotlib’s popularity is due to its reliability and utility - it's able to create both simple and complex plots with little code. You can also customize the plots in...

The term slicing in programming usually refers to obtaining a substring, sub-tuple, or sublist from a string, tuple, or list respectively. Python offers an array of straightforward ways to slice not only these three but any iterable. An iterable is, as the name suggests, any object that can be iterated...

Kristina Popovic

A list is the most flexible data structure in Python. Whereas, a 2D list which is commonly known as a list of lists, is a list object where every item is a list itself - for example: [[1,2,3], [4,5,6], [7,8,9]]. Flattening a list of...

Raksha Shenoy

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