A compilation of some must-know statistical concepts — If you are working with data, often you might have come across terms like “tests”, “scores”, “values”, etc. preceded by alphabets like ‘F’, ‘P’, ‘R’, ‘T’, ‘Z’, etc. This article is about a layman-explanation of a few of such statistical terms/concepts, often encountered in the world of Data Science. Disclaimer: What this article is not about?

An Overview of the Most Important Features in Version 0.24 — Scikit-learn, Python’s machine-learning library, just got better. It’s the best time to update it. Recently, in December 2020, scikit-learn released a major update in version 0.24. It is the last stable release of version 0. The next release will supposedly be version 1.0 and is currently in development. I will…

Basic must-know SQL for aspiring Data Scientists or Analysts — Every now and then, I see a new Medium article saying “7 must-have skills”, “10 important skills”, “top 3 skills”, etc. for a data scientist. All such posts acknowledge SQL as a must-know skillset for data scientists. Coming from a computational physics background, SQL was foreign to me until I…

One of the most important data structures in Python — In this article, I will talk about dictionaries. This is the second article in the series named “Data Structures in Python”. The first part of this series was about lists. Dictionaries are important data structures in Python that use keys for indexing. They are an unordered sequence of items (key-value…

Get proficient with lists — Python’s most versatile data structure — This article is about lists. They are the most versatile and resourceful, in-built data structure in Python. They can simultaneously hold heterogeneous data i.e., integers, floats, strings, NaN, Booleans, functions, etc. within the same list. They are an ordered sequence of items that means the order of the elements is…

An interesting feature of NumPy to filter unwanted data — All men are sculptors, constantly chipping away the unwanted parts of their lives, trying to create their idea of a masterpiece … Eddie Murphy If you ever wonder how to filter or handle unwanted, missing, or invalid data in your data science projects or, in general, Python programming, then you…

Learn six unique ways to visualize your big data — Often while working with data, no matter big or small, sometimes you want to compare things side-by-side or plot different attributes or features individually. In such cases, a single figure is rendered insufficient. Thus, you need to know the art of working with subplots. This article will focus on the…

Upgrade your Matplotlib today to the latest release 3.3 — A few days ago, Matplotlib released version 3.3 — the latest in the third generation of its family. It introduced some really exciting features and I would strongly recommend you to upgrade your Matplotlib today. This post will guide you through them using some examples. I updated to the latest…

A preview of a few new features of Python 3.10 — We are currently living in the stable age of Python 3.8 and the latest stable version of Python, 3.8.4, was released last week. Python 3.9 is already in the beta phase of its development and a beta version (3.9.0b4) was pre-released on July 3, 2020, with the fifth beta pre-release…