Simple and clear explanations of different statistical concepts — Introduction My professor once mentioned that if you can explain a term to someone who is completely unfamiliar with it and have them get the concept, then you are regarded to be knowledgeable about the subject. This method is also the approach I've taken whenever I've learned something new. …

Introduction Exploratory Data Analysis — EDA is an indispensable step in data mining. To interpret various aspects of a data set like its distribution, principal or interference, it is necessary to visualize our data in different graphs or images. Fortunately, Python offers a lot of libraries to make visualization more convenient…

An efficient and effective way of exploring complex datasets — Introduction Have you ever thought that engaging with the data frame directly may make studying it much easier and simpler? By turning complex data tables into editable and understandable presentations, complex data tables can be efficiently comprehended. In this article, I’ll explore and share with you some of the simple yet…

A collection of compelling data analysis scenarios that I find essential — Why Think SQL Series? When creating SQL queries, I realized that there have been some recurring patterns in problem-solving. This inspired me to initiate a series where I systematically outline my approach to diverse SQL analysis scenarios and share it with the community. The posts will be brief and straightforward, making them easy to…

Try Taipy with the simple augmented mark-down syntax to streamline your coding process to build interactive visualizations in Python — The story continues… After 2 previous parts introducing the Taipy package with: Part 1: Introducing a general idea of how Taipy GUI works and showing how different basic charts are created. Part 2: Applying more visual control elements In this article, I will show you how to utilize what we know about Taipy…

Improve & optimize your data analytical process with different techniques for data shaping — Why is Data Shaping? There is no one-size-fits-all data. For different purposes and used cases, data is customized accordingly. The more you are aware of the intended use of data afterward, the more equipped you will be to correctly present your data to the end users. For example, the data utilized to undertake in-depth…

Next part of Data Profiling — After defining the potential errors of data that require correction for precise analysis, data cleaning is the next step — Data Cleaning is Indispensable When you first receive a data set to explore, the first thing that we would always want to check is if this data is ready for analysis. Often, the answer is no. …

Simple explanations of different statistics concepts — Introduction In Part 1: Simple Explanations of Basic Statistics Concepts, I explained the fundamental ideas behind some statistical concepts, including different definitions relating to population and sample, sampling methods, and confidence interval. Today, I will provide you with additional explanations of several frequently encountered statistical topics. …

Explore the power of SQL profiling and learn how it can help you optimize your data — Data Profiling: What and Why? Different from data mining, which is a process of searching for insights underlying the data patterns, data profiling is a method of examining the data quality to identify potential problems with the data, such as inconsistencies, errors, or missing values, and to ensure that the data is accurate, complete, and…