Everything you need to know about Pandas to start increasing your productivity with code examples — Table of Contents Why use Pandas? Getting started Installing and importing Pandas Pandas DataFrame Reading files and creating a DataFrame Examining the DataFrame Manipulating data with Pandas DataFrame Index Rows and Columns Selecting data with loc and iloc Handling missing values Detecting missing values Removing missing values Filling missing values

Basic concepts such as Union, Intersection, and Conditional Probabilities, as well as Visualization with Venn Diagrams and Probability Trees — Table of Contents What is Probability How to calculate and display probabilities Visualizing probabilities with a Venn Diagram Intersection and Union Conditional Probabilities Visualizing probabilities with a Probability Tree Conclusion Today, we’ll talk about probability. …

Measuring Data Variability with a few codes in Python — Table of contents Variance Standard Deviation Conclusion In this article, we’ll take a closer look at how we can measure data variability. In the following sessions, you’ll learn the basics of Standard Deviation and Variance. …

With concepts of Range, Quartiles, and how to build Box Plots with Python — Table of contents Range Quartiles - How to identify the quartiles - Interquartile Range Box Plots - Anatomy of a Box Plot - Building a box plot with Python Conclusion In the first article of this series, we examined the most common measures of central tendency, the mean, median, and mode, as well…

Understanding the three most common measures of central tendency — When people need to get the “average” of something, we usually add up all the numbers/items and divide by how many numbers/items there are. …

Step by step guide on how to structure your first Data Science projects on Kaggle — If you are starting your journey in data science and machine learning, you may have heard of Kaggle, the world’s largest data science community. With the myriad of courses, books, and tutorials addressing the subject online, it’s perfectly normal to feel overwhelmed with no clue where to start. Although there…

Predicting the risk of client default using XGBoost, LightGBM and CatBoost — Note from Towards Data Science’s editors: While we allow independent authors to publish articles in accordance with our rules and guidelines, we do not endorse each author’s contribution. You should not rely on an author’s works without seeking professional advice. See our Reader Terms for details. Credit risk is associated…

How to parse and extract data from HTML documents in simple steps — One of the main concerns we have when starting a new project is how to obtain the data we’ll be working on. Companies like Airbnb and Twitter, for instance, simplify this task by providing APIs so we can compile information in an organized way. On other occasions, we can download…