Data Science Cheat Sheets

Welcome to our cheat sheet for working with text data in R! This resource is designed for R users who need a quick reference guide for common tasks related to cleaning, processing, and analyzing text data.

Welcome to our cheat sheet for working with text data in Python! We've compiled a list of the most useful functions and packages for cleaning, processing, and analyzing text data in Python, along with clear examples and explanations, so you'll have everything you need to start developing!

Welcome to our cheat sheet for working with dates and times in R! This resource provides a list of common functions and packages for manipulating, analyzing, and visualizing data with dates and times.

In this cheat sheet, you'll have a guide around the top supervised machine learning algorithms, their advantages and disadvantages, and use-cases.

In this cheat sheet, you'll have a guide around the top unsupervised machine learning algorithms, their advantages and disadvantages and use cases.

Python is the most popular programming language in data science. Use this cheat sheet to jumpstart your Python learning journey.

Plotly is one of the most widely used data visualization packages in Python. Learn more about it in this cheat sheet.

Learn all the fundamentals of Julia in this comprehensive cheat sheet.

Working with dates and times is essential when manipulating data in Python. Learn the basics of working with datetime data in this cheat sheet.

ggplot2 is considered to be one of the most robust data visualization packages in any programming language. Use this cheat sheet to guide your ggplot2 learning journey.

With this SQL Window Functions cheat sheet, you'll have a handy reference guide to the various types of window functions in SQL.

Regular expressions (regex or regexp) are a pattern of characters that describe an amount of text. Regular expressions are one of the most widely used tools in natural language processing and allow you to supercharge common text data manipulation tasks.