Data Analysis Tutorials

Discover how to make your Power BI reports more insightful, informative, and interactive with this advanced analytical features tutorial.

Learn basic visualizations of various data structures using Bokeh.

Data cleaning is a very basic building block of data science. Learn the importance of data cleaning and how to use Python and carry out the process.

Use Python Pandas and select columns from DataFrames. Follow our tutorial with code examples and learn different ways to select your data today!

In this Python tutorial, explore movie data of popular streaming platforms and build a recommendation system.

Learn how to sort vectors, data frames, and more in R using order(), sort(), and dplyr's arrange() with practical examples.

Learn how to effectively use list comprehension in Python to create lists, to replace (nested) for loops and the map(), filter() and reduce() functions, ...!

Wondering whether you should use Python or R for data analysis? You’ve come to the right place.

Discover how to write reusable and efficient Python functions. Master parameters, return statements, and advanced topics like lambda functions. Organize your code better with main() and other best practices.

In this tutorial, you'll learn about and how to code in Python the probability distributions commonly referenced in machine learning literature.

Learn about logistic regression, its basic properties, and build a machine learning model on a real-world application in Python using scikit-learn.

A NumPy tutorial for beginners in which you'll learn how to create a NumPy array, use broadcasting, access values, manipulate arrays, and much more.