Data Science Tutorials
Develop your data science skills with tutorials in our blog. We cover everything from intricate data visualizations in Tableau to version control features in Git.
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Box Plot in R Tutorial
Learn about box plots in R, including what they are, when you should use them, how to implement them, and how they differ from histograms.
DataCamp Team
25 settembre 2020
Pandas Add Column Tutorial
You are never stuck with just the data you are given. Instead, you can add new columns to a DataFrame.
DataCamp Team
18 settembre 2020
Python String Search and Replace: in, .find(), .index(), .count(), and .replace()
Practical patterns for finding, counting, and replacing substrings in modern Python.
DataCamp Team
31 marzo 2026
Python Select Columns Tutorial
Use Python Pandas and select columns from DataFrames. Follow our tutorial with code examples and learn different ways to select your data today!
DataCamp Team
25 novembre 2024
Building a Chatbot using Chatterbot in Python
In this tutorial, you'll learn how to build a chatbot using chatterbot in Python.
Avinash Navlani
10 gennaio 2024
Recommendation System for Streaming Platforms Tutorial
In this Python tutorial, explore movie data of popular streaming platforms and build a recommendation system.
Avinash Navlani
30 agosto 2020
How to Sort Data in R: A Complete Tutorial
Learn how to sort vectors, data frames, and more in R using order(), sort(), and dplyr's arrange() with practical examples.
Olivia Smith
6 febbraio 2026
Installation of PySpark (All operating systems)
This tutorial will demonstrate the installation of PySpark and hot to manage the environment variables in Windows, Linux, and Mac Operating System.
Olivia Smith
29 agosto 2020
How to Drop Columns in Pandas Tutorial
Learn how to drop columns in a pandas DataFrame.
DataCamp Team
18 agosto 2020
Python lambda Tutorial
Learn a quicker way of writing functions on the fly with lambda functions.
DataCamp Team
18 agosto 2020
Random Number Generator Using Numpy Tutorial
Numpy's random module, a suite of functions based on pseudorandom number generation. Random means something that can not be predicted logically.
DataCamp Team
18 agosto 2020
Python datetime: How to Work with Dates and Times in Python
Learn the different ways to work with Python’s datetime tools and simplify everything from parsing strings to managing timezone-aware timestamps.
Oluseye Jeremiah
8 dicembre 2025