Data Science Tutorials

Learn all about R's matrix, naming rows and columns, accessing elements also with computation like addition, subtraction, multiplication, and division.

Learn what variable scopes are all about and get familiar with the 'LEGB' rule. You will also deal with scenarios where you'll get to see the global and nonlocal keywords in action.

Learn what is Python IDLE (Integrated Development and Learning Environment) is, how you can install it, and leverage its various features for writing your Python programs.

Learn about type checking, different types of the type system in various languages along with duck typing, and type hinting.

Learn about data reshaping in R, different functions like rbind(), cbind(), along with Melt(), Dcast(), and finally about the transpose function.

Learn the basic concepts of threading and how you can use it with the help of Python.

Learn how to create data visualizations in Python using Altair and a Movies Dataset.

Learn about web scraping with python and how to scrape Amazon, with the help of the Beautiful Soup library.

Kevin Systrom published a really interesting article on estimating $R_t$, the measure known as effective reproduction number. We will use the same approach outlined by Kevin in his article to estimate COVID-19's Rt in real-time.

Learn about Python Docstrings. Find different examples & format types of docstrings for Sphinx, Numpy and Pydoc.

Learn about Arrays in R, including indexing with examples, along with the creation and addition of matrices and the apply() function.

Learn about R's Strings: its rules, concatenation, along with essential properties of the string, extracting and replacing a character string, and formatting a string.