14 Excel-like Functions in Python, Pandas, and Jupyter Notebook
A comprehensive list of tutorials in Python, Pandas, and Jupyter Notebook, explaining how to use 14 of your favorite Excel-like functions
--
Hello Excel super-user. My name is David, and I work on a Data Science team. I’d like to introduce you to a very popular analysis stack in the great wide world of Data Science: Python, Pandas, and Jupyter notebook.
This blog will guide you through setting up your computer to use this new analysis stack, and then walk through the Pandas/Python-equivalent of your favorite Excel functions, all executed in a Jupyter notebook.
As a former spreadsheet-jockey, I can tell you that getting started with this new data analysis stack is easy, and the GREAT NEWS FOR YOU is that it’s even easier if you’re familiar with Excel.
Let us begin.
Hello, Excel super-user
If you’ve been using Excel for a while, you’re well aware of the most common operations like IF statements, VLOOKUPS, Pivot Tables and others listed below.
- SUM, COUNT, AVERAGE
- MAX & MIN
- IF STATEMENTS
- VLOOKUP
- CONCATENATE
- PROPER, UPPER, LOWER
- CLEAN & TRIM
- SPLIT TEXT TO COLUMNS
- PIVOT TABLE
- FILTER & SORT
Did you know that you can easily write all of this with a simple stack of Python, Pandas and Jupyter notebook, while also learning an in-demand skill in the world of Machine Learning and Data Science?
Not only can you easily write Python and Pandas to do all of your Excel notebook work, you can also automate your Excel analysis processes — saving yourself hours of time — and expand your analysis abilities.
You’ll be able to do everything you can already know how to do in Excel, plus new skills like:
