In this tutorial, we’ll use Python’s Pandas and Numpy library to replace many Excel functions you probably used in the past.
Use Pandas and Numpy to ditch Excel forever.
As someone who has been working with Excel for many years, I know that the idea of learning things you can already do in Excel/VBA in a completely new environment like Python doesn’t sound so exciting. However, all the benefits that the Python environment offers make this worth it. For this reason, I came up with a useful and simple guide I wish I had when I switched from Excel to Python.
In this article, we’ll use Python’s Pandas and Numpy library to replace many Excel functions you probably used in the past.
Table of Contents
1. The Dataset
2. Sum, Average, Max, Min, Count
Columns (e.g. sum a column)
Rows (e.g. sum a row)
Replace IF with np.where
Replace nested IF with np.select
4. SumIf, CountIf, AverageIf
One condition (select a column with square brackets [ ] )
Two or more conditions (select columns and use & or |)
5. Basic Data Cleaning
Change the case of text with .str.lower, .str.upper or .str.title
Extract text in a column with .str.extract
Identify whether a cell is empty with the .isnull method
Find an element with .loc[ ]
Merge two tables with pd.merge or pd.concat
7. Pivot Table
Use the .pivot_table method
8. Replace Excel Graphs with Python’s Matplotlib or Seaborn
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