Pandas makes it easy to quickly load, manipulate, align, merge, and even visualize data tables directly in Python.

Python users can use the Pandas library to read data from various file formats (CSV, Excel, SQL databases), perform data cleaning (removing duplicates, converting data types, and handling ...

Yet that can often be the case for data scientists — particularly those working with large data sets and using the popular Pandas library for the Python programming language.

Python’s Pandas library allows for advanced data manipulation, statistical analysis, and exploration directly within Excel, streamlining workflows.