The author describes building a personal, open-source computational engine using Python libraries SymPy, NumPy, pandas, SciPy, statsmodels, Pingouin, Matplotlib, and Seaborn, effectively replicating the functionality of Wolfram Mathematica at no cost.
This article demonstrates how to use Pandas plotting capabilities for common data visualization tasks, suggesting that Pandas can be sufficient for routine EDA without relying on libraries like Matplotlib.
There’s a reason you’re confused
