Xinyue Gui and Wen Zhan
Exploratory Data Analysis (EDA) is vital in many data science related projects. Identifying trends and patterns in datasets is an initial and crucial step before building machine learning models, since it helps us better understand the data. In this blog (https://github.com/W3n2han/plots_python_seborn_matplotlib/blob/main/Understand%20Data%20with%20Plots.pdf), you will find some of the most frequently used graphs and plots, with summary of their use-cases and example codes (language used in Python). The goal of this blog is to help you quickly identify which plot could best satisfy your needs, helping you save time in the EDA procedure.
You can also see the pdf and code in ‘resources/plots_python_seaborn_matplotlib’.