Let the data speak for themselves.
This is a well-known quote to many data scientists in the field. However, it is often not trivial to capture the hidden characteristics or features in big data, and some exploratory data analysis must be done before we fully understand the dataset.
In this chapter, we aim to perform some exploratory data analysis on two datasets, using the techniques that we have discussed in previous chapters. Here is a brief outline of this chapter:
- Visualizing categorical data
- Visualizing geographical data
- GeoPandas library
- Working with images using the PIL library
- Importing/transforming images
- Multiple subplots
- Heatmap
- Survival graph
We assume that the readers are now comfortable with the use of pandas DataFrame as it will be heavily used in this chapter.
Readers should also be noted that most exploratory data analyses actually involve a significant amount of statistics, including dimension reduction approaches such as PCA...