Summary
In this chapter, you learned about ESDA and how to begin taking it a step further than traditional EDA by creating spatial data visualizations. As an example, you started to work with the New York City Airbnb data by first diving deep into the data to understand some of the issues it has related to missingness, skewness, and ill-formatted data types. After cleaning the dataset up, you learned about three visualizations: point maps, heatmaps, and choropleth maps.
After reviewing the results of the heatmap and the final choropleth map, you began to notice some patterns in the data as it relates to its geographic distribution. You noticed that the highest number of Airbnbs are located in Manhattan and Brooklyn. You also noticed that there was a pattern where certain census tracts were grouped together with higher prices. You’ll explore these patterns further in the next chapter.
