Chapter 1 Context & Objectives

1.1 Context

Uber released for some cities the datasets of their drivers movement. Those include the OSM way identifier, the mean and standard speed deviation. In order to anonymize them, the data have been aggregated per hour. Let’s have a look at the Berlin data for the month of June 2019, and how they are distributed in space and time. For this, we will combine those data with the OpenStreetMap shapefile for Berlin.

1.2 Objectives

Through this book, we will use some concepts of data analysis :

  • handle data formatted as table with the help of the data.table package,
  • create some vizualisations with the ggplot2,
  • create an animated map with sf and an interactive one with leaflet.

1.3 References

  • for data.table, i found the R Quick Tutorial an excellent introduction.
  • for ggplot2, i refer to this
  • for modeling and data analysis, i kindly refer to The Analytic Edge course, maybe not as fancy as datacamp programs, but free and with a very progressive and accessible learning curve. I personally get into R thanks to this course, the Coursera Stats in R and the Exploratory_Data_Analysis interacive console-based course from Swirl.