Step 1 - First Impressions

Before diving into data exploration, let's take a peek into one of the files... It's always good to have an idea of the data we'll be working with!

Notes

Nice. The data files have "txt" extensions, but contain structured, tabular data. In other words - CSV! So we can use the Pandas library, which will make our lives easier.


Step 2 - Loading the Data

Now we load the contents of the other files into the same structure, and differentiate the data source (file) with the user number.

Notes

We have a reasonably large dataset: 137824 readings for our 4 users.


Step 3 - Plotting Movement

Since this data describes user movements let's see what it looks like to project one into a surface - it's good to have a feeling about our users'movement patterns. We could have used a map, but these coordinates were transformed for privacy reasons so the map would just be noise.