I have data for 131,653 users about how often they do a task, and how much time they take when doing the task. I simply arrange the number of times they do the task in ascending order of the time they take, and make a scatter plot. This is what I get:
I don't understand what to make of this pattern. I have not seen anything like this before. Can anyone help me understand what might be going on?
I can zoom into the graph to show the plot for users 10,000 to 20,000:
And also, this is the zoomed in plot for uers 130,000 to the end:
EDIT: The dataset looks something like this:
User Time Number of ID (sec) occurrences 1 110 342 2 172 332 3 193 357 4 196 492 5 206 287 6 246 338 7 270 296 8 357 440
The time taken has been sorted in ascending order, as shown in the dataset, and the users have been marked with IDs according to the time. And then, I do the scatter plot of column 3, which is giving this bizarre pattern.
EDIT 2: Let me explain a bit about the context of the data. The task is opening of notifications and the time is the response delay (i.e., how long after receiving the notifications does the user open it). So, the response time ranges from 0 to 168 hours (i.e., 1 week, which is the duration for which the data was collected - and some notifications were never opened). So, I just took the raw data, sorted the records in increasing order of the response time, and plotted the number of times each user opened a notification. Hope the context is clearer now.
EDIT 3: Here is the graph of the number of occurrences vs the response time (note that the x-axis is in log scale, as in the linear scale all the points were cluttered near the origin):