Now that I know how to colour things in, this may be a good time to step back and see if I can improve on my data presentation. More importantly, if I can learn from the data and be able to present it in an understanable way. To do this, I’m using the Air Quality England data containing NO, NO2, NOXasNO2, and PM10. And I have already created extra columns for hour, day, and month. It looks like this:

The data looks fine, until we look a little further. Suddenly, I’m seeing some strange readings. Anything lower than 1 is a minus, and there are more different values than I was expecting. But I will go ahead and plot the NO readings and see what happens.

sort(plot(table(aqe2020$NO)))
[1] -0.98670 -0.87820 -0.83186 -0.79117 -0.77309 -0.72562 -0.70075 -0.69510 -0.69171 -0.68033 -0.63068 -0.53755 -0.53335 -0.52895 -0.52217
[16] -0.50815 -0.50395 -0.47035 -0.45775 -0.44306 -0.44095…