Building on the first chart , let’s add a few things to the chart that everyone expects to see in a chart like this, like the unit for the y-axis and a proper x-axis title.
Because the sensor only provides data every 15 minutes the first chart looks a bit rough. The NutriSense app on the phone makes the chart look a lot nicer, so let’s do the same here. Pandas provides a way to first add missing values (basically empty rows) to the dataset. Once that is done, those missing values can be interpolated. Pandas provides a number of different methods, I simply picked the default one, a cubic interpolation. This is what the new image looks like:
And for reference the is the old one (first chart):