How to plot timeseries with many NaNs?

Question

Originally I had a dataframe containing power consumption of some devices like this:

and I wanted to plot power consumption vs time for different devices, one plot per one of 6 possible dates. After grouping by date I got plots like this one (for each group = date):

Then I tried to create similar plot, but switch date and device roles so that it is grouped by device and colored by date. In order to do it I prepared this dataframe:

It is similar to the previous one, but has many NaN values due to differing measurement times. I thought it won't be a problem, but then after grouping by device, subplots look like this one (ex is just a name of sub-dataframe extracted from loop going through groups = devices):

This is the ex dataframe (mean lag between observations is around 20 seconds)

Question: What should I do to make plot grouped by device look like ones grouped by date? (I'd like to use ex dataframe but handle NaNs somehow.)

Answer 1

I found solution in answer to similar question: ex.interpolate(method='linear').plot(). This line will fill gaps between data points via interpolation between plotting. This is the result:

Another thing that can help is adding .plot(marker='o', ms = 3) which won't fill gaps between points, but at least will make points visible (previously some points, mainly the peaks in energy consumption were too small in scale of whole plot). This is the result: