text: We can re-run the example and plot the target variables for the first three chunks with complete data.
  Running the example creates a figure with 39 plots and three time series per plot, one for the targets for each chunk.
  The plot is busy, and you may want to increase the size of the plot window to better see the comparison across the chunks for the target variables.
  For many of the variables that have a cyclic daily structure, we can see the structure repeated across the chunks.
  Further, plots 3-to-10 correspond to variable 11 across seven different sites. The string similarity in temporal structure across these plots suggest that modeling the data per variable which is used across sites may be beneficial.
  We can start by taking a look at the distribution of each target variable for one chuck by creating box and whisker plots for each target variable.
  We can see that many of the variables have a median close to zero or one; we can also see a large asymmetrical spread for most variables, suggesting the variables likely have a skew with outliers.
  It is encouraging that the boxplots from 4-10 for variable 11 across seven sites show a similar distribution. This is further supporting evidence that data may be grouped by variable and used to fit a model that could be used across sites.
  We can see that outlier values do extend into the range 5-to-10 units. This suggests there might be some use in standardizing and/or rescaling the targets when modeling.
  Perhaps the most useful finding is that there are some targets that do not have any (or very much) data regardless of chunk. These columns probably should be excluded from the dataset.
  We can see that there are in fact no columns with zero non-NaN data, but perhaps two dozen (12) that have above 90% missing data.