If null values are sampled in one time step (e.g. nodata classes or masked areas), the resulting dataframe column will be cast to float before the nans can be dropped. When value_counts is run, you'll get a dataframe with a float index. Slicing that dataframe with an int index will throw a KeyError.
Explicitly casting to int after dropping nans avoids the float index problem and solves the issue.
Fix #22
If null values are sampled in one time step (e.g. nodata classes or masked areas), the resulting dataframe column will be cast to float before the nans can be dropped. When
value_countsis run, you'll get a dataframe with a float index. Slicing that dataframe with an int index will throw a KeyError.Explicitly casting to int after dropping nans avoids the float index problem and solves the issue.