The current box plot we use in the model.plot_benefit_distribution method is showing the average net benefit per household per sq km. This is not accurate as it does not show well the distribution of the data per household (as some cells will have a large number of households and others very few). To be able to show the weighted distribution per household, a box plot is not useful as for this amount of data (millions of data points) it will be unfeasible to plot as the number of outliers will be very large. We should remove the box plot option (at least for now) and add an option for histograms divided into facets. We can also consider later on adding an option for violin plots, which do not plot outliers as points; however, as a kernel density function needs to be calculated in that case, it can be also unfeasible due to computer power.
The current box plot we use in the
model.plot_benefit_distributionmethod is showing the average net benefit per household per sq km. This is not accurate as it does not show well the distribution of the data per household (as some cells will have a large number of households and others very few). To be able to show the weighted distribution per household, a box plot is not useful as for this amount of data (millions of data points) it will be unfeasible to plot as the number of outliers will be very large. We should remove the box plot option (at least for now) and add an option for histograms divided into facets. We can also consider later on adding an option for violin plots, which do not plot outliers as points; however, as a kernel density function needs to be calculated in that case, it can be also unfeasible due to computer power.