I'm trying to explore a large dataset, both with data frames and with charts. I'd like to analyze the distribution of each variable by different metrics (e.g., sum(x), sum(x*y)) and for different sub-populations. I have 4 sub-populations, 2 metrics, and many variables.
In order to accomplish that, I've made a list structure such as this:
$variable1
...$metric1 <--- that's a df.
...$metric2
$variable2
...$metric1
...$metric2
Inside one of the data_frames (e.g., list$variable1$metric1), I've calculated distributions of the unique values for variable1 and for each of the four population groups (represented in columns). It looks like this:
$variable1$metric1
unique_values med_all med_some_not_all med_at_least_some med_none
1 (1) 12-17 Years Old NA NA NA NA
2 (2) 18-25 Years Old 0.278 0.317 0.278 0.317
3 (3) 26-34 Years Old 0.225 0.228 0.225 0.228
4 (4) 35 or Older 0.497 0.456 0.497 0.456
$variable1$metric2
unique_values med_all med_some_not_all med_at_least_some med_none
1 (1) 12-17 Years Old NA NA NA NA
2 (2) 18-25 Years Old 0.544 0.406 0.544 0.406
3 (3) 26-34 Years Old 0.197 0.310 0.197 0.310
4 (4) 35 or Older 0.259 0.284 0.259 0.284
What I'm trying to figure out is a good way to loop through the list of lists (probably melting the DFs in the process) and then output a ton of bar charts. In this case, the natural plot format would be, for each dataframe, a stacked bar chart with one stacked bar for each sub-population, grouping by the variable's unique values.
But I'm not familiar with iterated plotting and so I've hit a dead end. How might I plot from that list structure? Alternately, is there a better structure in which i should be storing this information?