# Boxplot using absolute frequencies

I have a dataframe in the following form:

|Regions | F1 | F2 | F3 | ... | Fn |
|Region_1| X11| X12| X13| ... | X1n|
|Region_2| X21| X22| X23| ... | X2n|
...
|Region_k| Xk1| Xk2| Xk3| ... | Xkn|


Where every row represents an Italian region and every column is a feature that the individuals living in that region have. The value $X_{ij}$ is the number of individuals living in the region i and having the feature j, so the sum of each row gives the popolation living in that region; the sum of each column gives the people having that feature.

Boxplot depicts groups of numerical data through their quartiles. It is correct to create a boxplot on the columns of my data? It gives the correct information or I have to apply some transformation on my data (e.g., scaling, normalization, etc)?

• Every Xij is an absolute frequency. – darioSka Nov 26 '16 at 11:45
• Do you want to summarise each column or do you want to compare the distributions? – mdewey Nov 27 '16 at 13:44
• I want to summarise each column – darioSka Nov 27 '16 at 14:50