Percentage bar graph

[Lisa Salvetti]

Hi everybody,
I would like to have a bar graph of the percentage of frequencies of several variables (serra estinz camcli smarif amrum iaria inqsu inqfiu disdr catastr fores2 inqelet2 paesag2 esriso2 altamb2), across 3 different regions (coded in the variable ripmf as 1, 2, 3)

I manage to get the graph with frequencies which comes from the following code:

graph bar (count) serra estinz camcli smarif amrum iaria inqsu inqfiu disdr catastr fores2 inqelet2 paesag2 esriso2 altamb2, over (ripmf)

I tried the following code, but i get a weird output, that shows for each region (ripmf 1, 2, 3) the same value.

graph bar (percent) serra estinz camcli smarif amrum iaria inqsu inqfiu disdr catastr fores2 inqelet2 paesag2 esriso2 altamb2, over (ripmf)

how would you solve this?

The graph i want would be like this one:

[Tiago Pereira]

Hi, Lisa.
Can you share your data? Or give us an example? You can use -dataex-

ssc install dataex
help dataex

[Lisa Salvetti]

* Example generated by -dataex-. For more info, type help dataex
clear
input byte(serra estinz camcli smarif amrum iaria inqsu inqfiu disdr catastr fores2 inqelet2 paesag2 esriso2 altamb2 ripmf)
1 . . 4 . 6 7 . . . . . 13 . . 1
. 2 . . . . . 8 . 10 . 12 . . . 1
. . . 4 5 . . . . . 11 . . . . 1
. . 3 4 . . . . . . 11 . . . . 1
. . . . . . . . 9 . . . . . . 1
. . . . . . 7 . . . . . . . . 1
. . 3 4 . 6 . . . . 11 . . . . 1
. . 3 4 . 6 7 . . . 11 . . . . 1
. . . . . . . . . . 11 . . . . 1
. 2 3 . 5 . . . . . 11 . 13 . . 1
. . . 4 . . . 8 . . 11 12 13 . . 1
. . 3 . 5 6 7 8 . . . . . . . 1
. . 3 . 5 6 7 8 . . . . . . . 1
. . 3 4 5 6 7 . . . . . . . . 1
. 2 . . . 6 7 8 . . 11 . . . . 1
1 2 . 4 . . . . . . . . . . . 1
. . 3 4 . 6 7 8 . . . . . . . 1
1 . 3 . 5 6 7 . . . . . . . . 1
1 2 3 . . 6 7 . . . . . . . . 1
1 2 . 4 . . 7 8 . . . . . . . 1
1 . 3 . . 6 7 8 . . . . . . . 1
1 . 3 4 . 6 . 8 . . . . . . . 1
1 2 3 . . 6 . 8 . . . . . . . 1
. 2 3 . . . . 8 9 10 . . . . . 1
1 . 3 4 . 6 . 8 . . . . . . . 1
. 2 . . . . 7 8 . 10 11 . . . . 1
. 2 . . . . . 8 . 10 11 . . . . 1
1 . . . 5 . 7 . . . 11 . 13 . . 3
1 2 3 . . . . . 9 . . 12 . . . 3
. . 3 . . 6 . . 9 . 11 . . 14 . 3
. . . . . . . 8 . . . . . . . 3
. . . . . 6 7 8 . . . . . . . 3
. . . . . . . 8 . . . . . . . 3
. . . . . 6 7 8 . . . . . . . 3
. . 3 . . 6 7 8 . . 11 . . . . 3
. . 3 . . 6 7 8 . . 11 . . . . 3
. . 3 . . 6 7 . . 10 . . 13 . . 3
. . 3 . . 6 7 . . 10 . . 13 . . 3
. . 3 . . 6 7 8 . . 11 . . . . 3
. . 3 . . 6 7 8 . . . . . 14 . 3
1 . . . 5 6 7 . . 10 . . . . . 3
1 . . . . 6 . 8 9 10 . . . . . 3
1 . . 4 . 6 7 . . 10 . . . . . 3
1 . 3 4 . 6 . . . 10 . . . . . 3
1 2 3 4 . 6 . . . . . . . . . 3
1 2 3 4 . 6 . . . . . . . . . 3
1 . . . . 6 . . . . . . . . . 3
. . 3 . . 6 7 8 . . 11 . . . . 3
. . . 4 . 6 . 8 . . . 12 . 14 . 3
. . 3 4 . 6 . 8 . . . 12 . . . 3
. . 3 4 . 6 . 8 . 10 . . . . . 3
1 . 3 4 . 6 . . . . . . . 14 . 3
1 . 3 4 . 6 . . . . . . . 14 . 3
. . 3 . . 6 . 8 . . 11 . . 14 . 3
1 . 3 . . . . 8 . 10 11 . . . . 3
. . 3 4 . 6 . 8 . . . . . 14 . 3
. 2 3 . . 6 7 8 . . . . . . . 3
. . 3 . . 6 7 8 . . 11 . . . . 3
1 . 3 . . 6 7 8 . . . . . . . 3
. . 3 . 5 . . . 9 10 11 . . . . 3
. . 3 . . . 7 8 . . . . 13 14 . 3
1 2 3 4 5 . . . . . . . . . . 3
. 2 3 . 5 6 . . . . . 12 . . . 3
. . 3 4 . 6 7 8 . . . . . . . 3
1 . 3 . . 6 . 8 . . 11 . . . . 3
. . 3 . . . . . . . . . . . . 3
. 2 3 4 . 6 7 . . . . . . . . 3
. 2 3 4 . 6 7 . . . . . . . . 3
. 2 3 4 . . 7 8 . . . . . . . 3
. . . . . 6 . . . . . . . 14 . 3
1 . 3 4 . 6 7 . . . . . . . . 3
. . 3 4 . 6 . . . . . 12 13 . . 1
. . 3 . . . 7 8 . 10 . . 13 . . 1
. . . 4 . . 7 8 . 10 . . 13 . . 1
. . 3 4 . . 7 . . . 11 . . . . 1
. . . 4 . . 7 8 . . 11 . . . . 1
. . 3 4 . . . . . . . . . . . 1
. . 3 4 . . . . . . 11 . . . . 1
. 2 3 4 . . 7 8 . . . . . . . 1
1 . 3 . . . . . . . 11 . . . . 1
. . . 4 . . 7 . . . 11 . 13 . . 1
1 . 3 . . 6 . 8 . . 11 . . . . 1
1 . 3 . . 6 . 8 . . 11 . . . . 1
1 . . 4 . 6 . . . 10 . . 13 . . 1
. 2 3 . . . . . 9 . 11 . . 14 . 1
. . . 4 . . . 8 9 . . . 13 14 . 1
. . 3 4 . . . . . . . . 13 . . 1
1 2 3 . . . . . . . 11 12 . . . 1
. 2 . 4 . 6 . 8 9 . . . . . . 1
. 2 . . . 6 7 8 . . 11 . . . . 1
. . 3 . . 6 7 8 . . 11 . . . . 1
. . . . . . . . . . . . 13 . . 1
1 2 3 4 5 . . . . . . . . . . 1
. . 3 4 . . . . . . . . . . . 1
1 . 3 4 . . . 8 9 . . . . . . 1
. . . 4 . . 7 . 9 10 11 . . . . 1
. . 3 4 . . . . . . . . 13 . . 1
. . 3 4 . . . . . . . . 13 . . 1
. . 3 4 . . 7 . . . 11 . . . . 1
. . 3 4 . . 7 . . 10 . . . . . 1
end
label values ripmf label_ripmf
label def label_ripmf 1 "North", modify
label def label_ripmf 3 "South", modify
[/CODE]

So basically I have 15 variables that represent 15 environmental issues. People in the survey choose by crossing those that worry them the most. I want to visualize how these concerns spread across 3 italian regions: north, center and south, in percentage values.

[Sergiy Radyakin]

clear all
version 16.0

sysuse nlsw88
keep if inrange(occupation,1,5)

generate byte w=1
collapse (mean) wage (sum) w, by(race occu)

frame copy default t
drop w
frame change t
collapse (mean) wage [aw=w], by(occu)
forval i=1/`=_N' {
frame post default (9) (occu[`i']) (wage[`i'])
}
frame change default
label define racelbl 9 "All", modify

graph bar wage, ///
over(race, label(angle(vertical)) ) ///
over(occu, label(angle(vertical)) gap(300pct)) ///
asyvar ///
bar(1, color(ltblue)) ///
bar(2, color(ebblue)) ///
bar(3, color(gray)) ///
blabel(bar , format(%6.2f) size(vsmall)) ///
legend(pos(12) ring(0) bmargin(large) rows(1)) ///
ytitle("Wage, USD") ///
scale(0.5) xsize(16) ysize(9)

[Lisa Salvetti]

my problem is just about percentages, and i would like to avoid generating15x3 new variables in order to do a graph

[Sergiy Radyakin]

certainly.

graph bar (percent) serra estinz camcli smarif amrum iaria inqsu inqfiu disdr catastr fores2 inqelet2 paesag2 esriso2 altamb2, over (ripmf) blabel(bar, format(%6.2f)) scale(0.5)  legend(cols(4)) ytitle(percent)