Showing multiple graphs together when have many groups

[Anjali Kajan]

Hi
I have created a histogram of marriage ages for each ethnic group in my dataset using the by option, however there are around 100 ethnicities so each individual graph is showing up very small and hard to read. Is there a code I can use to make this look better by forming 2/3 graphs instead. Here is the code I have used

twoway hist agefrstmar , percent by(ethnicityall, note("") legend(off) ixaxes)

Thank you!

[Jared Greathouse]

Not with 100 different categories no there's not.

Maybe I'm wrong, but before we continue, I guess my question for you is "what's the value of this graph/ these graphs", "what's its purpose, what's it for", right? Are 100 histograms necessary, or even 50? I ask because there's likely a better way to do what you really want to represent.

Also, histograms are better for discrete or continous data, not really categorical data.

[Anjali Kajan]

My analysis relies on creating treatment and control groups from ages that different ethnicities typically get married. I already have tables showing the frequency for each group but I thought a graph would be better way to show the distribution of ages within each ethnicity in my paper. What type of graph would you suggest instead?

[Jared Greathouse]

Honestly I've never had to work with so many categories that I think doing so with a histogram or a more standard plot would be a nightmare. Maybe a heatmap or something? For me to give a decent suggestion, could you please show me what your data look like using dataex?

Also, once you've done that, the person who likely has more prescient thoughts on this than me would be Nick Cox

[Anjali Kajan]

Thank you, here's part of my data

* Example generated by -dataex-. For more info, type help dataex
clear
input byte agefrstmar long ethnicityall
12 155
11  33
14  33
17  33
12  33
10  33
11  33
14 155
17 155
24 155
16 155
19 155
32 155
13 155
11  33
12  33
16  33
16  33
15  33
12  33
12  33
23 155
12 155
11  33
15  33
15  33
16 155
11  33
14  33
19  33
37  33
15  33
13  33
21 155
16  33
16  33
17  33
26 195
13  33
10  33
15  33
16  33
10  33
19  33
15  33
18  33
26  33
19  33
20  33
17  33
14  33
20  33
16  33
20  33
15  33
12  33
11  33
13 155
15  33
14  33
12  33
15  64
15  33
14  64
16  64
21  33
14  33
20  33
13  33
21 195
19  33
12  33
36  33
12  33
21  75
18 194
24  33
19  33
18 155
17 155
20  64
14  75
12  33
19  33
22  33
14  33
19  33
14  33
15  33
29 195
17 155
18  33
20  33
25  33
17  33
19  33
18  33
16  33
27  33
16  33
end
label values agefrstmar agefrstmar_lbl
label values ethnicityall ethnicityall
label def ethnicityall 33 "Bariba", modify
label def ethnicityall 64 "Dendi", modify
label def ethnicityall 75 "Fon", modify
label def ethnicityall 155 "Peulh", modify
label def ethnicityall 194 "Yoa and Lokpa", modify
label def ethnicityall 195 "Yoruba", modify