The survey collected data on income (low 0/average 5 /higher 12) and access to electricity (yes 1/no 0) on 8,516 households from 383 communities (clusters). I can calculate the proportion of households having access/no access to electricity and so on at individual level by using the tabulate command. Is it possible to do so at community level in Stata 14? There are many other variables like this, and my goal is to convert them in a way as if they were measured at community level.

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str15 caseid int cluster_no byte(income electricity)
"       1   9  2" 1  0 1
"       1   9  3" 1  0 1
"       1  17  4" 1 12 1
"       1  17  7" 1  0 1
"       1  25  3" 1 12 1
"       1  29  2" 1 12 1
"       1  33  2" 1  5 1
"       1  37  2" 1  5 1
"       1  49  2" 1  0 1
"       1  53  6" 1  0 1
"       1  57  2" 1 12 1
"       1  61  2" 1  0 1
"       1  69  4" 1  0 1
"       1  73  2" 1  5 1
"       1  73  3" 1  5 1
"       1  81  4" 1  5 1
"       1  85  2" 1  0 1
"       1  89  2" 1  0 1
"       1  97  3" 1  5 1
"       1 101  2" 1  5 1
"       1 117  2" 1 12 1
"       2  23  2" 2  5 1
"       2  23  3" 2  0 1
"       2  23  4" 2 12 1
"       2  36 10" 2  0 0
"       2  49  3" 2 12 1
"       2  75  2" 2  5 1
"       2  82  4" 2  0 1
"       2  95  4" 2  5 1
"       2 121  2" 2  0 1
"       2 127  3" 2  0 1
"       2 153  1" 2  0 1
"       2 153  2" 2 12 1
"       2 160  3" 2 12 1
"       2 160  4" 2  0 1
"       2 160  6" 2 12 1
"       2 166  2" 2  0 1
"       2 173  2" 2 12 1
"       2 192  2" 2  5 1
"       3  10  3" 3  5 1
"       3  17  2" 3  0 1
"       3  24  2" 3  0 1
"       3  31  6" 3 12 1
"       3  45  4" 3  5 1
"       3  52  1" 3 12 1
"       3  52  2" 3 12 1
"       3  59  3" 3  0 1
"       3  66  3" 3  5 1
"       3  87  2" 3  5 1
"       3  87  3" 3  0 1
"       3  94  3" 3  0 1
"       3 101  3" 3  5 1
"       3 108  4" 3  5 1
"       3 115  4" 3 12 1
"       3 122  2" 3  0 1
"       3 122  4" 3 12 1
"       3 136  2" 3  0 1
"       3 143  1" 3  0 1
"       3 150  2" 3  0 1
"       3 157  1" 3 12 1
"       3 164  2" 3 12 1
"       3 171  2" 3  5 1
"       3 171  6" 3  0 1
"       3 178  4" 3  5 1
"       3 178  7" 3  0 1
"       3 185  3" 3  0 1
"       3 185  6" 3  0 1
"       3 192  2" 3  0 1
"       3 206  3" 3 12 1
"       3 206  5" 3  0 1
"       4   7  2" 4  0 1
"       4  20  1" 4  0 1
"       4  48  1" 4  0 1
"       4  69  1" 4  5 1
"       4  76  1" 4  0 1
"       4  90  4" 4  0 0
"       4  97  3" 4  5 1
"       4  97  4" 4  0 1
"       4 104  2" 4  0 1
"       4 111  1" 4  0 1
"       4 118  3" 4 12 1
"       4 118  4" 4  0 1
"       4 118  5" 4  5 1
"       4 118  6" 4 12 0
"       4 118  7" 4  0 0
"       4 125  4" 4  5 1
"       4 125  7" 4  5 1
"       4 132  2" 4  0 1
"       4 139  3" 4 12 1
"       4 146  3" 4  0 1
"       4 160  3" 4  0 1
"       4 167  1" 4  0 1
"       4 181  2" 4 12 1
"       4 181  3" 4  0 1
"       4 188  1" 4  5 1
"       4 195  4" 4  0 1
"       4 195  9" 4 12 1
"       4 202  3" 4  0 1
"       4 209  4" 4  0 1
"       5  21  2" 5  0 1
end