Expand data

[Bridget Kauma]

Dear Statalist Members,

I am looking for help with expanding my dataset below to include a categorical variable that takes the values 1 to 15 for each observation. How can i do it. So i need to have 15 observations of each of the individual observations currently in the dataset.

* Example generated by -dataex-. To install: ssc install dataex
clear
input str5 nuts318cd str9 ttwa11cd double area_intersection_sqm float(percentage_nuts3_in_ttwa percentage_ttwa_in_nuts3)
"UKC11" "E30000093" 203769975.4     68.5304    26.73737
"UKC11" "E30000199" 31866.05631  .010716955   .00800233
"UKC11" "E30000203" 8120.006566   .00273086   .00047345
"UKC11" "E30000215" 93514618.39    31.45014    92.84214
"UKC11" "E30000246" 16150.06451  .005431469  .000754046
"UKC11" "E30000275" 1721.391752  .000578926  .000566958
"UKC12" "E30000093" 298643393.4    99.99471    39.18604
"UKC12" "E30000147" 15797.86158  .005289595  .003358221
"UKC13" "E30000093" 40310.33369  .020412154  .005289259
"UKC13" "E30000199" 197413336.2    99.96523    49.57521
"UKC13" "E30000203" 14324.15059  .007253395  .000835193
"UKC13" "E30000246" 14039.81523  .007109415  .000655519
"UKC14" "E30000064" 22453.95394  .001006206  .001029967
"UKC14" "E30000093" 434.9438238 .0000194907 .0000570705
"UKC14" "E30000106" 56045.84077  .002511524  .002862576
"UKC14" "E30000199"  47431345.3   2.1254914   11.911146
"UKC14" "E30000203"  1714908898    76.84842    99.99057
"UKC14" "E30000215" 7209707.493    .3230811    7.157861
"UKC14" "E30000245" 318562308.6     14.2754    25.26244
"UKC14" "E30000246" 9913.175135  .000444229  .000462846
"UKC14" "E30000275" 143346252.4    6.423626    47.21256
"UKC21" "E30000064"  2030476941    40.40051    93.13832
"UKC21" "E30000106" 12.28169309 2.44369e-07 6.27295e-07
"UKC21" "E30000173"  1460636223   29.062355    99.99895
"UKC21" "E30000203" 10266.28956  .000204269  .000598593
"UKC21" "E30000245" 563125216.8   11.204532    44.65662
"UKC21" "K01000009" 971549507.2    19.33097    57.50991
"UKC21" "K01000010" 51041.11077  .001015568  .002415779
"UKC21" "S22000067" 20922.50236  .000416296  .001403097
"UKC22" "E30000173" 1066.288223  .000265062 .0000730009
"UKC22" "E30000245" 379294671.4    94.28657     30.0786
"UKC22" "E30000275" 22982843.17    5.713166    7.569636
"UKC23" "E30000203" 5531.766495  .004028287  .000322539
"UKC23" "E30000245" 29468.49058  .021459244  .002336893
"UKC23" "E30000275"   137288062    99.97451    45.21724
"UKD11" "E30000106" 15318.28089  .000738895  .000782391
"UKD11" "E30000163" 77898272.46    3.757515   14.123253
"UKD11" "E30000223"  7257.39641  .000350069  .000672506
"UKD11" "E30000286" 737526859.2   35.575474    99.99664
"UKD11" "E30000290" 851034545.5    41.05065    99.99887
"UKD11" "K01000010" 406650680.9    19.61527   19.246805
"UKD12" "E30000039" 392.9681989 8.27563e-06 .0000333336
"UKD12" "E30000064" 149557684.9    3.149577    6.860236
"UKD12" "E30000076" 22084.66337  .000465087  .003840515
"UKD12" "E30000106"  1957803573    41.22993    99.99604
"UKD12" "E30000163" 473662135.9    9.974983    85.87675
"UKD12" "E30000203" 82740.55843  .001742456  .004824324
"UKD12" "E30000223"  1079124408    22.72558    99.99703
"UKD12" "E30000246" 20307.96607  .000427671  .000948179
"UKD12" "E30000286" 24754.72675  .000521317  .003356338
"UKD12" "E30000290" 9621.292648  .000202617  .001130528
"UKD12" "K01000010"  1088165321    22.91598    51.50294
"UKD12" "S22000067" 27691.31014  .000583159  .001857024
"UKD33" "E30000239" 115595841.7         100    6.289208
"UKD34" "E30000239" 203167544.3    99.99309    11.05371
"UKD34" "E30000284" 14042.44305  .006911277  .001959212
"UKD35" "E30000239" 229213855.8         100    12.47081
"UKD36" "E30000170" 8056.388494  .002456537   .00111413
"UKD36" "E30000239"   172919193    52.72615    9.407992
"UKD36" "E30000255" 24226.78715  .007387181  .002584866
"UKD36" "E30000284" 155005669.1      47.264    21.62651
"UKD37" "E30000029" 7006.580527  .001751785  .001925189
"UKD37" "E30000170" 11991.00274   .00299799  .001658254
"UKD37" "E30000219" 20101.86674  .005025868  .005382483
"UKD37" "E30000239" 399928974.5    99.99023   21.758884
"UKD41" "E30000170" 107194506.6    78.21149   14.824088
"UKD41" "E30000239"    29849325    21.77873   1.6240083
"UKD41" "E30000255" 13401.89378   .00977832  .001429909
"UKD42" "E30000171" 34872029.36         100    16.13467
"UKD44" "E30000039" 12103.43673  .001412412  .001026678
"UKD44" "E30000076" 574996921.4    67.09933    99.99177
"UKD44" "E30000170" 183.1079797 .0000213678 .0000253223
"UKD44" "E30000171"  64195469.6    7.491297    29.70211
"UKD44" "E30000223" 16445.66858  .001919129  .001523937
"UKD44" "E30000255" 217712862.6   25.406025   23.228775
"UKD45" "E30000039" 7479.785688  .000744056  .000634475
"UKD45" "E30000076" 13721.62053  .001364966  .002386185
"UKD45" "E30000170" 422956930.5    42.07388    58.49134
"UKD45" "E30000171" 117063523.2    11.64496    54.16322
"UKD45" "E30000182" 19037.76823  .001893793  .006798087
"UKD45" "E30000255" 465211381.6    46.27716    49.63552
"UKD46" "E30000018" 346.9086397 .0000706419  .000100878
"UKD46" "E30000029"  14486.7692  .002949978   .00398051
"UKD46" "E30000039" 9279.847951  .001889679  .000787166
"UKD46" "E30000170" 192902964.5    39.28132    26.67684
"UKD46" "E30000182" 280009612.2    57.01907    99.98702
"UKD46" "E30000239" 18143955.22      3.6947    .9871558
"UKD47" "E30000170" 17756.33516  .003231584   .00245555
"UKD47" "E30000233" 248511241.2    45.22808    40.97392
"UKD47" "E30000239" 18148.76411  .003303004  .000987417
"UKD47" "E30000255" 254286723.4    46.27919   27.131006
"UKD47" "E30000284" 46628424.33    8.486192    6.505633
"UKD61" "E30000239" 38439.87147   .02128579  .002091393
"UKD61" "E30000284" 180550930.7    99.97871   25.190605
"UKD62" "E30000185" 841.4333672 .0000721424  .000189205
"UKD62" "E30000197" 662756971.6    56.82312     78.0034
"UKD62" "E30000239" 475823055.3    40.79588    25.88804
"UKD62" "E30000262" 13702.54716  .001174822  .001188375
"UKD62" "E30000273" 27661249.03    2.371606   2.5870845
"UKD62" "E30000284" 19827.24759  .001699938  .002766313
end

Best,

Bridget

[Leonardo Guizzetti]

Thanks for providing a data example using -dataex-.

I am a little unclear on your request, but I think this is what you mean to do:
1) duplicate every observation in your example data
2) number those replicates from 1 to 15.

The following code will do this for you. I have assumed that "individuals" are index by your first two variables (-nuts318cd ttwa11cd-), but you may replace these as necessary.

If this is not what you intended, then you need to explain (or show) more clearly what you want your dataset to look like.

expand 15
sort nuts318cd ttwa11cd
by nuts318cd ttwa11cd: gen byte replicate = _n

[Bridget Kauma]

Hi Leonardo this works. Thanks a lot. You have been a great help.