Extract strings from value labels

Adam Madison

Join Date: Nov 2019
Posts: 11

Extract strings from value labels

10 Jul 2022, 12:22

I have a variable (crds) that is numeric but has string value labels (AAA, AA+, AA, AA- .....). I would like to extract the string labels when I use the "levelsof" command. However, the command returns the numeric values (1, 2, 3,....).
Ultimately, I want the local macro 'rates' to contain just the labels that exist for that given year.

Code:

levelsof fyear, local(years)
foreach x of local years  {
levelsof crds if fyear==`x', local(rates)
   oprobit crds size profitability if fyear==`x'
  if c(rc) == 0 {    // SUCCESSFUL REGRESSION, PREDICT
predict `rates' if fyear==`x',p
egen double m2= rowmax( `rates' )
gen wanted=""
foreach y of local rates {
replace wanted = "`var'" if m2==`y'
}
drop m2
drop `rates'



  }
          else if !inlist(c(rc), 2000, 2001) {    // UNANTICIPATED PROBLEM -- COMPLAIN AND HALT!
            display as error `"Unexpected error performing regression with FYear == `x'"'
            exit c(rc)
        }
        
        
          

}

Code:

* Example generated by -dataex-. To install: ssc install dataex
clear
input float crds double fyear float(size profitability)
 8 1986  5.697738    .14509776
 8 1987  5.851168    .14861053
 8 1988  6.007239    .15657243
 8 1989  6.097794    .13145955
 8 1990  6.145348    .08674178
 8 1991  6.046561     .0698235
 8 1992   5.94746    .04133795
 8 1993  6.010664    .05976706
 8 1994  6.112343    .05851647
 7 1995  6.224539     .0761882
 7 1996  6.378983    .09795681
 7 1997  6.662012    .12220158
 8 1998  6.822237    .11539774
 8 1999  6.931797    .09724069
 8 2000  6.773372    .06179504
 8 2001  6.459468   .006712222
 7 2002  6.407436   .005030985
 4 2003   6.47998     .0303093
 4 2004    6.6172    .04768699
 4 2005  6.799372    .08556738
 4 2006  6.967126     .0885843
 5 2007  7.233397    .12042527
 5 2008  7.261208    .09216452
 5 2009  7.209452    .06926624
 5 2010  7.481996     .0912806
 5 2011  7.637475    .08355799
 5 2012  7.681145    .06221383
 5 2013  7.618251    .06673218
 5 2014   7.37419 -.0039099795
 6 2015  7.416138    .04363036
 6 2016  7.477378    .05353304
 7 1986   6.00607    .19869854
 7 1987  6.191094    .15719526
 5 1990  5.618432    .11621958
 5 1991  5.671741    .04589111
 5 1992  5.687355    .07940808
 4 1998  6.404541    .10856099
 4 1999  6.596385    .10729799
 4 2000  6.803277    .10833464
 4 2001  6.882427    .05339551
 4 2002  7.115389    .05970649
 4 2003  7.168029    .04595145
 3 2004  7.200037   .028598255
 2 2005  6.316473    .04790547
 2 2006  6.482844    .05916102
 3 2007  6.582613  -.005955315
 8 2000  7.769051    .09020176
 3 1989  6.047755    .04169867
 3 1990  6.105851    .05271026
 3 1991  6.007547   .029315056
 3 1992  6.002565     .0772308
 3 1993  6.375796    .16235144
 4 1994  6.336231    .10179821
 4 1995   6.48901    .13495636
 4 1996  6.619536    .12488365
 4 1997  6.741458      .051216
 4 1998  6.934125   .016725728
 3 1999  7.062142 -.0018550215
 3 2000  7.102335 -.0020507989
 1 2001  7.201548     .0519506
 1 2002  7.490848    .05680793
 2 2003  7.485951   .071463525
10 1986  8.702539    .06399575
11 1987  8.881555     .0612468
11 1988  9.085264    .09574577
11 1989  9.257186     .0765243
11 1990  9.369018   .011399782
10 1991  9.463974  .0003744309
 9 1992  9.574706 -.0015424482
 8 1993   9.66148     .0307388
 6 1994   9.68887   .066438995
 6 1995  9.735661    .07944165
 6 1996  9.784309    .09536715
 6 1997  9.829303    .09396497
 7 1998  9.862926     .1117858
 7 1999  9.783013    .05183159
 7 2000  9.888526    .05665873
 7 2001  9.850245   -.07095716
 5 2002  9.758404   -.07983922
 4 2003  9.766521   -.02626623
 1 2004  9.833333 -.0045346064
 1 2005  9.938469    .00354499
 1 2006 10.024067   .035938296
 2 2007 10.038717   .035306226
 2 2008 10.076012    -.0200553
 1 2009  9.899329   -.02959285
 1 2010 10.006495    .01210787
 1 2011 10.086725  -.011399873
 4 1994  7.769495    .04681891
 4 1995  7.811076   -.10509934
 3 1996  7.651426    -.2053701
 3 1986  3.988095      .088161
 3 1987 4.1050043    .10455878
 3 1988  4.462396    .06977539
 2 1986   5.59917    .05506955
 5 1986  5.274839    .02453905
 5 1987   5.60539    .12987158
 5 1988  6.013566    .14057508
 5 1989  6.022285    .13289216
 6 1992   7.43227      .084452
 7 1993  7.449229    .08250108
 7 1994   7.42977     .0767264
 7 1995  7.420458     .0813957
 7 1996   7.50536     .0777269
 8 1997  7.598413    .07976581
 8 1998  7.664152    .08278737
 8 1999  7.792907    .08480813
 8 2000  8.213429    .10228802
 8 2001  8.423184    .09436464
 8 2002  7.877503    .06465338
 8 2003   7.94373     .0572115
 8 2004  7.972371    .05308714
 8 2005  8.002344    .06606726
 7 2006  8.132045    .05465773
 7 2007  8.167244      .054055
 7 2008    8.1218    .04718602
 7 2009  8.100799    .04993299
 7 2010    8.0906    .06130373
 7 2011  8.083755    .06038388
 8 2012  8.102224    .06496483
 9 2013   8.14747    .06325466
10 2014  8.158125    .06005336
10 2015  8.159215    .05970588
10 2016  8.160142     .0569583
10 2017  8.179003    .05838617
15 1986  8.244763    .25332078
15 1987 8.3866005     .2601585
15 1988  8.504511    .25127295
15 1989  8.590398     .2530743
15 1990  8.725618    .28980768
15 1991  8.835877    .27988276
15 1992  8.968513     .2783274
16 1993  9.036921    .28207743
16 1994  9.122166    .27888247
16 1995  9.211559     .2795614
16 1996  9.306873    .28196955
16 1997  9.382903    .25620425
16 1998   9.43171    .25851133
16 1999  9.486276    .25223374
16 2000  9.528497    .22542037
16 2001  9.698015    .23149076
14 2002  9.780453    .16916077
14 2003  9.887386    .17167874
14 2004  9.887359     .1667703
14 2005 10.011795     .1680855
14 2006 10.020218     .1667817
14 2007 10.162548     .1526762
14 2008  10.29308     .1630938
14 2009 10.334124    .16275036
14 2010 10.467855     .1533632
14 2011 10.567495    .15129676
14 2012 10.593477    .16230954
12 2013  9.991864    .03977098
12 2014  9.915762   .068144254
12 2015  9.923535    .08169594
12 2016  9.945253    .08781245
 8 2017 10.217934    .07587438
 5 1993  7.533159   -.02289857
 5 1994  7.654917   .015514977
 7 1997  8.228711    .04761905
 7 1998  8.114025   .018268468
 7 1999  8.303752    .02355523
 7 2000  8.644178    .14264792
 7 2001  8.704834    .08387383
 7 2002    8.5413   .015546255
 7 2003  8.473451   -.01527765
 6 2004  8.665786   .017378498
 4 2005  8.583355    .01348728
 3 2006   8.48694   .016907012
 3 1998  5.547717    .11485256
 4 1999  5.628297    .06827657
 4 2000  5.414161   .006924207
 4 2001  5.292586     -.039039
 4 2004  7.248403     .1905117
 4 2005  7.291656   .011649908
 4 2006  7.321857    .05157535
 4 2007  7.971823    .26735127
 4 1986 4.1470003    .12500253
 3 1986  6.448859   -.08427946
 3 1987  6.904831   -.01930785
 3 1988  7.026298   .028231615
 3 1989  7.007244   .035542335
 3 1990  6.965309   -.04554465
 3 1991  7.112041    .09819266
 3 1992  7.322834     .2089749
 5 1993  7.407487    .21065815
 3 1994  7.666062     .2659811
 4 1995  7.795533     .1424037
 5 1996  7.577132    -.0806956
 4 1997   7.76488   -.02882189
 4 1998  7.840762   -.04655175
 2 1999  7.957739   -.06646794
 2 2000  8.443372    .20301445
 2 2001  8.266615    .00657936
 2 2002  7.899906    -.1510137
 1 2003   8.16598   -.04400588
 1 2004   8.51748    .03203467
 2 2005  8.673782   .031571694
 3 2006  8.639234    .05502363
 3 2007  8.701679   -.09211227
end
label values crds mylabel1
label def mylabel1 1 "B-", modify
label def mylabel1 2 "B", modify
label def mylabel1 3 "B+", modify
label def mylabel1 4 "BB-", modify
label def mylabel1 5 "BB", modify
label def mylabel1 6 "BB+", modify
label def mylabel1 7 "BBB-", modify
label def mylabel1 8 "BBB", modify
label def mylabel1 9 "BBB+", modify
label def mylabel1 10 "A-", modify
label def mylabel1 11 "A", modify
label def mylabel1 12 "A+", modify
label def mylabel1 14 "AA", modify
label def mylabel1 15 "AA+", modify
label def mylabel1 16 "AAA", modify

Tags: levelsof, value labels

Clyde Schechter

Join Date: Apr 2014
Posts: 29964

10 Jul 2022, 12:46

Code:

levelsof fyear, local(years)
foreach x of local years {
    levelsof crds if fyear==`x', local(n_rates)
    local rates
    foreach r of local n_rates {
        local rates `rates' `:label (crds) `r''
    }
    display `"`rates'"'
    // ETC>
}

Added: It just dawns on me it might be simpler and more transparent to just do this:

Code:

decode crds, gen(alpha_crds)
levelsof fyear, local(years)
foreach x of local years {
    levelsof alpha_crds if fyear==`x', local(rates)
    display `"`rates'"'
    // ETC.
}

Unless your data set is huge and you are tight on memory, this is probably better than my first solution.

Last edited by Clyde Schechter; 10 Jul 2022, 12:50.

Comment

Adam Madison

Join Date: Nov 2019

Posts: 11
#3

10 Jul 2022, 13:36

Thank you Clyde. Your second solution seems to be moving me in the right direction. One last problem: The strings contained in local macro 'rates' are surrounded by quotation marks. Is there any way to remove them?
Comment
William Lisowski

Join Date: Dec 2014

Posts: 10150
#4

10 Jul 2022, 13:44

The output of

Code:

help levelsof

suggests that adding the clean option to the levelsof command will do what you want.
Comment
Adam Madison

Join Date: Nov 2019

Posts: 11
#5

10 Jul 2022, 17:25

Thank you both. Your recommendations worked.
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