how do reshaping my data

[Hamid muili]

I have a panel data which is structured in the long format, however i want to transform it to a wide format where the time variable will be on the row while the cross sectional units with all the variables for each countries will be under their country clusters. just like the attachment added

[Clyde Schechter]

There are three different possible long arrangements for the kind of data shown. I can't tell which you have. Please post back with example data from your Stata data set. Be sure to use the -dataex- command to do that. If you are running version 18, 17, 16 or a fully updated version 15.1 or 14.2, -dataex- is already part of your official Stata installation. If not, run -ssc install dataex- to get it. Either way, run -help dataex- to read the simple instructions for using it. -dataex- will save you time; it is easier and quicker than typing out tables. It includes complete information about aspects of the data that are often critical to answering your question but cannot be seen from tabular displays or screenshots. It also makes it possible for those who want to help you to create a faithful representation of your example to try out their code, which in turn makes it more likely that their answer will actually work in your data.

[Hamid muili]

The data is posted below

* Example generated by -dataex-. For more info, type help dataex
clear
input int year str18 country byte cid float(co2kt co2percap) long efc_total_gha float(efc_total_percapita informal renewcon regquality corruption)
1996 "Argentina" 1 122545.9 3.46279 124924291 3.53 25.5  8.6  .518067 -.101317
1997 "Argentina" 1 126118.7  3.5213 114942205 3.21 24.9  9.7  .519706 -.152399
1998 "Argentina" 1 132669.9 3.66156 123480790 3.41 24.6  9.6  .521346 -.203482
1999 "Argentina" 1   134502  3.6696 117161992  3.2 25.2  8.8  .351819 -.187945
2000 "Argentina" 1 132265.5 3.56792 116673328 3.15 25.4  9.8  .182292 -.172408
2001 "Argentina" 1 125255.2 3.34188 117305163 3.13   26 11.5 -.349212 -.294732
2002 "Argentina" 1 117462.1 3.10049 112160799 2.96 26.5 11.6 -.880717 -.417056
2003 "Argentina" 1 127653.5 3.33489 121787215 3.18 25.8 10.8 -.691476 -.479977
2004 "Argentina" 1 141376.4 3.65608 120226619 3.11 25.1  9.3 -.698035 -.414409
2005 "Argentina" 1 145995.4 3.73672 124802049 3.19 24.7  9.6 -.525074 -.377738
2006 "Argentina" 1 154917.5 3.92426 129793366 3.29 24.3  9.2 -.614567 -.331239
2007 "Argentina" 1 162820.2 4.08315 141429570 3.55 23.7  7.7 -.635694 -.372122
2008 "Argentina" 1 167231.8 4.15238 147014050 3.65 23.5  7.7 -.702629 -.434875
2009 "Argentina" 1 156567.5 3.84835 103327085 2.54 24.4  8.6 -.830837 -.445475
2010 "Argentina" 1 167226.3 4.09984 140778122 3.43 23.6  8.8 -.742941  -.35523
2011 "Argentina" 1 176641.6 4.28103 141578532 3.41 23.3  8.8 -.701964 -.364098
2012 "Argentina" 1 177955.3 4.26411 140959781 3.36 23.6  8.6 -.897687 -.445909
2013 "Argentina" 1 183255.7 4.34225 154362839 3.64 23.5  8.9 -.928135 -.434016
2014 "Argentina" 1 179600.7 4.20911 151518529 3.54 23.8  9.8 -1.06615 -.549443
2015 "Argentina" 1   185550 4.30191 154895873 3.58 23.9  9.4 -.898022 -.580869
2016 "Argentina" 1 183158.7 4.20182 137069557 3.14   24  9.4 -.347571 -.298965
2017 "Argentina" 1 179267.3 4.07011 144210379 3.27 23.9 10.4   -.1963 -.308798
2018 "Argentina" 1 176894.6 3.97565 136979487 3.08 24.1 10.5 -.195978 -.098668
2019 "Argentina" 1   168162 3.74203 135365170 3.03 24.3 10.7  -.45308  -.10694
2020 "Argentina" 1 154535.9 3.40562 124821797 2.77 25.3  9.8 -.498344 -.163781
1996 "Brazil"    2 262414.1 1.58045 501273700 3.02 40.3 44.5  .296933 -.018579
1997 "Brazil"    2   281335 1.66918 498014338 2.95 40.2 43.7  .312115  .011448
1998 "Brazil"    2 290587.2 1.69894 497131629 2.91 40.9 43.8  .327298  .041475
1999 "Brazil"    2 300958.7 1.73477 513028400 2.96 40.8   44   .29287  .027357
2000 "Brazil"    2 313670.8  1.7835 529358077 3.01 39.8 42.7  .258442  .013239
2001 "Brazil"    2 319375.7 1.79211 514012309 2.88 40.2 41.3  .220505  .047591
2002 "Brazil"    2 317756.5 1.76065 505608234  2.8 40.4 42.9  .182567  .081942
2003 "Brazil"    2 310808.1 1.70185 518405690 2.84 39.7 45.1  .196701  .090239
2004 "Brazil"    2 328517.3 1.77844 488888125 2.65   39 45.2  .037414 -.027269
2005 "Brazil"    2 331689.1 1.77566 474812658 2.54 39.2 46.1  .036901 -.153748
2006 "Brazil"    2 335624.6 1.77748 482280478 2.55   39 46.7 -.041273  -.12048
2007 "Brazil"    2 352555.8 1.84798 508840150 2.67 38.3 47.2 -.022835 -.083989
2008 "Brazil"    2 373633.1 1.93922 543820830 2.82 37.6   47  .077027  .003437
2009 "Brazil"    2 350000.9 1.79933 520557105 2.68 38.4 48.9  .127607 -.079986
2010 "Brazil"    2 397931.1 2.02661 570933267 2.91 37.2 46.8   .24662  .043806
2011 "Brazil"    2 418295.4 2.11063 607141103 3.06 36.5 45.2  .258022  .168382
2012 "Brazil"    2 454232.9 2.27142 607187501 3.04 36.2 43.5  .173244 -.046854
2013 "Brazil"    2 486844.7 2.41345 615999512 3.05 36.2 42.3   .14629   -.0977
2014 "Brazil"    2   511618 2.51459 607387746 2.99 36.4 41.7  -.02822 -.365746
2015 "Brazil"    2 485344.1 2.36536 579158778 2.82 37.8 43.7  -.18191 -.457373
2016 "Brazil"    2 447077.3 2.16126 565004402 2.73 39.2 45.4 -.189952 -.445451
2017 "Brazil"    2 455684.8 2.18549 590014222 2.83 39.2 45.3 -.130867 -.559336
2018 "Brazil"    2 433838.8 2.06426 569242027 2.71 39.1 46.9 -.293126 -.480606
2019 "Brazil"    2   434318 2.05077 551386524  2.6 38.9 47.5 -.121404 -.407679
2020 "Brazil"    2 414138.8 1.94252 531925303  2.5   40   50 -.111011 -.428935
1996 "Chile"     3  44896.3 3.07183  57234275 3.92 19.4 32.2  1.54276  1.45412
1997 "Chile"     3  51285.2 3.46304  53303906  3.6 19.3   30  1.45934  1.37582
1998 "Chile"     3  52013.7 3.46833  53774689 3.59 19.3 29.8  1.37592  1.29751
1999 "Chile"     3  54430.3 3.58651  54354066 3.58   20 29.1  1.39032  1.41886
2000 "Chile"     3  50424.5  3.2846  57801994 3.77 19.8 31.4  1.40473  1.54022
2001 "Chile"     3  48425.1 3.11937  54099439 3.48 19.7 32.1  1.36161  1.50969
2002 "Chile"     3  49121.4 3.12999  53768911 3.43 19.7 33.1   1.3185  1.47916
2003 "Chile"     3  50200.6 3.16541  54931354 3.46 19.5 31.6  1.33344   1.1671
2004 "Chile"     3  54972.1  3.4319  59818039 3.73 19.3 31.4  1.36798  1.30586
2005 "Chile"     3  55968.9 3.46014  60915730 3.77   19 32.3  1.31246  1.41653
2006 "Chile"     3  57148.1  3.4986  61986431 3.79 18.8 32.9   1.4239  1.41256
2007 "Chile"     3    64574 3.91463  65660461 3.98 18.5 30.5  1.48559  1.34515
2008 "Chile"     3  67991.6 4.08077  70376536 4.22 18.7 30.8  1.50249  1.31799
2009 "Chile"     3  65450.6 3.88813  62567417 3.72 19.2 31.5   1.4274  1.32123
2010 "Chile"     3  69749.1 4.10188  73908692 4.35 18.7   27  1.41517  1.44163
2011 "Chile"     3  76470.5  4.4528  78600803 4.58 18.4 28.8  1.44053  1.47659
2012 "Chile"     3  78412.6  4.5216  77553502 4.47 18.2 30.3   1.5362  1.54359
2013 "Chile"     3  82998.5 4.74008  79115536 4.52   18 30.2  1.48287  1.49896
2014 "Chile"     3  76560.3 4.32859  74899872 4.23 18.2   27  1.48459  1.44106
2015 "Chile"     3  82260.4 4.60324  79182214 4.43 18.2 25.1  1.31984  1.18317
2016 "Chile"     3  86504.7 4.78353  80765285 4.47 18.3 24.6  1.36391  1.02332
2017 "Chile"     3  87136.9  4.7438  84288417 4.59 18.4 24.1   1.3252  1.00148
2018 "Chile"     3  86581.3 4.62966  85415030 4.57 18.4 25.5  1.30045  .958149
2019 "Chile"     3  91915.4 4.82762  87062798 4.57 18.4 25.3  1.15849  .979157
2020 "Chile"     3  84827.8 4.39515  80270701 4.16 19.4 26.7  .948648  1.10673
1996 "Colombia"  4  59253.3  1.6175  83053637 2.27 37.9 33.6 -.105488 -.512254
1997 "Colombia"  4    64837 1.73863  83832977 2.25 37.7 25.7 -.136833 -.517978
1998 "Colombia"  4  65071.4 1.71491  83821667 2.21 38.1 25.8 -.168178 -.523702
1999 "Colombia"  4  55922.1 1.44932  79306511 2.06   39   29 -.038332 -.464982
2000 "Colombia"  4  58995.5 1.50441  84043751 2.14 39.1 27.9  .091515 -.406262
2001 "Colombia"  4  59588.3 1.49577  84281217 2.12 38.9 27.1  .034126 -.335297
2002 "Colombia"  4    57373 1.41823  83302440 2.06 38.9 28.6 -.023263 -.264331
2003 "Colombia"  4    56716 1.38137  84255015 2.05 38.2 30.6 -.126519 -.204286
2004 "Colombia"  4  56608.9 1.35921  82350351 1.98   38   29 -.086416 -.140631
2005 "Colombia"  4    58187 1.37815  85350359 2.02 37.5 28.9 -.016364 -.145389
2006 "Colombia"  4    58193 1.36051  86097592 2.01   37 30.6  .106225 -.175138
2007 "Colombia"  4  59709.9 1.37877  86640043    2 36.5   31  .284263  -.27916
2008 "Colombia"  4  60298.1 1.37619  85966633 1.96 36.2 30.8   .27239 -.261543
2009 "Colombia"  4  62670.6 1.41424  87474494 1.97 36.6 31.4  .088282 -.337012
2010 "Colombia"  4  64146.1 1.43132  93164434 2.08 36.2 30.6  .157254 -.423333
2011 "Colombia"  4  69771.1  1.5399  93046344 2.05 35.5 29.6  .279602 -.317528
2012 "Colombia"  4  70223.2 1.53385  90374233 1.97 35.2 29.6  .326595 -.422298
2013 "Colombia"  4  77725.4 1.68099  93670736 2.03 34.8   32  .339824 -.441053
2014 "Colombia"  4    80091 1.71582  98071646  2.1 34.8 32.1  .444412 -.397179
2015 "Colombia"  4  81017.2 1.71939  99456686 2.11 34.5 31.1   .40772  -.35224
2016 "Colombia"  4  83526.2  1.7538  99766227 2.09 34.4 30.5  .339025 -.384033
2017 "Colombia"  4    75674 1.56508 106849215 2.21 34.6 32.2  .257449 -.429445
2018 "Colombia"  4  79355.2 1.61039 109966439 2.23 34.7 30.4  .224889 -.339971
2019 "Colombia"  4  79186.7 1.57782 114308525 2.28 34.6 31.5  .317911 -.283157
2020 "Colombia"  4  79057.6 1.55226 107742269 2.12 36.7   32  .225666 -.251916
end
format %ty cid

[Clyde Schechter]

The exact result you want is not possible in a Stata data set, because Stata does not support two levels of variable names, the parameter in one level and the country below it. The closest you can come is a sequence of variables whose names begin with the country followed by the name of the parameter, in alphabetical order. The following code will do that:

replace country = "_" + strtoname(country)
drop cid

ds year country, not
reshape wide `r(varlist)', i(year) j(country) string

ds year, not
order `r(varlist)', alphabetic after(year)

Note: I don't know if what you've shown includes all of the variables, are just some of them. It is possible that there will be some combinations of original variable name and country name that, when put together with an underscore between them, result in a proposed variable name that exceeds Stata's 32 character limit. The -reshape- command will give you an error message if that happens. The remedy will be to either shorten the name of the country or shorten the original variable name so that the combination fits within the 32 character limit, and then try again.