Dear all,

I am working with a large dataset of nearly 3 million observations on house prices in the UK from year 2019 to 2020.

I need to merge together two variables into one, split by region.
For example, I would like to merge x2019 and x2020 into a new variable y, which is linked through region.
Both of these variables came from different datasets.

I need this to be in a panel data format so I can plot out the coordinates of y with x1 and x2 on the axis.

Below is an example of my x2019 and x2020 variables using dataex.

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input double(x2019 x2020)
                 . .42308459033822843
                 .                  .
.24348377773469856                  .
                 .  .4683997003237069
                 . .16909276343238608
 .5787574449282433                  .
 .1365918764292748                  .
                 .   .460714720318014
 .3303238932587331                  .
  .265934841146259                  .
.28729663560259044                  .
 .2716066023747963                  .
 .4123490338164251                  .
.23285661071666422                  .
 .1664648289168497                  .
                 .  .3152704688759304
                 .  .4914925660087157
                 .  .4752179752286342
                 . .36603411584390955
 .1561791497567391                  .
                 .  .2119552035328655
.19282310232009203                  .
   .27372177496442                  .
 .3488016048991659                  .
                 .  .5945918777643747
.20533381933053885                  .
.38149989641599336                  .
.24573953472471496                  .
 .2409179992615105                  .
 .2804320544998207                  .
.08273121387283237                  .
.40612155515127013                  .
 .3170900748034319                  .
                 .  .5224719101123596
                 .   .617407502569373
.24407748862177617                  .
                 . .22166680704118588
                 .  .4852172147100137
 .2582730389985398                  .
 .5766047242033632                  .
 .2641388540836086                  .
                 . .27048574101063716
                 .  .4648585410036104
.21969389376312956                  .
.17276593457535794                  .
.10039173195532589                  .
.39619787280496555                  .
                 . .33669012713161045
.21956334215770845                  .
                 . .30773099456483377
.22532540034566617                  .
  .362444120625355                  .
.14336389298293822                  .
                 . .24082764998266096
.09470704857306829                  .
                 .  .3798186432956592
.18431877215559644                  .
.24290262090619685                  .
                 .  .2777777777777778
.09690204108593699                  .
.21872986810429593                  .
                 .  .3840880389680678
                 .  .2912608059294722
.24347066248098645                  .
 .2864613226197309                  .
 .4615424505797673                  .
                 . .24955764342321687
                 . .22979053294013924
.43715965430359516                  .
                 .  .1758399864586566
                 .  .4808308192155953
                 . .33978913591565435
                 .  .2718742870180242
 .3155639176335319                  .
                 . .17306037245243633
 .3491067799904582                  .
                 .   .348773754149255
 .1671383130415707                  .
 .2812089711833895                  .
                 . .34860474802165764
                 .  .2861936922090452
                 . .33535291577214604
                 .  .5764460194912037
.42285143667053215                  .
                 .   .338753524812995
                 . .24162223914699163
                 . .20313215030253726
                 .  .5341546825675202
                 .  .4235055939200899
                 .  .4456736248158546
                 .  .3978756638550453
 .3576040781648258                  .
.22698625440264314                  .
                 .  .3287705999796961
 .4423823797732308                  .
.26536086800143865                  .
.15740628264619422                  .
.22256726982529795                  .
.25606091647886364                  .
                 .   .419142689371697
end
As you can see above, each observation does not correspond to a value in both 2019 and 2020. This is what I am trying to change.

If anyone has any suggestions on how to go about this I'd greatly appreciate it.

I am using Stata 15.1 for Windows 10.

Many thanks in advance,
James.