Sorting Panel Data to clean errors

[Sadie Belechak]

I am using NLSY1979 panel data. I want to sort my variable weight in ascending order, but I want to still see every weight observation for that ID. This way I can determine if the extreme weight values are mistakes or if they are reasonable weights in comparison to the ID's weights in every year. So I'm trying to get it to do something like this and I cannot figure out what commands to use.
'sort weightchange ID' and vice versa are not working
"sort ID year
sort weightchange, stable " also dont work. any ideas?

ID	year	Weightchange	weight
1	2002	-700	200
1	2001	100	900
1	2003	0	200
2	2001	-650
2	2002
2	2003
3	2001	-645
3	2002
3	2003

[Maarten Buis]

What do you exactly want your commands to do?
What do you mean with "does not work"?

Maybe you can give us an example dataset (see the FAQ in the black bar on the top of this page, on how to do that), run the commands you tried on that example dataset. Show us what Stata showed you and explain why that is not what you want

[William Lisowski]

Let me agree with the advice from Maarten Buis about providing an example of your data using dataex.

If you are running version 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 and 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.

One thing dataex will do is make it clear if your Weightchange variable is stored as a numeric value or as a string. If it is stored as a string, that is probably why your sorts "are not working" - they are in fact working, but strings containing numbers do not sort in the same order as numbers. Here is an example.

* Example generated by -dataex-. For more info, type help dataex
clear
input float number str4 string
 100 "100" 
 200 "200" 
  25 "25"  
  10 "20"  
-100 "-100"
-200 "-200"
 -25 "-25" 
 -10 "-10" 
   0 "0"   
end

sort number
list, clean
sort string
list, clean

. sort number

. list, clean

       number   string  
  1.     -200     -200  
  2.     -100     -100  
  3.      -25      -25  
  4.      -10      -10  
  5.        0        0  
  6.       10       20  
  7.       25       25  
  8.      100      100  
  9.      200      200  

. sort string

. list, clean

       number   string  
  1.      -10      -10  
  2.     -100     -100  
  3.     -200     -200  
  4.      -25      -25  
  5.        0        0  
  6.      100      100  
  7.       10       20  
  8.      200      200  
  9.       25       25

[William Lisowski]

Having done the work above, I now see that instead of posting the example as a reply to this topic, a new topic was started and responded to at

https://www.statalist.org/forums/for...o-clean-errors

[Farai Matanga]

Hello I have a similar question about sorting/cleansing my data. I am currently trying to see if there is a relationship between Foreign Direct Investment/Foreign Aid between Donor and Recipient countries. I would like to see the number of times a donor country is sending both Foreign Aid and Foreign Direct investment to a Recipient country for specific years. Do you guys know any codes that would help?

Here is my dataset

dataex IsoCode1 IsoCode2 FDIOutflowsDonor NetODA

clear
input str4 IsoCode1 str3 IsoCode2 double(FDIOutflowsDonor NetODA)
"DEU" "AFG" 2 20.29
"DEU" "AFG" -1.7 24.78
"DEU" "AFG" 0 15.66
"DEU" "AFG" 0 23.09
"DEU" "AFG" 0 17.32
"DEU" "AFG" . 73.06
"DEU" "AFG" 0 143.61
"DEU" "AFG" 0 104.86
"DEU" "AFG" 0 86.3
"DEU" "AFG" 0 113.48
"DEU" "AFG" 0 133.08
"DEU" "AFG" 0 220.67
"DEU" "AFG" 0 281.01
"DEU" "AFG" 0 327.91
"DEU" "AFG" 0 477.04
"DEU" "AFG" 0 516.11
"DEU" "AFG" 0 525.87
"DEU" "AFG" 1.33 531.41
"DEU" "AFG" -7.97 503.64
"DEU" "AFG" 0 404.49
"DEU" "AFG" 0 556.11
"DEU" "AFG" 1.13 511.34
"DEU" "AFG" -1.18 438.53
"DEU" "AFG" 0 423.2
"DEU" "AGO" 12 29.43
"DEU" "AGO" 15.6 21.04
"DEU" "AGO" 6.3 15.96
"DEU" "AGO" 2.1 25.27
"DEU" "AGO" -1.8 18.4
"DEU" "AGO" 2.68453973566232 16.45
"DEU" "AGO" -2.823396546044892 25.57
"DEU" "AGO" 0 17.19
"DEU" "AGO" 2.483346060481893 14.88
"DEU" "AGO" 2 14
"DEU" "AGO" 0 12.8
"DEU" "AGO" 31.47933723677115 12.46
"DEU" "AGO" 19 11.13
"DEU" "AGO" 11.1 8.17
"DEU" "AGO" 30.5 7.16
"DEU" "AGO" . 5.44
"DEU" "AGO" . 4.92
"DEU" "AGO" 13.28 4.03
"DEU" "AGO" -13.29 4.03
"DEU" "AGO" -8.88 2.49
"DEU" "AGO" -1.11 2.91
"DEU" "AGO" 0 2.84
"DEU" "AGO" -2.36 4.2
"DEU" "AGO" -3.36 4.4
"DEU" "BDI" -2.7 16.1
"DEU" "BDI" 0 8.21
"DEU" "BDI" 1.7 6.73
"DEU" "BDI" -1.1 2.37
"DEU" "BDI" 0 4.92
"DEU" "BDI" 0 5.38
"DEU" "BDI" 0 4.2
"DEU" "BDI" 0 6.1
"DEU" "BDI" 0 11.91
"DEU" "BDI" 0 12.99
"DEU" "BDI" 0 16.4
"DEU" "BDI" 0 23.39
"DEU" "BDI" 0 22.11
"DEU" "BDI" 0 27.12
"DEU" "BDI" 0 29.92
"DEU" "BDI" 0 31.49
"DEU" "BDI" 0 24.54
"DEU" "BDI" 0 24.03
"DEU" "BDI" 0 24.59
"DEU" "BDI" -1.11 19.46
"DEU" "BDI" 0 50.97
"DEU" "BDI" 0 35.13
"DEU" "BDI" 0 33.38
"DEU" "BDI" 0 38.67
"DEU" "BEN" -.7 26.08
"DEU" "BEN" 0 27.12
"DEU" "BEN" 0 43.64
"DEU" "BEN" 0 38.36
"DEU" "BEN" 0 35.39
"DEU" "BEN" 0 36.2
"DEU" "BEN" 0 37.25
"DEU" "BEN" 0 39.92
"DEU" "BEN" . 28.09
"DEU" "BEN" . 31.56
"DEU" "BEN" . 29.85
"DEU" "BEN" . 30.06
"DEU" "BEN" . 44.55
"DEU" "BEN" . 41.92
"DEU" "BEN" 0 35.21
"DEU" "BEN" 0 47.37
"DEU" "BEN" 0 48.58
"DEU" "BEN" 0 49.37
"DEU" "BEN" 0 73.93
"DEU" "BEN" 1.11 42.88
"DEU" "BEN" 4.43 44.06
"DEU" "BEN" 2.26 39.83
"DEU" "BEN" 0 42.15
"DEU" "BEN" 0 46.68
"DEU" "BFA" 0 47.76
"DEU" "BFA" -.6 42.08
"DEU" "BFA" 0 56.8
"DEU" "BFA" 0 51.25
end

[Nick Cox]

#6 That would depend on whatever variable(s) you have that represent time or date, which aren't evident in your data example.