Listing a series of 10 max and 10 min values of a variable in stata

[Aamina Khurraa]

Hi

I want to extract a list of my panel IDs named as "FI" and months/years named as "Time_period" having the 10 maximum and 10 minimum values corresponding to three variables i.e. X1,X2 and X3 as listed below. I have tried to look at stata forum and FAQ but could resolve this.

I have attached a sample data set. Dataex is giving problems while showing random data for my sample.

Time_Period	FI	X1	X2	X3
2006m12	1	-31.62	-17.2541	5.59478
2007m1	1	-31.1079	-13.6183	4.89549
2007m2	1	-35.0292	-21.3673	3.61578
2007m3	1	-32.0316	-13.8069	3.35394
2007m4	1	-32.1261	-14.8359	5.03884
2007m5	1	-34.7342	-17.2733	2.82228
2007m6	1	-32.1319	-15.8077	9.02871
2007m7	1	-33.2637	-16.4245	3.7428
2007m8	1	-32.4987	-14.8021	4.67124
2007m9	1	-30.7949	-12.8132	10.2397
2007m10	1	-33.5104	-15.5779	4.98208
2007m11	1	-32.8088	-17.422	2.4125
2007m12	1	-31.9746	-15.7475	0.264498
2008m1	1	-32.3618	-14.7923	4.21812
2008m2	1	-31.386	-10.8896	3.05475
2008m3	1	-32.8108	-16.8539	5.65313
2008m4	1	-31.1901	-9.4226	3.40321
2008m5	1	-30.9669	-9.5927	2.4106
2008m6	1	-28.1117	-10.4687	4.33386
2008m7	1	-37.349	-9.2677	3.50355
2008m8	1	-28.4493	-13.0546	5.14516
2008m9	1	-29.3784	-14.7088	2.7661
2008m10	1	-31.0301	-20.771	4.85348
2008m11	1	-32.0214	-18.136	1.65883
2008m12	1	-32.5977	-15.8387	1.38131
2009m1	1	-26.2674	-17.4087	3.35616
2009m2	1	-31.4534	-28.3432	1.64986
2009m3	1	-33.5362	-30.7234	1.20864
2009m4	1	-34.3029	-39.8339	2.18494
2009m5	1	-34.1437	-34.3469	2.75695
2009m6	1	-34.9015	-31.897	1.6435
2009m7	1	-32.7348	-31.4532	0.395141
2009m8	1	-32.8876	-36.4342	3.06275
2009m9	1	-35.1103	-35.6647	1.71369
2009m10	1	-34.4853	-35.1553	1.77603
2009m11	1	-33.6103	-32.3969	1.89342
2009m12	1	-32.6687	-31.1351	2.53184
2010m1	1	-32.9219	-33.26	0.377065
2010m2	1	-32.7273	-30.6241	1.48177
2007m5	2	-36.399	-12.4001	2.45553
2007m6	2	-36.7031	-10.9524	2.52438
2007m7	2	-35.1544	-9.8063	1.34138
2007m8	2	-36.7315	-13.9833	1.73393
2007m9	2	-34.6924	-13.3162	2.03121
2007m10	2	-36.5771	-15.4347	0.903296
2007m11	2	-35.3132	-14.3729	1.92998
2007m12	2	-31.9243	-13.8944	2.01513
2008m1	2	-36.4854	-11.82	2.15618
2008m2	2	-38.7875	-9.4712	1.37465
2008m3	2	-35.2983	-7.2655	0.164659
2008m4	2	-34.5109	-6.7124	0.760472
2008m5	2	-35.3267	-7.6855	2.11197
2008m6	2	-34.2074	-6.0948	0.357734
2008m7	2	-34.3853	-6.1205	1.33408
2008m8	2	-32.2983	-7.9216	1.99192
2008m9	2	-32.7456	-9.0042	1.8572
2008m10	2	-29.3405	-13.0682	1.28423
2008m11	2	-25.9295	-18.1566	1.18597
2008m12	2	-34.3702	-14.1004	1.84264
2009m1	2	-32.9606	-12.9358	1.73874
2009m2	2	-32.4144	-12.1557	1.88879
2009m3	2	-36.1901	-10.4371	2.30612
2009m4	2	-39.5233	-7.6807	1.78613
2009m5	2	-35.1506	-7.9609	2.59944
2009m6	2	-37.4168	-8.6087	1.67847
2009m7	2	-37.4519	-7.5728	1.84188
2009m8	2	-36.7478	-9.7603	1.88078
2009m9	2	-39.3216	-6.7513	1.52824
2009m10	2	-36.3919	-5.58	1.69917
2009m11	2	-31.529	-12.6839	2.18918
2009m12	2	-32.2721	-11.7222	1.77936
2010m1	2	-40.899	-10.7459	2.06669
2010m2	2	-37.0198	-14.6874	2.58071
2010m3	2	-37.6377	-11.0552	2.00856
2010m4	2	-38.3496	-6.0151	1.91164
2010m5	2	-34.9085	-12.4874	1.89597
2010m6	2	-33.7598	-14.873	1.47095
2010m7	2	-38.6767	-10.7353	1.82498
2010m8	2	-37.0398	-11.1229	2.24761
2005m5	3	-33.3961	-4.9435	1.17461
2005m6	3	-30.5544	-12.9705	2.65861
2005m7	3	-33.3243	-8.1051	2.3987
2005m8	3	-30.712	-9.0695	3.06638
2005m9	3	-32.6332	-7.1768	2.18306
2005m10	3	-32.4904	-8.352	2.23325
2005m11	3	-34.2676	-6.2287	1.75638
2005m12	3	-31.7104	-10.1193	1.94831
2006m1	3	-30.5068	-14.6299	1.12014
2006m2	3	-32.0584	-10.8112	1.99931
2006m3	3	-29.9282	-13.8727	2.05349
2006m4	3	-26.8388	-20.9504	2.49089
2006m5	3	-29.9139	-9.2954	3.16111
2006m6	3	-33.852	-18.4747	2.85708
2006m7	3	-35.5596	-17.5367	2.16876
2006m8	3	-32.8254	-20.0149	1.237
2006m9	3	-32.4573	-12.8746	1.18647
2006m10	3	-33.3377	-11.7411	2.27633
2006m11	3	-31.2758	-11.4121	2.04178
2006m12	3	-33.1126	-20.9257	1.86742
2007m1	3	-34.7782	-14.5807	2.00617
2007m2	3	-32.2737	-17.3267	1.26322
2007m3	3	-32.826	-14.8892	1.19135
2007m4	3	-34.5409	-13.3523	2.16866
2007m5	3	-33.4108	-12.2583	2.23999
2007m6	3	-33.6427	-10.6883	2.11074
2007m7	3	-32.3879	-10.6242	2.10911
2007m8	3	-33.6884	-13.5362	2.03304
2007m9	3	-32.1469	-14.2952	2.4145
2007m10	3	-33.6297	-15.0259	2.18978
2007m11	3	-32.5434	-14.82	2.36588
2007m12	3	-29.9317	-16.6507	1.8595
2008m1	3	-33.3868	-11.5976	1.73856
2008m2	3	-34.7829	-7.6451	1.82701
2008m3	3	-32.1477	-7.9235	1.36305
2008m4	3	-31.4283	-7.8764	0.424538
2008m5	3	-32.1398	-8.2825	1.43384
2008m6	3	-31.1971	-7.4982	1.67966
2008m7	3	-31.4153	-7.4362	2.09772
2008m8	3	-29.7896	-10.5289	1.24054
2008m9	3	-30.145	-11.2543	1.75509
2008m10	3	-27.7855	-17.5109	2.33656
2008m11	3	-24.8172	-24.4392	2.45384
2008m12	3	-30.8208	-14.7409	2.34108
2009m1	3	-29.4666	-14.4634	2.36558
2009m2	3	-28.905	-14.0348	1.82533
2009m3	3	-31.8386	-9.8923	0.981194
2009m4	3	-34.436	-5.0643	1.65122
2009m5	3	-30.8944	-7.1197	0.814917
2009m6	3	-32.5789	-6.5994	2.0814
2009m7	3	-32.5967	-6.2433	2.08569
2009m8	3	-32.0396	-8.7694	1.36878
2009m9	3	-34.0069	-4.1943	1.92471
2009m10	3	-31.6576	-5.02	1.41787
2009m11	3	-27.8475	-14.0928	1.49899
2009m12	3	-28.4354	-12.8362	1.71027
2010m1	3	-35.3102	-6.9316	1.95136
2010m2	3	-32.2556	-12.4605	2.04053
2010m3	3	-32.7135	-8.6773	1.52413
2010m4	3	-33.2616	-4.1516	2.1554
2010m5	3	-30.5935	-11.9555	2.79395
2014m4	4	-11.4182	-12.4488	4.12049
2014m5	4	-11.5161	-12.5761	5.57937
2014m6	4	-11.2398	-12.2653	4.87862
2014m7	4	-11.3379	-12.378	4.16158
2014m8	4	-11.0363	-12.031	4.61227
2014m9	4	-11.1065	-12.3985	5.32779
2014m10	4	-10.7403	-11.7295	4.53812
2014m11	4	-10.7211	-11.929	3.60818
2014m12	4	-9.5328	-10.9003	1.63048
2015m1	4	-8.52541	-9.9607	2.63183
2015m2	4	-11.4398	-3.9184	2.0124
2015m3	4	-10.0863	-12.3341	2.6707
2015m4	4	-16.3682	-18.584	2.53167
2015m5	4	-10.2965	-12.5639	1.54793
2015m6	4	-8.99634	-11.172	2.72849
2015m7	4	-9.52738	-14.2586	1.59571
2015m8	4	-10.671	-12.3933	1.44922
2015m9	4	-8.50324	-10.0703	0.445449
2015m10	4	-11.2874	-12.6297	3.33785
2015m11	4	-11.8667	-13.2271	3.47578
2015m12	4	-11.24	-12.345	2.6214
2016m1	4	-10.9375	-11.617	1.78829
2016m2	4	-10.4502	-11.0948	3.24688
2016m3	4	-10.4882	-11.0943	1.69079
2016m4	4	-11.0395	-11.7848	0.991117
2016m5	4	-10.3019	-10.7041	4.3579
2016m6	4	-9.29865	-15.4396	3.19182
2016m7	4	-11.2813	-11.0149	2.08944
2016m8	4	-10.8509	-10.2114	3.99318
2016m9	4	-11.6247	-10.8009	2.93907
2016m10	4	-10.733	-9.7781	1.66417
2016m11	4	-11.247	-10.2747	1.69814
2016m12	4	-10.2298	-9.0935	2.61739
2017m1	4	-11.2033	-9.93	2.57637
2017m2	4	-11.6587	-10.3313	3.00756
2017m3	4	-11.4011	-9.944	4.32675
2017m4	4	-12.5527	-5.2793	2.33856
2017m5	4	-11.0864	-9.9169	2.24577
2017m6	4	-10.5698	-9.2978	3.02978
2017m7	4	-10.4599	-8.9525	2.65721
2017m8	4	-8.75301	-7.7424	1.95377
2017m9	4	-9.15071	-8.1362	2.40478
2017m10	4	-8.51483	-7.4921	2.84579
2017m11	4	-8.44625	-7.2867	2.07805
2017m12	4	-8.03553	-6.5698	2.53319
2018m1	4	-9.354	-7.447	2.29817
2018m2	4	-9.61835	-7.2637	2.03962
2018m3	4	-8.93064	-1.9172	2.07927
2018m4	4	-8.16795	-4.7822	2.11018
2018m5	4	-7.93117	-4.5514	0.908515
2018m6	4	-6.2193	-2.8093	1.66997
2018m7	4	-8.62767	-4.6205	1.7408
2018m8	4	-11.4251	-7.4867	1.66439
2018m9	4	-10.5638	-5.9207	2.6215
2018m10	4	-11.0462	-6.652	1.98961
2018m11	4	-10.7081	-5.8977	1.42967
2018m12	4	-9.7917	-4.3473	2.19367
2019m1	4	-10.7452	-5.1528	2.20975
2019m2	4	-7.24964	-1.8362	2.09057
2019m3	4	-11.2934	-5.579	1.71869
2019m4	4	-10.6879	-5.7262	2.03399
2019m5	4		0	4.55039
2019m6	4		0	4.58949
2019m7	4		0	3.14705
2019m8	4		0	5.42092

Best Regards

[Andrew Musau]

Sort and list

sort var
l var in 1/10
l var in -10/l

[Nick Cox]

I am fuzzy about exactly what is wanted here, and the absence of a good data example using dataex is inhibiting

-- a quick check on your previous threads shows repeated mentions of dataex or requests to read https://www.statalist.org/forums/help#stata --

but I flag the existence of extremes on SSC. e.g.

. sysuse auto, clear
(1978 Automobile Data)

. ssc install extremes 

. extremes mpg make

  +--------------------------------+
  | obs:   mpg   make              |
  |--------------------------------|
  |  26.    12   Linc. Continental |
  |  27.    12   Linc. Mark V      |
  |  11.    14   Cad. Deville      |
  |  12.    14   Cad. Eldorado     |
  |  28.    14   Linc. Versailles  |
  +--------------------------------+

  +-----------------------------+
  |  68.    31   Toyota Corolla |
  |  43.    34   Plym. Champ    |
  |  57.    35   Datsun 210     |
  |  66.    35   Subaru         |
  |  71.    41   VW Diesel      |
  +-----------------------------+

note: 6 values of 14

. extremes mpg make, n(10)

  +--------------------------------+
  | obs:   mpg   make              |
  |--------------------------------|
  |  26.    12   Linc. Continental |
  |  27.    12   Linc. Mark V      |
  |  11.    14   Cad. Deville      |
  |  12.    14   Cad. Eldorado     |
  |  28.    14   Linc. Versailles  |
  |--------------------------------|
  |  30.    14   Merc. Cougar      |
  |  33.    14   Merc. XR-7        |
  |  64.    14   Peugeot 604       |
  |   5.    15   Buick Electra     |
  |  31.    15   Merc. Marquis     |
  +--------------------------------+

  +-----------------------------+
  |  42.    28   Plym. Arrow    |
  |  62.    28   Honda Civic    |
  |  14.    29   Chev. Chevette |
  |  20.    30   Dodge Colt     |
  |  63.    30   Mazda GLC      |
  |-----------------------------|
  |  68.    31   Toyota Corolla |
  |  43.    34   Plym. Champ    |
  |  57.    35   Datsun 210     |
  |  66.    35   Subaru         |
  |  71.    41   VW Diesel      |
  +-----------------------------+

note: 3 values of 28

[Aamina Khurraa]

Thank you both !

Indeed it was as simple as it is.

Nick Cox I tried to use dataex (randomtag) but could not sort how to extract random data to show substantial panel IDs and time periods.

Best Regards

[Leonardo Guizzetti]

If one listing is desired, Andrew's recommendation can be compressed somewhat:

sysuse auto
sort mpg
list mpg if inrange(_n, 1, x) | inrange(_n, _N-x+1, _N)  // replace x with whatever number of extreme values you want.

[Nick Cox]

it doesn't bite with with the example in #5 -- which uses a trick that deserves to be better known -- but more general code has to be deal with

* missing values --- which in this context are rarely of interest

* other if (or occasionally in) conditions.

[Nick Cox]

#4 No call for anything subtle. From #1 you make clear that FI is the panel identifier so something like

dataex FI TimePeriod X1 X2 X3  if FI <= 3

should work fine, including showing the time variable in a way that is easy to read in.