64 attribute fields, profiled from the March 2023 vintage.
Columns in Lea County
| Field | Type | Filled | Distinct | Example values |
|---|---|---|---|---|
| triadic | OFTString | 31.3k | 12634, 2891, 17147 | |
| upc_xy | OFTString | 39.8k | 4225107158151, 4225107158226, 4225107159302 | |
| calc_acre | OFTReal | 30.4k | 0.20650204, 0.22336952, 0.2200612 | |
| twp | OFTString | 19 | 18, 18, 18 | |
| rng | OFTString | 9 | 38, 38, 38 | |
| section_ | OFTString | 38 | 27, 27, 27 | |
| fcode | OFTInteger | 8 | 500, 500, 500 | |
| parcelcode | OFTString | 36.2k | 4000126340001, 4000028910001, 4000171470001 | |
| gpryr | OFTString | 30 | 2012, 2012, 2018 | |
| gpcod | OFTString | 1 | 06, 06, 06 | |
| gonam | OFTString | 22.8k | MEDRANO, FERNANDO G, GARCIA, ROSA CARMINA, HAWKINS, J BRAD | |
| shape_area | OFTReal | 42.2k | 8995.22891033, 9729.97663893, 9585.86624413 | |
| objectid | OFTInteger | 42.5k | 34191, 34192, 34193 | |
| shape_len | OFTReal | 42.2k | 394.91237995, 406.49406778, 404.128231316 | |
| gpprp | OFTString | 36.2k | 4000126340001, 4000028910001, 4000171470001 | |
| gpprpe | OFTString | 1 | 1, 1, 1 | |
| gpxy | OFTReal | 1 | 0.0, 0.0, 0.0 | |
| gonum | OFTInteger | 30.8k | 12634, 2891, 17147 | |
| gocon | OFTString | 11.5k | PENA, JOSE LUIS OMAR, VARNER, MARY JO, HAVENS, JAMIE M | |
| goad1 | OFTString | 15.4k | 2234 N ADOBE DR, 2230 ADOBE DR, 2222 N ADOBE DR | |
| goad2 | OFTString | 6.2k | PO BOX 762, 1501 N GRIMES, HCR 65 BOX 900 | |
| gocit | OFTString | 980 | HOBBS, HOBBS, HOBBS | |
| gost | OFTString | 47 | NM, NM, NM | |
| gffor | OFTString | 3 | GERMANY, ONTARIO L4B-3G2 CANADA, ONTARIO L4B-3G2 CANADA | |
| gozp5 | OFTString | 1.5k | 88240, 88240, 88240 | |
| gozp4 | OFTString | 2.4k | 4406, 1837, 9709 | |
| gdcdst | OFTString | 10 | 161, 161, 161 | |
| gdcdss | OFTString | — | ||
| gptyp | OFTString | 2 | S, S, S | |
| gpyrc | OFTInteger | 3 | 2020, 2020, 2020 | |
| gprc_ | OFTInteger | 21.4k | 43875, 44378, 0 | |
| gpmis | OFTString | 7 | 1, 1, 1 | |
| gpbk | OFTString | 1.9k | 1779, 1781, 070 | |
| gppg | OFTInteger | 1.0k | 649, 421, 696 | |
| gprdat | OFTInteger | 6.8k | 20120522, 20120605, 0 | |
| gstnam | OFTString | 1.1k | ADOBE RD, ADOBE RD, ADOBE RD | |
| ganum | OFTString | 3.0k | 2234, 2230, 2222 | |
| gahlf | OFTString | 136 | 1/2, 730, 311 | |
| gadir | OFTString | 4 | N, N, N | |
| gaqtr | OFTString | — | ||
| gabdg | OFTString | 42 | #1-#2, #5-#6, #4 | |
| gabap | OFTString | 37 | 2509, APTD, &717 | |
| greapv | OFTInteger | 1 | 0, 0, 0 | |
| greapl | OFTInteger | 1 | 0, 0, 0 | |
| grdtev | OFTInteger | 1 | 0, 0, 0 | |
| grdtes | OFTInteger | 1 | 0, 0, 0 | |
| gtnum | OFTReal | 2.2k | 0.0, 0.0, 0.0 | |
| gtvall | OFTInteger | 6.7k | 15999, 15915, 10716 | |
| gtvali | OFTInteger | 18.4k | 122502, 150900, 127332 | |
| gtvalc | OFTInteger | 88 | 0, 0, 0 | |
| gtvalp | OFTInteger | 412 | 0, 0, 0 | |
| gtvalh | OFTInteger | 1 | 0, 0, 0 | |
| gtvalo | OFTInteger | 183 | 0, 0, 0 | |
| gtfull | OFTInteger | 21.7k | 138501, 166815, 138048 | |
| gttxbl | OFTInteger | 21.7k | 46167, 55605, 46016 | |
| gtexmp | OFTInteger | 843 | 0, 0, 2000 | |
| gtnet | OFTInteger | 21.1k | 46167, 55605, 44016 | |
| gdat | OFTInteger | 3.3k | 20160104, 20160104, 20110818 | |
| gtim | OFTInteger | 19.3k | 90521, 90252, 131817 | |
| gtyrc | OFTInteger | 3 | 2019, 2019, 2019 | |
| gtbill | OFTInteger | 30.4k | 21714, 12048, 14467 | |
| gttax | OFTReal | 23.9k | 1219.22, 1468.47, 1127.03 | |
| gtdat | OFTInteger | 79 | 20190918, 20190918, 20190918 | |
| gttim | OFTInteger | 144 | 172015, 172007, 172009 |
Why this differs from the next county over
There is no national parcel schema. Every assessor's office built its own, usually decades ago, usually inside whatever CAMA system it bought at the time. One county's owner column is OWNER_NAME, the next one's is own1, and a third splits it across four fields. Shapefile's ten-character DBF limit truncated a generation of them into things like TOTLNDVAL.
Nothing here is renamed or remapped. The columns above are exactly what is in the file, because a normalisation layer that quietly guesses wrong is worse than no normalisation at all — and every guess it makes is one you cannot audit.
The Filled column is the share of rows with a real value. Placeholder text such as n/a counts as empty; a column that is 100% present but 90% placeholder is a column that will disappoint you, and the profiler treats it accordingly.