52 attribute fields, profiled from the January 2023 vintage.
Columns in Delaware County
| Field | Type | Filled | Distinct | Example values |
|---|---|---|---|---|
| objectid | OFTInteger | 50.0k | 83576, 83577, 83581 | |
| parcel_no | OFTString | 50.0k | 60033407016000, 60033407020000, 60033408016000 | |
| splitdate | OFTInteger | 4.4k | 19840303, 19840303, 19840303 | |
| sub_name | OFTString | 4.5k | MUIRFIELD VILLAGE PH 17 PT 2, MUIRFIELD VILLAGE PH 17 PT 2, MUIRFIELD VILLAGE PH 17 PT 2 | |
| condo | OFTString | 1.3k | 8740 & 8742 CRAIGSTON COURT CONDO, 8708 & 8712 CRAIGSTON COURT CONDO, 8740 & 8742 CRAIGSTON COURT CONDO | |
| mapsheet | OFTString | 362 | 600334, 600334, 600334 | |
| subparcel | OFTString | 10 | 0, 0, 0 | |
| nghbrhdcd | OFTString | 781 | 10111, 10111, 10001 | |
| mailname1 | OFTString | 33.2k | CORELOGIC, LERETA LLC, LERETA LLC | |
| mailname2 | OFTString | 12.8k | ATTN: TAX DEPARTMENT, ATTN: TAX DEPARTMENT, & RUQIAO C | |
| mailaddr1 | OFTString | 30.9k | 3001 HACKBERRY, 901 CORPORATE CENTER DR, 901 CORPORATE CENTER DR | |
| mailaddr2 | OFTString | 1.3k | IRVING, TX 75063, POMONA, CA 91768, POMONA, CA 91768 | |
| owner1 | OFTString | 50.0k | KERN MELANIE & CHRISTOPHER, MUSAH TAWFIQ, MARCHAL MEGAN E & TODD C | |
| owner2 | OFTString | 1 | 0, 0, 0 | |
| addr1 | OFTString | 50.0k | 8465 DAVINGTON DR, 8393 DAVINGTON DR, 8378 DAVINGTON DR | |
| addr2 | OFTString | 28 | DUBLIN, OH 43017, DUBLIN, OH 43017, DUBLIN, OH 43017 | |
| taxdist | OFTReal | 65 | 10.0, 10.0, 10.0 | |
| legal | OFTString | 50.0k | LOT 54^RIVIERA SEC 2^TIF 25%, LOT 55^RIVIERA SEC 2^TIF 25%, LOT 56^RIVIERA SEC 2^TIF 25% | |
| class | OFTString | 137 | 510, 510, 510 | |
| acres | OFTReal | 9.9k | 0.0, 0.0, 0.0 | |
| market_lan | OFTInteger | 5.4k | 80000, 80000, 125000 | |
| market_imp | OFTInteger | 8.1k | 259500, 320200, 333500 | |
| market_tot | OFTInteger | 10.1k | 339500, 400200, 458500 | |
| taxable_la | OFTReal | 5.4k | 28000.0, 28000.0, 43750.0 | |
| taxable_im | OFTReal | 8.1k | 90830.0, 112070.0, 116730.0 | |
| taxable_to | OFTReal | 10.1k | 118830.0, 140070.0, 160480.0 | |
| cauv | OFTInteger | 3.9k | 0, 0, 0 | |
| annualtax | OFTReal | 50.0k | 7286.6, 8589.02, 9840.56 | |
| yrbuilt | OFTInteger | 201 | 1986, 1986, 1985 | |
| yrremod | OFTInteger | 78 | 0, 2016, 2017 | |
| rooms_tot | OFTInteger | 25 | 8, 10, 8 | |
| bdrooms | OFTInteger | 14 | 4, 4, 4 | |
| famrooms | OFTInteger | 8 | 1, 1, 1 | |
| dinrooms | OFTInteger | 5 | 1, 1, 1 | |
| hafbaths | OFTInteger | 7 | 1, 1, 1 | |
| fulbaths | OFTInteger | 12 | 2, 3, 2 | |
| grade | OFTString | 5 | B, B, B | |
| gradeadjs | OFTString | 1 | +, +, + | |
| storyhgt | OFTReal | 18 | 2.0, 2.0, 1.5 | |
| aircond | OFTString | 1 | CENTRAL, CENTRAL, CENTRAL | |
| firepl_sta | OFTInteger | 7 | 1, 1, 1 | |
| heating | OFTString | 1 | BASE, BASE, BASE | |
| sale_date | OFTString | 8.6k | 2021-07-12, 2018-06-20, 2010-05-07 | |
| sale_amnt | OFTInteger | 17.6k | 460000, 465000, 180000 | |
| sqft | OFTInteger | 6.2k | 2360, 2908, 3356 | |
| basement | OFTString | 2 | PART, PART, PART | |
| attic | OFTString | 4 | FULL, 3/4, FULL | |
| school | OFTString | 12 | DUBLIN, DUBLIN, DUBLIN | |
| twp_name | OFTString | 25 | WASHINGTON, WASHINGTON, WASHINGTON | |
| mun_name | OFTString | 10 | DUBLIN, DUBLIN, DUBLIN | |
| shape_leng | OFTReal | 50.0k | 518.207065860025, 454.704798423218, 499.042841977522 | |
| shape_area | OFTReal | 50.0k | 15723.2078663002, 12590.0201266405, 15281.2244586234 |
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.