Hello,
I am trying to find a formula to find same first three digits of zibCode in a big data column. return value to be "1" or "0".
example:
zibcode
59527
59528
59523
59505
80120
80133
80122
Thank you for your help.
Solved! Go to Solution.
You can use left([zibcode], 3) to extract the first 3 digits and use that to compare. I can help you further with a workflow if you provide further detail and an example of what you expect the output to look like.
Hi,
I have attached a sample of my data sheet.
ZipCode | State | City | Population | SquareMiles |
59001 | Montana | Absarokee | 1,566 | 135.7 |
59002 | Montana | Acton | 63 | 15.3 |
59003 | Montana | Ashland | 1,023 | 316.7 |
59006 | Montana | Ballantine | 865 | 67.8 |
59007 | Montana | Bearcreek | 120 | 59.1 |
59008 | Montana | Belfry | 374 | 85.0 |
59010 | Montana | Bighorn | 185 | 513.9 |
59011 | Montana | Big Timber | 3,014 | 1050.2 |
59012 | Montana | Birney | 170 | 236.1 |
59013 | Montana | Boyd | 203 | 30.8 |
59014 | Montana | Bridger | 1,474 | 842.3 |
59015 | Montana | Broadview | 488 | 338.9 |
59016 | Montana | Busby | 936 | 497.9 |
59018 | Montana | Clyde Park | 408 | 104.9 |
59019 | Montana | Columbus | 3,347 | 290.5 |
59020 | Montana | Cooke City | 112 | 103.7 |
59022 | Montana | Crow Agency | 2,290 | 591.7 |
59024 | Montana | Custer | 348 | 511.8 |
59025 | Montana | Decker | 96 | 533.3 |
59026 | Montana | Edgar | 193 | 47.0 |
59027 | Montana | Emigrant | 372 | 127.8 |
59028 | Montana | Fishtail | 518 | 340.8 |
59029 | Montana | Fromberg | 770 | 33.7 |
59030 | Montana | Gardiner | 1,792 | 1086.1 |
59031 | Montana | Garryowen | 296 | 40.7 |
59032 | Montana | Grass Range | 391 | 387.1 |
59033 | Montana | Greycliff | 121 | 29.9 |
59034 | Montana | Hardin | 4,726 | 847.0 |
59035 | Montana | Yellowtail | 326 | 479.4 |
59036 | Montana | Harlowton | 1,630 | 711.8 |
59037 | Montana | Huntley | 1,554 | 193.5 |
59038 | Montana | Hysham | 720 | 774.2 |
59039 | Montana | Ingomar | 121 | 864.3 |
59041 | Montana | Joliet | 1,748 | 154.1 |
59043 | Montana | Lame Deer | 2,908 | 370.4 |
59044 | Montana | Laurel | 9,618 | 186.0 |
59046 | Montana | Lavina | 408 | 600.0 |
59047 | Montana | Livingston | 12,103 | 854.1 |
59050 | Montana | Lodge Grass | 1,731 | 562.0 |
59052 | Montana | Mc Leod | 199 | 537.8 |
59053 | Montana | Martinsdale | 378 | 771.4 |
59054 | Montana | Melstone | 282 | 258.7 |
59055 | Montana | Melville | 142 | 211.9 |
59057 | Montana | Molt | 442 | 300.7 |
59058 | Montana | Mosby | 40 | 307.7 |
59059 | Montana | Musselshell | 164 | 213.0 |
59061 | Montana | Nye | 305 | 160.5 |
59062 | Montana | Otter | 79 | 395.0 |
59063 | Montana | Park City | 1,704 | 98.4 |
59064 | Montana | Pompeys Pillar | 215 | 179.2 |
59065 | Montana | Pray | 88 | 16.0 |
59066 | Montana | Pryor | 713 | 373.3 |
59067 | Montana | Rapelje | 221 | 345.3 |
59068 | Montana | Red Lodge | 3,498 | 622.4 |
59069 | Montana | Reed Point | 463 | 208.6 |
59070 | Montana | Roberts | 758 | 91.4 |
59071 | Montana | Roscoe | 106 | 67.1 |
59072 | Montana | Roundup | 4,032 | 1376.1 |
59074 | Montana | Ryegate | 604 | 511.9 |
59075 | Montana | Saint Xavier | 255 | 303.6 |
59076 | Montana | Sanders | 47 | 11.3 |
59077 | Montana | Sand Springs | 83 | 592.9 |
59078 | Montana | Shawmut | 148 | 255.2 |
59079 | Montana | Shepherd | 3,059 | 242.6 |
59081 | Montana | Silver Gate | 26 | 2.1 |
59085 | Montana | Two Dot | 76 | 304.0 |
59086 | Montana | Wilsall | 757 | 411.4 |
59087 | Montana | Winnett | 493 | 1700.0 |
59088 | Montana | Worden | 1,203 | 333.2 |
59089 | Montana | Wyola | 491 | 306.9 |
59101 | Montana | Billings | 36,335 | 498.8 |
59102 | Montana | Billings | 44,391 | 15.1 |
59105 | Montana | Billings | 23,343 | 103.5 |
59106 | Montana | Billings | 8,009 | 126.9 |
59201 | Montana | Wolf Point | 5,027 | 1416.1 |
59211 | Montana | Antelope | 174 | 122.5 |
59212 | Montana | Bainville | 310 | 233.1 |
59213 | Montana | Brockton | 855 | 527.8 |
Requirement:
For this case, rural is defined as an area with less than 100,000 people. To simplify this analysis, areas are defined as having the same first three digits of the ZIP code.
User | Count |
---|---|
19 | |
15 | |
15 | |
9 | |
8 |