tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: c3f7244a-a151-4c15-8afd-088b0022fa48
Sheet: Sheet1

electronica 2010 - List of exhibitors | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5
 | Search by product and service index (1 Entry):
 | 1 Semiconductors 1.4 Opto semiconductor components 1.4.9 Photo reproduction equipment
No. | Company | Country | City | [NAME] | Hall/Booth
1 | Hamamatsu Photonics Deutschland GmbH | Germany | Herrsching | 82211 | A2.315
Spreadsheet: 807491d1669916480-vlookup-does-not-accept-value-first-parameter-of-function-excel-mistake
Sheet: Excel Problem

[NAME].St. Titel | Von | Bis | VZÄ | Anteil | TVL | 2022-01-15 00:00:00 | 2022-12-15 00:00:00
Ausleihe | 2022-01-04 00:00:00 | 2022-12-31 00:00:00 | 0.25 | 801.940943125 | E4
Ausleihe | 2022-01-01 00:00:00 | 2022-12-31 00:00:00 | 1 | 3416.821275 | E6
Ausleihe | 2022-01-01 00:00:00 | 2022-12-31 00:00:00 | 0.45 | 1736.953635375 | E9
Retro | 2022-10-04 00:00:00 | 2022-12-31 00:00:00 | 0.125 | 298.35 | WHK
 |  | Ausleihe |  | E2-E8
 |  |  |  | E9-E12
 |  |  |  | E13-E15+
 |  | Hoheitlich |  | E2-E8
 |  |  |  | E9-E12
 |  |  |  | E13-E15
 | E10 | MidInc
 | E9 | MidInc
 | E8 | LowInc
 | E7 | LowInc
 | E6 | LowInc
 | E5 | LowInc
 | E4 | LowInc
 | WHK | [NAME]
Spreadsheet: c40e6d09-d22d-4196-9380-56a8c1901855
Sheet: Sheet1

[NAME] | Unnamed: 1 | Unnamed: 2 | Unnamed: 3
Hensikten med fagfolkdatabasen er at det skal bli enklere for fagpersoner å finne andre                                                                  man kan utveksle kunnskap og erfaringer med.
 | Fyll ut registreringsskjemaet, lagre det på egen PC og send med epost til [EMAIL] eller post [NAME], Sandbakkvn 18, 1404 Siggerud
For Frambu: | [NAME]: |  | Arkiv:
 | [NAME] dato: |  | Slettet:
Registreringsskjema
Fornavn
Etternavn
Diagnose/r                                                                     (kan skrives her eller sett et eller flere kryss nedenefor)
Yrke/profesjon
Annen, relevant informasjon
Arbeidssted
Fylke
Kommune
Telefon arbeid
Ev. mobil
Ev. [NAME] telefon
E-post 1
E-post 2
[NAME] hjemmeside
Dato
Underskrift
Diagnoser (sett kryss) | x
47 XYY
48 XXYY
Adrenoleukodystrofi
Aicardi-Goutières syndrom
Aldringstilstander, premature
Alexanders sykdom
Alpers sykdom
[NAME] fremadskridende nevrologiske sykdommer
Angelmans syndrom
[NAME] syndrom
Cri du chat syndrom
Fragilt X syndrom
Aspartylglukosaminuri
[NAME]
Beckers muskeldystrofi
Beckwith-Wiedemanns syndrom
Cockaynes sykdom
Corpus callosum agenesi
DiGeorges syndrom
Duchennes muskeldystrofi
[NAME]
Emery Dreyfuss muskeldystrofi
Fahrs sykdom
[NAME]
Forstyrrelser i glukosaminoglykanmetabolismen
Friedreichs ataxi
Glutarsyreuri type 1
Hallervorden-Spatz syndrom
Hemiplegi, alternerende
Hereditær spastisk [NAME]
Hvit substans-sykdommer
Infantil nevroaxonal dystrofi
Infantil nevronal ceroid lipofuscinose
Jouberts syndrom
Kallmanns syndrom
Kearn-Sayres syndrom
Kjønnskromosomavvik
Klinefelters syndrom
Klippell-Trenaunays syndrom
Kongenitt muskeldystrofi
Krabbes syndrom
Kromosomavvik, svært sjeldne med utviklingshemning
Leighs sykdom
Lesh-Nyhans syndrom
[NAME] muskeldystrofi
Lysosomale sykdommer
Mannosidose
Marinesco-Sjögrens sykdom
Menkes sykdom
Metakromatisk leukodystrofi
Migrasjonsforstyrrelser
Migrasjonsforstyrrelser i hjernen
Mitokondrie nevrogastrointestinal encefalomyelopati
Mitokondrielle sykdommer
Mitokondriemyopatier
Mukolipidose II og III og Sialidose
Mukopolysakkaridosesykdommer
Möbius’ syndrom
Nevrofibromatose type 1
Nevrofibromatose type 2
Nevromuskulære sykdommer
Noonans syndrom
Ornithine transcarbamylase defiency
Overvekstsyndromer
Pelizaeus-Merzbachers sykdom
Polynevropatier
[NAME] syndrom
Proteus’ syndrom
Retts syndrom
Rubinstein-Taybis syndrom
Sandhoffs sykdom
Seninfantil nevronal ceroid lipofuscinose
Smith-Magenis’ syndrom
Uten kjent diagnose med utviklingshemning
[NAME] syndrom
Sotos’ syndrom
[NAME] sykdom (JNCL)
[NAME] syndrom
Tay-Sachs sykdom
Trippel X syndrom
Turners syndrom
Weavers syndrom
[NAME] syndrom
Spreadsheet: 862341d1710094471-sick-pay-entitlement-based-on-length-of-service-dummy-sickpay-julaboyce-
Sheet: Sheet1

 |  |  |  |  | Startdate | Year service
 |  |  |  |  | 2020-09-07 00:00:00
Name:
Number of working hours | 10
Normal Working days | 5
 |  |  |  |  |  |  | Number of weeks Full Pay | Number of weeks half Pay
End Date of last sickness |  |  |  |  |  | Less Than 6 months service | SSP | SSP | 0
No of Sick Days in  12 month Period |  |  |  |  |  | Less than 1 year servcie | 1 | 1 | 0.5
Number of sick [NAME] |  |  |  |  |  | One to two years' service: | 2 | 2 | 1
 |  |  |  |  |  | Two to three years’ service: | 4 | 4 | 2
 |  |  |  |  |  | Three years service and above | 6 | 6 | 3
First Day of Absence | Last Day of Absence | Number of Days off | Reason for Absence | Days of Week off
2022-06-22 00:00:00 | 2022-06-27 00:00:00 |  |  |  |  | Total Days Entitelment
2022-08-10 00:00:00 | 2022-08-11 00:00:00
2022-11-14 00:00:00 | 2022-11-25 00:00:00
2022-12-28 00:00:00 | 2022-12-30 00:00:00
2023-02-28 00:00:00 | 2023-03-02 00:00:00 |  |  |  |  | Days Entitlement used
2023-05-09 00:00:00 | 2023-05-11 00:00:00
2024-02-27 00:00:00 | 2024-03-01 00:00:00 |  | Fall at home
2024-03-06 00:00:00 | 2024-03-08 00:00:00 |  | swollen/painful foot
Spreadsheet: 65fddd3f-126a-4134-8f44-e02547f24610
Sheet: Sheet1

Test Referenced | Entry Type | Mayo ID | Description | Reporting Description | Method | Collection Container | Temperature | Stability | [NAME] | Unit of Measure | [NAME] | Minimum Volume | Reject Due To | Reference Values | Days/Times Performed | Analytic Time | Maximum Lab Time | CPT Units | CPT Code | LOINC® Code | LOINC® Attributes | Always Performed | Orderable Separately | Performing Location
GD65C | Test | GD65C | Glutamic Acid Decarboxylase (GAD65) Antibody Assay, Spinal Fluid | GAD65 Ab Assay, CSF | Immunoprecipitation Assay | Plastic vial: PlV |  |  | 1 | mL | Container/Tube: Sterile vial [NAME]: 1 mL Forms: If not ordering electronically, submit a General Request Form (Supply T239) with the specimen. | 0.75 mL | Hemolysis	Mild OK; Gross reject Thawing	Warm OK; Cold OK Lipemia	Mild OK; Gross reject Icterus	Mild OK; Gross reject Other	NA | < or =0.02 nmol/L | Monday through Friday;  6 a.m. | 2 days/negative 3 days/positive | 6 days | 1 | 86341 |  |  |  |  | Rochester
GD65C | [NAME] | CSF | CSF |  |  |  | Refrigerated | 14 days
GD65C | Result | 21702 | GAD65 Ab Assay, CSF | GAD65 Ab Assay, CSF | Numeric |  |  |  |  | nmol/L |  |  |  |  |  |  |  |  |  | 53708-4
Spreadsheet: 880472d1728279396-power-query-find-text-in-a-list-in-another-list-allisterb-match-3-spill-365-aligw
Sheet: Sheet1

 |  |  |  |  |  | Customer | Customer Name |  |  |  | Customer | Customer Name
 |  |  |  |  |  | MOH North | Health GH |  |  |  | MOH North | Health GH
 |  |  |  |  |  | Sth MOE New | North Education Supply |  |  |  | Sth MOE New | North Education Supply
 |  |  |  |  |  | Central MO | Central K Health |  |  |  | Central MO | Central K Health
 |  |  |  |  |  | SDM | [NAME] |  |  |  | SDM | [NAME]
 |  |  |  |  |  | Search |  |  |  |  | Search
 |  |  |  |  |  | MOE |  |  |  |  | MOE
 |  |  |  |  |  | MOH |  |  |  |  | MOH
 |  |  |  |  |  | MO |  |  |  |  | MO
 |  |  |  |  |  | Health |  |  |  |  | Health
 |  |  |  |  |  | Supply |  |  |  |  | Supply
 |  |  |  |  |  | Education |  |  |  |  | Education
 |  |  |  |  |  |  |  |  |  |  | Desired Result
 |  |  |  |  |  |  | Customer Name | Found |  |  | Customer | Customer Name | Found
 |  |  |  |  |  | MOH North | Health GH | MOH, Health |  |  | MOH North | Health GH | MOH, Health
 |  |  |  |  |  | Sth MOE New | North Education Supply | MOE, Supply, Education |  |  | Sth MOE New | North Education Supply | MOE, Education, Supply
 |  |  |  |  |  | Central MO | Central K Health | MO, Health |  |  | Central MO | Central K Health | MO, Health
 |  |  |  |  |  | SDM | [NAME] |  |  |  | SDM | [NAME]
Spreadsheet: 169273d1342764867-addidtional-calculation-and-conditional-formating-within-pivot-table-calculation-and-conditional-formating-with-in-the-pivot-table
Sheet: Data

Period | Customer | Sales |  | Pivot table
1.2012 | ABB | 200 |  | Sum of Sales | Period
1.2012 | ABC | 100 |  | Customer | 1.2012 | 2.2012 | 3.2012 | 4.2012 | 5.2012 | 6.2012 | 7.2012 | July Extrapolated | Average | comparison with [NAME] | Grand Total
1.2012 | ABD | 358 |  | ABB | 200 | 243 | 324 | 456 | 345 | 658 | 124 | 181.8666666666667 | 405.2 | 0.4488318525830866 | 2937.51549851925
2.2012 | ABB | 243 |  | ABC | 100 | 276 | 578 | 56 | 567 | 568 | 897 | 1315.6 | 409 | 3.216625916870415 | 4769.816625916871
2.2012 | ABC | 276 |  | ABD | 358 | 456 | 987 | 456 | 45 | 555 | 23 | 33.73333333333333 | 499.8 | 0.0674936641323196 | 3413.600826997465
2.2012 | ABD | 456 |  | ABE |  | 321 | 443 |  |  |  |  | 0 | 152.8 | 0 | 916.8
2.2012 | ABE | 321 |  | Grand Total | 658 | 1296 | 2332 | 968 | 957 | 1781 | 1044 | 1531.2 | 1466.8 | 3.732951433585821 | 12037.73295143359
3.2012 | ABB | 324
3.2012 | ABC | 578 |  | I need to include three columns in the pivot table
3.2012 | ABD | 987
3.2012 | ABE | 443 |  | July Extrapolated |  | Average of Last 5 months (Feb Mar, April,May, June) |  |  |  |  | Comparisson of July Extrapolated with Average
4.2012 | ABB | 456 |  | 181.8666666666667 |  | 405.2 |  |  |  |  | 0.4488318525830866
4.2012 | ABC | 56 |  | 1315.6 |  | 409 |  |  |  |  | 3.216625916870415
4.2012 | ABD | 456 |  | 33.73333333333333 |  | 499.8
5.2012 | ABB | 345
5.2012 | ABC | 567
5.2012 | ABD | 45
6.2012 | ABB | 658
6.2012 | ABC | 568
6.2012 | ABD | 555 |  |  |  |  |  |  |  |  | If [NAME] figures is better than average, colour of cell to be green with % calculation
7.2012 | ABB | 124
7.2012 | ABC | 897 |  | July Data  is not full month data. There are 22 working days in july
7.2012 | ABD | 23 |  | This data is for 15  days in July. So I have to extrapolate it to reflect full month value
 |  |  |  | Not sure if this is the right way to extrapolate. Or can we use a trend analysis formula or something else based on the last 6 months data ??
Spreadsheet: 705661d1606242155-data-comparison-and-aggregation-looking-for-help-copy-template-1-
Sheet: analysis

ID | Acc Num |  |  | Value | totalValue | otherPercentage | otherCharge | My%Charged | MyCharge | MybrandCheaper? |  |  | Aggregated comparison required - total value? | family pricing % | family pricing charge
111 | 1111 |  |  | 1133059.89 | 1133059.89 |  |  |  |  |  |  |  | I need sum of 1133059.89 + 3984.4 + 38657.34 + 445112.3 here (111 and 333 has same postcode in Individuals tab, so taking their values from column F) = 16,20,813.9 | I will use the same formula as in column G3 for the total value in N3 | I will use the same formula as in column H3 for the total value in N3
111 | 1112 |  |  | 3984.4 | 3984.4 |  |  |  |  |  |  |  | I need sum of 1133059.89 + 3984.4 + 38657.34 + 445112.3 here (111 and 333 has same postcode in Individuals tab, so taking their values from column F) = 16,20,813.9
222 | 1113 |  |  | 199959.2 | 199959.2 |  |  |  |  |  |  |  | For ID-222, nothing to be displayed in N6, as I have already done the calculations in column G6 and [NAME] (because there is no other individual ID with this post code)
222 | 1114 |  |  | 716513.7 | 716513.7 |  |  |  |  |  |  |  | For ID-222, nothing to be displayed in N7, as I have already done the calculations in column G7 and H7 (because there is no other individual ID with this post code)
222 | 1115 |  |  | 55676.77 | 55676.77 |  |  |  |  |  |  |  | For ID-222, nothing to be displayed in N8, as I have already done the calculations in column G8 and H8 (because there is no other individual ID with this post code)
333 | 1116 |  |  | 38657.34 | 38657.34 |  |  |  |  |  |  |  | I need sum of 1133059.89 + 3984.4 + 38657.34 + 445112.3 here (111 and 333 has same postcode in Individuals tab, so taking their values from column F) = 16,20,813.9
333 | 1117 |  |  | 445112.3 | 445112.3 |  |  |  |  |  |  |  | I need sum of 1133059.89 + 3984.4 + 38657.34 + 445112.3 here (111 and 333 has same postcode in Individuals tab, so taking their values from column F) = 16,20,813.9
444 | 1118 |  |  | 121 | 121
444 | 1119 |  |  | 157763.62 | 157763.62
555 | 1120 |  |  | 612748.12 | 612748.12
555 | 1121 |  |  | 906128.44 | 906128.44
666 | 1122 |  |  | 5678224.49 | 5678224.49
777 | 1123 |  |  | 456034.94 | 456034.94
777 | 1124 |  |  | 123456.29 | 123456.29
888 | 1125 |  |  | 2509.43 | 2509.43
888 | 1126 |  |  | 75748.43 | 75748.43
888 | 1127 |  |  | 12745.31 | 12745.31
999 | 1128 |  |  | 123461.02 | 123461.02
999 | 1129 |  |  | 509000.2 | 509000.2
1000 | 1130 |  |  | 131575.33 | 131575.33
1000 | 1131 |  |  | 31040.95 | 31040.95
Spreadsheet: 685797d1594203565-cell-formts-in-a-pivot-table-2020-07-08-oeldere-rider2-685739d1594163835-cell-formts-in-a-pivot-table-kitting-tracking-r2
Sheet: Report

Production Report - Finishing |  |  |  |  |  |  |  | Printed
Job No. |  | Date | [NAME] | Som van SUPERVISOR TOTAL HRS. | Som van TOTAL TEMP HOURS | TOTAL | Sum of Qty. Produced | Sum of Qty. | Average of 1st Pass Yield
123456 | Smith Co | 2020-06-05 00:00:00 | Evie | 5 | 20 | 25 | 5000 | 4995 | 0.999
 |  | 2020-06-06 00:00:00 | Evie | 9 | 32.5 | 41.5 | 3000 | 2999 | 0.9996666666666667 |  |  | I created a basic pivot table (Report) to track hours on projects. I get the correct information but it will not stay formatted. I checked the box "Preserve Cell Formatting on Update" in the pivot table Options.
 |  | 2020-06-07 00:00:00 | Evie | 0 | 12 | 12 | 3000 | 2950 | 0.9833333333333333
 |  | 2020-06-16 00:00:00 | Evie | 10.5 | 31.5 | 42 | 3500 | 3490 | 0.9971428571428571 |  |  | I supplied a copy of the file. Look at the report tab:
 |  | 2020-06-17 00:00:00 | Evie | 10.5 | 42 | 52.5 | 500 | 500 | 1 |  |  | 1) Position in the cell - I center the info but as soon as I update it it looses the position i selected.
 |  | 2020-06-17 00:00:00 | [NAME] | 10.5 | 52.5 | 63 | 1200 | 1198 | 0.9983333333333333 |  |  | 2) Columns E and F, I want all numbers to show 2 decimal places. I set it in the cell formats but it does not hold in an update.
 |  | 2020-06-18 00:00:00 | [NAME] | 10.5 | 42 | 52.5 | 1500 | 1495 | 0.9966666666666667
 |  | 2020-06-19 00:00:00 | [NAME] | 10.5 | 42 | 52.5 | 2000 | 1995 | 0.9975
 |  | 2020-06-20 00:00:00 | [NAME] | 10.5 | 31.5 | 42 | 1500 | 1499 | 0.9993333333333333
 |  | 2020-06-21 00:00:00 | Evie | 9.5 | 47.5 | 57 | 1200 | 1198 | 0.9983333333333333
 |  | 2020-06-22 00:00:00 | [NAME] | 10.5 | 63 | 73.5 | 1100 | 1100 | 1
 |  | 2020-06-23 00:00:00 | [NAME] | 8.499999999999998 | 33.99999999999999 | 42.49999999999999 | 1300 | 1300 | 1
 |  | 2020-06-24 00:00:00 | Evie | 10.5 | 52.5 | 63 | 900 | 880 | 0.9777777777777777
 |  | 2020-06-25 00:00:00 | [NAME] | 10.5 | 42 | 52.5 | 1600 | 1598 | 0.99875
Totaal 123456 |  |  |  | 126.5 | 545 | 671.5 | 27300 | 27197 | 0.9961312358276643
456789 | Bobs Co | 2020-06-05 00:00:00 | [NAME] | 7.5 | 1.000000000000002 | 8.500000000000002 | 2500 | 2500 | 1
 |  | 2020-06-06 00:00:00 | [NAME] | 8.499999999999998 | 55.24999999999999 | 63.74999999999999 | 2400 | 2400 | 1
Totaal 456789 |  |  |  | 16 | 56.24999999999999 | 72.24999999999999 | 4900 | 4900 | 1
987654 | [NAME] | 2020-06-10 00:00:00 | Evie | 10 | 50 | 60 | 3000 | 3000 | 1
 |  | 2020-06-11 00:00:00 | Evie | 4.000000000000002 | 32.00000000000001 | 36.00000000000001 | 10000 | 7500 | 0.75
 |  | 2020-06-12 00:00:00 | [NAME] | 9 | 76.5 | 85.5 | 5000 | 4500 | 0.9
 |  | 2020-06-13 00:00:00 | [NAME] | 8.75 | 65.625 | 74.375 | 6000 | 5600 | 0.9333333333333333
 |  | 2020-06-14 00:00:00 | Evie | 10 | 95 | 105 | 2500 | 2450 | 0.98
 |  | 2020-06-15 00:00:00 | Evie | 10.5 | 78.75 | 89.25 | 2500 | 2500 | 1
Totaal 987654 |  |  |  | 52.25 | 397.875 | 450.125 | 29000 | 25550 | 0.9272222222222221
Eindtotaal |  |  |  | 194.75 | 999.125 | 1193.875 | 61200 | 57647 | 0.9776895743145743
Spreadsheet: 65469d1266188555-pivot-percentage-of-subtotal-and-total-budget
Sheet: SUMMARY

[NAME] | AMOUNT | DATE | % of Description |  | [NAME] | AMOUNT | DATE | % of Description |  | [NAME] | AMOUNT | DATE | % of Description
INCOMEA | 1500 | 2010-01-05 00:00:00 |  |  | ELECTRIC | 114 | 2010-01-14 00:00:00 |  |  | GROCERY | 100 | 2010-01-02 00:00:00
INCOMEA | 1400 | 2010-01-10 00:00:00 |  |  | WATER | 50 | 2010-01-15 00:00:00 |  |  | FASTFOOD | 7 | 2010-01-05 00:00:00
INCOMEB | 800 | 2010-01-17 00:00:00 |  |  | WATER | 58 | 2010-01-17 00:00:00 |  |  | FASTFOOD | 15 | 2010-01-07 00:00:00
INCOMEC | 450 | 2010-01-25 00:00:00 |  |  | CABLE | 33 | 2010-01-20 00:00:00 |  |  | CLEANERS | 23 | 2010-01-26 00:00:00
INCOMEA | 1400 | 2010-02-05 00:00:00 |  |  | ELECTRIC | 115 | 2010-02-13 00:00:00 |  |  | GROCERY | 115 | 2010-02-13 00:00:00
INCOMEB | 1500 | 2010-02-11 00:00:00 |  |  | WATER | 60 | 2010-02-14 00:00:00 |  |  | FUEL | 8 | 2010-02-14 00:00:00
INCOMEB | 700 | 2010-02-15 00:00:00 |  |  | GAS | 57 | 2010-02-16 00:00:00 |  |  | FUEL | 20 | 2010-02-17 00:00:00
INCOMEC | 350 | 2010-02-22 00:00:00 |  |  | GAS | 30 | 2010-02-21 00:00:00 |  |  | CLEANERS | 25 | 2010-02-20 00:00:00
Row Labels | Sum of AMOUNT | Sum of % of Description
INCOMEA | 4300 | 1
2010-01-05 00:00:00 | 1500 | 0.3488372093023256
2010-01-10 00:00:00 | 1400 | 0.3255813953488372
2010-02-05 00:00:00 | 1400 | 0.3255813953488372
INCOMEB | 3000 | 1
2010-01-17 00:00:00 | 800 | 0.2666666666666667
2010-02-11 00:00:00 | 1500 | 0.5
2010-02-15 00:00:00 | 700 | 0.2333333333333333
INCOMEC | 800 | 1
2010-01-25 00:00:00 | 450 | 0.5625
2010-02-22 00:00:00 | 350 | 0.4375
Grand Total | 8100 | 3
Spreadsheet: 145875d1331790808-transfer-data-from-one-sheet-to-another-when-specific-value-entered-in-first-sheet-example_2012_file
Sheet: Invoice

Address
Address |  |  |  |  | INVOICE # |  |  | 123456
Phone |  |  |  |  | DATE:
TO:
JOB REC. | JOB COMP. | JOB DESC. | WITNESS NAME | PAGES COMP. | JOB TYPE | RATE |  | AMOUNT
2012-11-30 00:00:00 | 2012-12-01 00:00:00 | 113012-01 | Hones, [NAME] | 114 | Regular | 0.85
2012-12-01 00:00:00 | 2012-12-02 00:00:00 | 121012-01 | [NAME], [NAME] | 60 | Regular | 0.85
2012-12-04 00:00:00 | 2012-12-05 00:00:00 | 121012-04 | Blake, [NAME] | 14 | Daily | 3
 |  |  |  |  |  | TOTAL
Spreadsheet: 696881d1601022645-counting-three-columns-whilst-ignoring-duplicates-in-one-of-the-columns-book1
Sheet: Values

Division | Computername | Operating System | User |  | Division | Operating System | Sum1 | Sum2 | Sum3
Business Unit 1 | Workstation 1 | Microsoft Windows 10 Enterprise | User 2 |  | Business Unit 1 | Microsoft Windows 10 Enterprise
Business Unit 1 | Workstation 1 | Microsoft Windows 10 Enterprise | User 2 |  | Business Unit 1 | Microsoft Windows 10 Pro
Business Unit 1 | Workstation 1 | Microsoft Windows 10 Enterprise | User 3 |  | Business Unit 2 | Microsoft Windows 10 Enterprise
Business Unit 1 | Workstation 2 | Microsoft Windows 10 Pro | User 1 |  | Business Unit 2 | Microsoft Windows 10 Pro
Business Unit 1 | Workstation 2 | Microsoft Windows 10 Pro | User 2 |  | Business Unit 3 | Microsoft Windows 10 Enterprise
Business Unit 1 | Workstation 2 | Microsoft Windows 10 Pro | User 3 |  | Business Unit 3 | Microsoft Windows 10 Pro
Business Unit 1 | Workstation 2 | Microsoft Windows 10 Pro | User 4
Business Unit 1 | Workstation 3 | Microsoft Windows 10 Enterprise | User 1
Business Unit 1 | Workstation 3 | Microsoft Windows 10 Enterprise | User 2
Business Unit 1 | Workstation 4 | Microsoft Windows 10 Pro | User 1
Business Unit 1 | Workstation 4 | Microsoft Windows 10 Pro | User 2
Business Unit 1 | Workstation 4 | Microsoft Windows 10 Pro | User 3
Business Unit 1 | Workstation 5 | Microsoft Windows 10 Pro | User 1
Business Unit 2 | Workstation 1 | Microsoft Windows 10 Pro | User 1
Business Unit 2 | Workstation 1 | Microsoft Windows 10 Pro | User 2
Business Unit 2 | Workstation 1 | Microsoft Windows 10 Pro | User 3
Business Unit 2 | Workstation 2 | Microsoft Windows 10 Enterprise | User 1
Business Unit 2 | Workstation 2 | Microsoft Windows 10 Enterprise | User 2
Business Unit 2 | Workstation 2 | Microsoft Windows 10 Enterprise | User 3
Business Unit 2 | Workstation 2 | Microsoft Windows 10 Enterprise | User 4
Business Unit 2 | Workstation 3 | Microsoft Windows 10 Pro | User 1
Business Unit 2 | Workstation 3 | Microsoft Windows 10 Pro | User 2
Business Unit 2 | Workstation 4 | Microsoft Windows 10 Enterprise | User 1
Business Unit 2 | Workstation 4 | Microsoft Windows 10 Enterprise | User 2
Business Unit 2 | Workstation 4 | Microsoft Windows 10 Enterprise | User 3
Business Unit 3 | Workstation 1 | Microsoft Windows 10 Pro | User 1
Business Unit 3 | Workstation 1 | Microsoft Windows 10 Pro | User 2
Business Unit 3 | Workstation 1 | Microsoft Windows 10 Pro | User 3
Business Unit 3 | Workstation 2 | Microsoft Windows 10 Enterprise | User 1
Spreadsheet: 267866d1380255240-use-selections-from-two-data-validation-lists-to-lookup-and-return-a-mailing-address-state-county-fips-codes
Sheet: MONTANA-25

 | COUNTY | CODE
 | Beaverhead | 1
 | Big Horn
 | Blaine
 | Broadwater
 | Carbon
 | [NAME]
 | Cascade
 | [NAME]
 | Custer
 | Daniels
 | Dawson
 | [NAME]
 | Fallon
 | Fergus
 | Flathead
 | [NAME]
 | [NAME]
 | Glacier
 | Golden Valley
 | Granite
 | Hill
 | [NAME]
 | [NAME]
 | Lake
 | Lewis & Clark
 | Liberty
 | Lincoln
 | McCone
 | [NAME]
 | Meagher
 | Mineral
 | Missoula
 | Musselshell
 | Park
 | Petroleum
 | Phillips
 | Pondera
 | Powder River
 | [NAME]
 | Prairie
 | [NAME]
 | Richland
 | Roosevelt
 | Rosebud
 | Sanders
 | [NAME]
 | Silver Bow
 | Stillwater
 | [NAME]
 | Teton
 | Toole
 | Treasure
 | Valley
 | Wheatland
 | Wibaux
 | Yellowstone
Spreadsheet: 887585d1737825155-generating-1-column-of-data-into-a-calendar-reviews-calendar-test_3
Sheet: Apr

 |  |  | 2025-03-31 00:00:00 | 2025-04-01 00:00:00 | 2025-04-02 00:00:00 | 2025-04-03 00:00:00 | 2025-04-04 00:00:00 | 2025-04-05 00:00:00
 |  |  | 2025-04-07 00:00:00 | 2025-04-08 00:00:00 | 2025-04-09 00:00:00 | 2025-04-10 00:00:00 | 2025-04-11 00:00:00 | 2025-04-12 00:00:00
 |  |  | 2025-04-14 00:00:00 | 2025-04-15 00:00:00 | 2025-04-16 00:00:00 | 2025-04-17 00:00:00 | 2025-04-18 00:00:00 | 2025-04-19 00:00:00
 |  |  | 2025-04-21 00:00:00 | 2025-04-22 00:00:00 | 2025-04-23 00:00:00 | 2025-04-24 00:00:00 | 2025-04-25 00:00:00 | 2025-04-26 00:00:00
 |  |  | 2025-04-28 00:00:00 | 2025-04-29 00:00:00 | 2025-04-30 00:00:00 | 2025-05-01 00:00:00 | 2025-05-02 00:00:00 | 2025-05-03 00:00:00
 |  |  | 2025-05-05 00:00:00 | Notes