tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: e3558ff5-83a9-417b-a446-e8abf9271ae7
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
PALB | Test | PALB | Prealbumin (PAB), Serum | Prealbumin (PAB), S | Nephelometry | Serum Gel Tube: SGT |  |  | 1 | mL | Container/Tube:  Preferred: Serum gel Acceptable: Red top [NAME]: 1 mL Additional Information: This is an immunologic protein measurement. For thyroxine-binding measurement of prealbumin, see TBPE/8838 Thyroxine-Binding Protein Electrophoresis, Serum. | 0.5 mL | Hemolysis	Mild OK; Gross OK Thawing	Warm OK; Cold OK Lipemia	Mild OK; Gross reject Icterus	Mild OK; [NAME] OK Other	NA | 19-38 mg/dL | Monday through Saturday; Continuously until 3 p.m. | 1 day | 2 days | 1 | 84134 |  |  |  |  | Rochester
PALB | [NAME] | SERUM | Serum |  |  |  | Refrigerated | 14 days
PALB | Result | PALB | Prealbumin (PAB), S | Prealbumin (PAB), S | Numeric |  |  |  |  | mg/dL |  |  |  |  |  |  |  |  |  | 46130-1
Spreadsheet: 193884d1352982550-instant-search-in-excel-2007-search-and-filter
Sheet: Sheet1

 | Search...
 |  | Tour Operators (TO)
 | Hotels | TO1 | TO2 | TO3 | TO4 | TO5 | TO6 | TO7 | TO8 | TO9
 | Hotel1 | x |  | x |  |  | x |  | x
 | Hotel2 |  | x |  | x | x |  | x
 | Hotel3 |  | x |  |  | x |  |  |  | x
 | Hotel4 | x |  | x |  |  | x |  | x
 | Hotel5 | x |  | x |  | x |  |  | x
 | Hotel6 |  | x |  | x |  |  | x
 | Hotel7 |  |  | x |  | x | x |  | x | x
 | Hotel8 | x |  |  |  |  |  | x
 | Hotel9 |  | x | x | x | x |  | x | x
 | Hotel10 |  |  |  |  |  |  |  |  | x
 | Hotel11 |  | x |  | x |  | x |  |  | x
 | Hotel12 | x |  | x |  | x |  | x | x
 | Hotel13 |  | x | x | x |  | x |  | x
 | Hotel14 |  |  |  |  | x
 | Hotel15 | x | x | x | x |  |  | x | x | x
 | Hotel16 |  | x |  | x |  | x
 | Hotel17 | x |  | x |  | x |  | x | x
Spreadsheet: 299438d1393189576-how-to-merge-2-different-excel-sheets-into-one-file-2
Sheet: Sheet1

[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
[EMAIL]
Spreadsheet: 044a937a-1d3f-4aed-996b-fb907e9eb5ef
Sheet: Table II.3

Table II.3 الجدول
Fisheries Trade contribution to GDP
مساهمة تجارة مصائد الأسماك في الناتج المحلي الإجمالي
 | Year | GDP | Total fish imports (thousand USD)b/ | Total fish exports (thousand USD)b/ | Imports out of GDP (%)c/ | Exports out of GDP (%)c/
 | السنة | (Million USD)a/, 1 | مجموع واردات الأسماك (ألف دولار أمريكي) | مجموع صادرات الأسماك (ألف دولار أمريكي) | نسبة واردات الأسماك من الناتج [NAME] (بالنسبة المئوية) | نسبة صادرات الأسماك من الناتج [NAME] (بالنسبة المئوية)
 |  | الناتج [NAME] (مليون دولار أمريكي)
Bahrain | 2006 | 11491 | 6620 | 12640 | 0.0006 | 0.0011 | البحرين
 | 2007 | 12454 | 6590 | 16070 | 0.0005 | 0.0013
 | 2008 | 13241 | 6590 | 16070 | 0.0005 | 0.0012
Egypt | 2006 | 126688 | 156920 | 3360 | 0.0012 | - | مصر
 | 2007 | 135772 | 166640 | 4470 | 0.0012 | -
 | 2008 | 142113 | 166640 | 11240 | 0.0012 | 0.0001
Iraq | 2006 | 19226 | ... | ... | ... | ... | العراق
 | 2007 | 19514 | ... | ... | ... | ...
 | 2008 | 21368 | ... | ... | ... | ...
Jordan | 2006 | 11234 | 47170 | 10 | 0.0042 | - | الأردن
 | 2007 | 12187 | 53860 | 790 | 0.0044 | 0.0001
 | 2008 | 13114 | 77360 | 4940 | 0.0059 | 0.0004
Kuwait | 2006 | 58609 | 18920 | 2990 | 0.0003 | 0.0001 | الكويت
 | 2007 | 61166 | 18920 | 2990 | 0.0003 | -
 | 2008 | 65078 | 18920 | 2990 | 0.0003 | -
Lebanon | 2006 | 20915 | 37410 | 460 | 0.0018 | - | لبنان
 | 2007 | 22484 | 37410 | 460 | 0.0017 | -
 | 2008 | 24575 | 37410 | 460 | 0.0015 | -
Oman | 2006 | 23836 | 17950 | 183030 | 0.0008 | 0.0077 | عمان
 | 2007 | 25439 | 21490 | 152170 | 0.0008 | 0.006
 | 2008 | 28706 | 25780 | 156610 | 0.0009 | 0.0055
Palestine | 2006 | 4400 | 9960 | 180 | 0.0023 | - | فلسطين
 | 2007 | 4636 | 9960 | 180 | 0.0021 | -
 | 2008 | 4908 | 9960 | 180 | 0.002 | -
Qatar | 2006 | 29270 | 16220 | 12740 | 0.0006 | 0.0004 | قطر
 | 2007 | 37101 | 23760 | 10490 | 0.0006 | 0.0003
 | 2008 | 46534 | 23760 | 11690 | 0.0005 | 0.0003
Saudi Arabia | 2006 | 234423 | 135000 | 47100 | 0.0006 | 0.0002 | المملكة العربية السعودية
 | 2007 | 239152 | 135000 | 60400 | 0.0006 | 0.0003
 | 2008 | 249265 | 135000 | 60400 | 0.0005 | 0.0002
The Sudan | 2006 | 18265 | 2920 | 830 | 0.0002 | - | السودان
 | 2007 | 20009 | 2620 | 830 | 0.0001 | -
 | 2008 | 21566 | 4500 | 830 | 0.0002 | -
Syrian Arab Republic | 2006 | 26272 | 35620 | 80 | 0.0014 | - | الجمهورية العربية السورية
 | 2007 | 27763 | 37840 | 130 | 0.0014 | -
 | 2008 | 29006 | 39170 | 130 | 0.0014 | -
United Arab Emirates | 2006 | 119683 | 181860 | 31510 | 0.0015 | 0.0003 | الإمارات العربية المتحدة
 | 2007 | 126978 | 220280 | 37150 | 0.0017 | 0.0003
 | 2008 | 136315 | 220280 | 37150 | 0.0016 | 0.0003
Yemen | 2006 | 12882 | 8670 | 257630 | 0.0007 | 0.02 | اليمن
 | 2007 | 13485 | 9890 | 216050 | 0.0007 | 0.016
 | 2008 | 14093 | 9820 | 227930 | 0.0007 | 0.0162
Sources: | a/ | National Accounts Studies of the ESCWA Region, Bulletin No. 30, United Nations, New York, 2010.
 | [NAME] | Arab Agricultural Statistics Yearbook, Arab Organization for Agricultural Development, Volume 29, 2009.
 | c/ | ESCWA calculation
Note: | 1 | Gross Domestic Product refer to GDP at constant prices and base year 2000.
Spreadsheet: 463086d1464289309-old-newby-needs-help-test-1-format-dart-scorer
Sheet: Sheet1

 | TEAM A | VS |  | TEAM B
1 | name 1 | W | 9 | name 9 | L
2 | name 2 |  | 10 | name 10
3 | name3 |  | 11
4 | name4 |  | 12
5 |  |  | 13
6 |  |  | 14
7 |  |  | 15
8 |  |  | 16
 | 1 |  |  | 0
 | 1
Spreadsheet: 840990d1693243664-copying-only-certain-items-to-separate-sheet-based-on-if-formula-master-2
Sheet: Master Attractions

 | 2023-08-26 00:00:00 | Date
Time | Party Name | Room | Host | Drinks | Food | Quanity | Game Cards/Attractions | Party Add-Ons
13:00:00 | Test Party | Center | [NAME] | Coke/Sp/LM | Cheese Pizza | 5 | $10 Game Card | wristbands
 |  |  |  |  | Pepperoni Pizza | 5 | 2 Hours Attractions
 |  |  |  |  | Taco Bar | 25
14:00:00 | Second Party | 3 | [NAME] | S/F/FP | Cookies | 30
 |  |  |  |  | Chips | 30
Spreadsheet: 775552d1649175854-conditional-formatting-to-highlight-dates-which-are-false-best-llnings-mall-med-formler-
Sheet: Sheet1

Beställnings nr. | Beställare | Namn | Beställning |  |  | [NAME] | Beställning |  |  | [NAME] | Beställningsdatum | Leveransdatum | Mängd | [NAME]
[NAME] |  | Tobias jansson | 2 | N | White | 35 | 2 | K | Yellow | 40 | 2010-07-20 00:00:00
 |  | [NAME] | 5 | N | Blue | 30 | 3 | K | Red | 40
 |  | [NAME] | 4 | N | Black | 40 | 1 | K | White | 45
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Products
Summa: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | N = needle
K-002 |  | [NAME] | 3 | N | Black | 45 | 3 | K | Red | 60 | 2020-02-14 00:00:00 |  |  |  |  |  | K = clamp
 |  | [NAME] | 2 | N | Black | 40 | 4 | K | Red | 60
 |  | [NAME] | 5 | N | Blue | 45 | 1 | K | Green | 40
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | FALSE | TRUE
Summa: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | [NAME] | G3 | G2
K-003 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | G4 | K2
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | K4 | K3
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | K-002 | G9 | K10
Summa:
K-004 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | Dates | Price N | Price K
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2000-01-01 00:00:00 | 30 | 35
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2005-03-01 00:00:00 | 35 | 40
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2010-08-20 00:00:00 | 40 | 55
 |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | 2020-01-15 00:00:00 | 45 | 60
Summa:
[NAME]
Summa:
K-006
Summa:
K-007
Summa:
K-008
Summa:
K-009
Summa:
K-010
Summa:
K-011
Summa:
K-012
Summa:
K-013
Summa:
K-014
Summa:
K-015
Summa:
K-016
Summa:
K-017
Summa:
K-018
Summa:
K-019
Summa:
K-020
Summa:
K-021
Summa:
K-022
Summa:
K-023
Summa:
K-024
Summa:
K-025
Summa:
K-026
Summa:
K-027
Summa:
K-028
Summa:
K-029
Summa:
[NAME]
Summa:
K-031
Summa:
K-032
Summa:
K-033
Summa:
K-034
Summa:
K-035
Summa:
K-036
Summa:
[NAME]
Summa:
K-038
Summa:
K-039
Summa:
K-040
Summa:
K-041
Summa:
K-042
Summa:
K-043
Summa:
K-044
Summa:
K-045
Summa:
[NAME]
Summa:
K-047
Summa:
K-048
Summa:
K-049
Summa:
[NAME]
Summa:
K-051
Summa:
[NAME]
Summa:
K-053
Summa:
K-054
Summa:
[NAME]
Summa:
[NAME]
Summa:
K-057
Summa:
K-058
Summa:
K-059
Summa:
K-060
Summa:
Spreadsheet: 14a6a830-835b-4a81-9440-3389ef828f66
Sheet: 7

 | Oct 26 | Nov 2 | Nov 9 | Nov 16 | Nov 23
Total Interest Rates* | N/A*** | N/A | N/A | N/A | N/A
Cleared** | N/A | N/A | N/A | N/A | N/A
Uncleared | N/A | N/A | N/A | N/A | N/A
Total Cross-Currency | N/A | N/A | N/A | N/A | N/A
Cleared | N/A | N/A | N/A | N/A | N/A
Uncleared | N/A | N/A | N/A | N/A | N/A
Total Credit | N/A | N/A | N/A | N/A | N/A
Cleared | N/A | N/A | N/A | N/A | N/A
Uncleared | N/A | N/A | N/A | N/A | N/A
Total Equities | N/A | N/A | N/A | N/A | N/A
Cleared | N/A | N/A | N/A | N/A | N/A
Uncleared | N/A | N/A | N/A | N/A | N/A
Total Commodities | N/A | N/A | N/A | N/A | N/A
Cleared | N/A | N/A | N/A | N/A | N/A
Uncleared | N/A | N/A | N/A | N/A | N/A
TOTAL | N/A | N/A | N/A | N/A | N/A
Weekly total, estimated swap dollar volumes by asset class and cleared status (value of all trades in millions of USD), all products, tenors, and participant types.
Estimates of weekly event volumes are derived from data published in the 2012 ISDA Operations Benchmarking Survey, which defines an "event" as a new trade, confirmable amendment, partial or full termination, increase, decrease, or novation.
*See Data Dictionary for asset class descriptions.
**See Explanatory Notes for cleared and uncleared descriptions.
***N/A indicates that data are not currently available.
The Commission requests feedback on the format and content of this CFTC Swaps Report table. Submit comments to [EMAIL].
Spreadsheet: sally_beck__33712__Metrics 0623
Sheet: Chairman

E N R O N   N O R T H   A M E R I C A - H O T  L I S T  M E T R I C S |  |  |  |  |  |  |  |  |  |  |  |  | Team: | Office of the Chairman
Results based on Activity through June 23, 2000 |  |  |  |  |  |  |  |  |  |  |  |  | Week | 12
 |  | Weekly Summary - 2Q00 through 1Q01
 |  | # of Transactions
 |  | Week 1 | Week 2 | Week 3 | Week 4 | Week 5 | Week 6 | Week 7 | Week 8 | Week 9 | Week 10 | Week 11 | Week 12 | Week 13
 |  | 2000-04-07 00:00:00 | 2000-04-14 00:00:00 | 2000-04-21 00:00:00 | 2000-04-28 00:00:00 | 2000-05-05 00:00:00 | 2000-05-12 00:00:00 | 2000-05-19 00:00:00 | 2000-05-26 00:00:00 | 2000-06-02 00:00:00 | 2000-06-09 00:00:00 | 2000-06-16 00:00:00 | 2000-06-23 00:00:00 | 2000-06-30 00:00:00
Postings Rollforward:
Beginning |  | 0
+ Entrances |  | 0 | 0 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0
- Exits |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0
- Executions |  | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
Ending
 | Dollar Value of Transactions
 | Week 1 | Week 2 | Week 3 | Week 4 | Week 5 |  | Week 6 | Week 7 | Week 8 | Week 9 | Week 10 | Week 11 | Week 12 | Average
Postings Rollforward:
Beginning |  | 100.5
+ Entrances |  | 0 | 14.3 | 1
- Exits |  | 0 | 0 | 0
+/- [NAME] |  | 0 | 0 | -13
- Executions |  | 0 | 0 | 0
Ending
Average Deal Size
 |  |  |  |  |  |  |  | Forward Quarters
 | Actual |  |  | Current Quarter |  | Per |  |  |  |  |  |  |  | Total Year
 | 1Q00 |  |  | 2Q00 |  | Hot List |  | 3Q00 |  |  | 4Q00 |  |  | 2000 |  |  | 1Q01
 | # | $ |  | # | $ |  |  | # | $ |  | # | $ |  | # | $ |  | # | $
Executions | 0 | 0 |  | 0 | 0 |  |  | 0 | 0 |  | 0 | 0 |  |  |  |  | 0 | 0
DPR/MPR |  | 0 |  |  | -18.812 |  |  |  | 0 |  |  | 0 |  |  |  |  |  | 0
Postings | 0 | 0 |  | 0 | 0 |  |  | 1 | 30 |  | 0 | 0 |  |  |  |  | 0 | 0
Identified Margin
Budget |  | 0 |  |  |  |  |  |  | 23.4 |  |  | 23.4 |  |  |  |  |  | 0.01
$ Coverage | 0
$ millions
Spreadsheet: 766628d1643973494-calculate-up-to-this-day-sum-sheets-v2
Sheet: Sales

Date | EMPLOYEE | SALES
2022-01-01 00:00:00 | Yoan | 100
2022-01-01 00:00:00 | Yola | 125
2022-01-01 00:00:00 | Smith | 150
2022-01-01 00:00:00 | [NAME] | 175
2022-01-02 00:00:00 | Yoan | 25
2022-01-02 00:00:00 | Yola | 50
2022-01-02 00:00:00 | Smith | 75
2022-01-02 00:00:00 | [NAME] | 80
2022-01-03 00:00:00 | Yoan | 50
2022-01-03 00:00:00 | Yola | 100
2022-01-03 00:00:00 | Smith | 150
2022-01-03 00:00:00 | [NAME] | 200
2022-01-31 00:00:00 | Smith | 250
2022-01-31 00:00:00 | [NAME] | 300
Spreadsheet: 30187d1225542489-automation-of-variables-xls
Sheet: Photocentres

Flight_Line | Easting | Northing
1 | 287307.6 | 87000
1 | 287653.8 | 87000
1 | 288000 | 87000
1 | 288346.2 | 87000
1 | 288692.4 | 87000
1 | 289038.6 | 87000
1 | 289384.8 | 87000
1 | 289731.0000000001 | 87000
1 | 290077.2000000001 | 87000
1 | 290423.4000000001 | 87000
1 | 290769.6000000001 | 87000
1 | 291115.8000000001 | 87000
1 | 291462.0000000001 | 87000
1 | 291808.2000000001 | 87000
1 | 292154.4000000001 | 87000
1 | 292500.6000000002 | 87000
1 | 292846.8000000002 | 87000
1 | 293193.0000000002 | 87000
1 | 293539.2000000002 | 87000
1 | 293885.4000000002 | 87000
1 | 294231.6000000002 | 87000
1 | 294577.8000000002 | 87000
1 | 294924.0000000002 | 87000
1 | 295270.2000000002 | 87000
1 | 295616.4000000003 | 87000
1 | 295962.6000000003 | 87000
1 | 296308.8000000003 | 87000
1 | 296655.0000000003 | 87000
1 | 297001.2000000003 | 87000
1 | 297347.4000000003 | 87000
1 | 297693.6000000003 | 87000
1 | 298039.8000000003 | 87000
1 | 298386.0000000003 | 87000
Spreadsheet: 767033d1644250423-what-would-cause-excel-to-pause-its-calcs-when-it-is-set-to-automatic-livecards
Sheet: Diamondbacks

Hitters |  |  | Pitchers
UIG | NAME |  | UIG | NAME
Spreadsheet: 883359d1731984720-sumifs-with-indirect-did-not-work-stock-control-sumifs
Sheet: Others

Date | Names | Stock | Quantity | Price | Total
2024-11-07 00:00:00 | [NAME] | Coffee | 2
2024-11-08 00:00:00 | [NAME] | Sugar | 6
2024-11-14 00:00:00 | [NAME] | Milk | 1
Spreadsheet: 79379d1279649084-excel-2007-max-function-in-pivot-analysis-example-worksheet-copy
Sheet: Sheet1

Survey Respondent | Item | Answer
[NAME] | www.cnn.com | media
[NAME] | www.bbc.com | news
[NAME] | www.bbc.com | entertainment
Klaus | www.bbc.com | entertainment
Klaus | www.bbc.com | media
Klaus | www.bbc.com | entertainment | Item | Answer | Count of Survey Respondent
Klaus | www.slate.com | media | www.bbc.com | entertainment | 3
[NAME] | www.slate.com | media |  | media | 4
[NAME] | www.foxnews.com | news |  | news | 5
[NAME] | www.foxnews.com | entertainment | www.bbc.com Total |  | 12
[NAME] | www.slate.com | entertainment | www.cnn.com | entertainment | 2
[NAME] | www.cnn.com | entertainment |  | media | 3
[NAME] | www.slate.com | entertainment |  | news | 2
[NAME] | www.cnn.com | news |  | news | 1
[NAME] | www.slate.com | news | www.cnn.com Total |  | 8
[NAME] | www.slate.com | news | www.foxnews.com | entertainment | 6
[NAME] | www.slate.com | entertainment |  | media | 4
[NAME] | www.foxnews.com | entertainment |  | news | 4
[NAME] | www.bbc.com | media | www.foxnews.com Total |  | 14
[NAME] | www.slate.com | media | www.slate.com | entertainment | 5
[NAME] | www.cnn.com | news |  | media | 7
[NAME] | www.foxnews.com | entertainment |  | news | 3
[NAME] | www.bbc.com | news | www.slate.com Total |  | 15
[NAME] | www.slate.com | entertainment | Grand Total |  | 49
[NAME] | www.slate.com | news
[NAME] | www.foxnews.com | media
[NAME] | www.cnn.com | news |  |  | Since I have 5,000 "items" (like bbc or cnn), I need
[NAME] | www.foxnews.com | entertainment |  |  | a program to figure out which Answer is the most
[NAME] | www.slate.com | media |  |  | prevalent for each "item"
[NAME] | www.foxnews.com | news
[NAME] | www.cnn.com | media |  |  | So for BBC, it's News
[NAME] | www.foxnews.com | news |  |  | For CNN, it's Media
[NAME] | www.slate.com | media |  |  | For Fox, it's entertainment, etc.
[NAME] | www.bbc.com | news
Branson | www.foxnews.com | news |  |  | I just can't go down the list of 5,000 items by hand.
[NAME] | www.foxnews.com | media
[NAME] | www.cnn.com | entertainment |  |  | Any ideas?
[NAME] | www.bbc.com | media
[NAME] | www.slate.com | media
Branson | www.bbc.com | news
Ina | www.foxnews.com | entertainment
Danielle | www.foxnews.com | entertainment
Branson | www.slate.com | entertainment
[NAME] | www.foxnews.com | media
[NAME] | www.foxnews.com | media
Danielle | www.slate.com | media
Danielle | www.bbc.com | news
Danielle | www.cnn.com | media
[NAME] | www.bbc.com | media
Spreadsheet: 888654d1739222071-change-format-of-data-diabetes-27-apr-2017-to-23-april-2018
Sheet: Table 1

Thu 27 Apr Glucose mmol/L
00:00 | 02:00 |  | 04:00 |  | 06:00 |  | 08:00 |  | 10:00 |  | 12:00 |  | 14:00 |  | 16:00 |  | 18:00 |  | 20:00 |  | 22:00 |  | 00:00
00:00 | 02:00 |  | 04:00 |  | 06:00 |  | 08:00 |  | 10:00 |  | 12:00 |  | 14:00 |  | 16:00 |  | 18:00 |  | 20:00 |  | 22:00 |  | 00:00
Fri 28 Apr Glucose mmol/L
Sat 29 Apr Glucose mmol/L
00:00 | 02:00 |  | 04:00 |  | 06:00 |  | 08:00 |  | 10:00 |  | 12:00 |  | 14:00 |  | 16:00 |  | 18:00 |  | 20:00 |  | 22:00 |  | 00:00
 |  |  |  |  | 6.7
00:00 | 02:00 |  | 04:00 |  | 06:00 |  | 08:00 |  | 10:00 |  | 12:00 |  | 14:00 |  | 16:00 |  | 18:00 |  | 20:00 |  | 22:00 |  | 00:00
Sun 30 Apr Glucose mmol/L
Mon 1 May Glucose mmol/L
00:00 | 02:00 |  | 04:00 |  | 06:00 |  | 08:00 |  | 10:00 |  | 12:00 |  | 14:00 |  | 16:00 |  | 18:00 |  | 20:00 |  | 22:00 |  | 00:00
00:00 | 02:00 |  | 04:00 |  | 06:00 |  | 08:00 |  | 10:00 |  | 12:00 |  | 14:00 |  | 16:00 |  | 18:00 |  | 20:00 |  | 22:00 |  | 00:00
Tue 2 May Glucose mmol/L
Wed 3 May Glucose mmol/L
00:00 | 02:00 |  | 04:00 |  | 06:00 |  | 08:00 |  | 10:00 |  | 12:00 |  | 14:00 |  | 16:00 |  | 18:00 |  | 20:00 |  | 22:00 |  | 00:00
00:00 | 02:00 |  | 04:00 |  | 06:00 |  | 08:00 |  | 10:00 |  | 12:00 |  | 14:00 |  | 16:00 |  | 18:00 |  | 20:00 |  | 22:00 |  | 00:00
[NAME] mmol/L
Legend          High Glucose (>13.3)            Low Glucose (<3.9)
Fri 5 May Glucose mmol/L
Spreadsheet: 30212d1225597462-mirror-image-or-flipping-cells-kew
Sheet: Sheet1

Crocus & Grape Hyacinths | Blue Fescue | Crocus & Grape Hyacinths | Blue Fescue | Crocus & Grape Hyacinths | Blue Fescue | Crocus & Grape Hyacinths | Blue Fescue |  | Blue Fescue | Crocus & Grape Hyacinths | Blue Fescue | Crocus & Grape Hyacinths | Blue Fescue | Crocus & Grape Hyacinths | Blue Fescue | Crocus & Grape Hyacinths
Ajuga | Tulips | Ajuga | Tulips | Ajuga | Tulips | Ajuga | Crocus & Grape Hyacinths |  | Crocus & Grape Hyacinths | Ajuga | Tulips | Ajuga | Tulips | Ajuga | Tulips | Ajuga
Crocus & Grape Hyacinths | Sedum Autumn Joy | [NAME] d'Oro | Sedum Autumn Joy | Daffodils | Euonymous fortunei '[NAME]' | Tulips | Blue Fescue |  | Blue Fescue | Tulips | Euonymous fortunei '[NAME]' | Daffodils | Sedum Autumn Joy | [NAME] d'Oro | Sedum Autumn Joy | Crocus & Grape Hyacinths
Ajuga | Alliums | Daffodils | Daffodils | Daffodils | Daffodils | Ajuga | Crocus & Grape Hyacinths |  | Crocus & Grape Hyacinths | Ajuga | Daffodils | Daffodils | Daffodils | Daffodils | Alliums | Ajuga
Dwarf [NAME] | Alliums | Daffodils | Dwarf [NAME] | Daffodils | Sedum Autumn Joy | Tulips | Blue Fescue |  | Blue Fescue | Tulips | Sedum Autumn Joy | Daffodils | Dwarf [NAME] | Daffodils | Alliums | Dwarf [NAME]
Ajuga | Alliums | Daffodils | Daffodils | Daffodils | [NAME] d'Oro | Ajuga | Crocus & Grape Hyacinths |  | Crocus & Grape Hyacinths | Ajuga | [NAME] d'Oro | Daffodils | Daffodils | Daffodils | Alliums | Ajuga
Crocus & Grape Hyacinths | Red Barberry | Alliums | Alliums | Alliums | Sedum Autumn Joy | Tulips | Blue Fescue |  | Blue Fescue | Tulips | Sedum Autumn Joy | Alliums | Alliums | Alliums | Red Barberry | Crocus & Grape Hyacinths
Ajuga | Crocus & Grape Hyacinths | Ajuga | Dwarf [NAME] | Ajuga | Crocus & Grape Hyacinths | Ajuga | Crocus & Grape Hyacinths |  | Crocus & Grape Hyacinths | Ajuga | Crocus & Grape Hyacinths | Ajuga | Dwarf [NAME] | Ajuga | Crocus & Grape Hyacinths | Ajuga
 |  |  | left |  |  |  |  |  |  | right
Spreadsheet: 124639d1318520615-excel-2007-4-columns-need-to-match-2-cattle-samp-bc
Sheet: Sheet1

Cow Tag | Birth Date | [NAME] | Weaning Wght
1 | 2011-03-06 00:00:00 | 1 | 600
2 | 2011-03-08 00:00:00
3 | 2011-03-09 00:00:00 | 3 | 540
4 | 2011-03-11 00:00:00 | 8 | 555
5 | 2011-03-07 00:00:00 | 10 | 550
6 | 2011-03-10 00:00:00 | 6 | 525
7 | 2011-03-14 00:00:00 | 4 | 515
8 | 2011-03-13 00:00:00 | 9 | 510
9 | 2011-03-12 00:00:00 | 5 | 530
10 | 2011-03-15 00:00:00
Tags | Birth Date | Weaning Weight
1
Spreadsheet: 217905d1362248814-if-and-functions-identifying-text-book1
Sheet: Sheet1

A | B | C | D | E | Helper |  | Unique Items | Colours/Item
[NAME] | Size | Small | Colour | Blue | 1 |  | [NAME] | 3
[NAME] | Size | Small | Colour | Blue |  |  | AA002-Bottoms | 4
[NAME] | Size | Small | Colour | Maroon | 1
[NAME] | Size | Small | Colour | Indigo | 1
[NAME] | Size | Small | Colour | Indigo
AA002-Bottoms | Size | Small | Colour | Blue | 1
AA002-Bottoms | Size | Small | Colour | Red | 1
AA002-Bottoms | Size | Small | Colour | Violet | 1
AA002-Bottoms | Size | Small | Colour | Orange | 1
Spreadsheet: 138165d1327538404-hyperlink-with-a-vlookup-for-web-addresses-excel-test-sheetvladz
Sheet: TR Menu

Course Title |  | Category | Credits | Focus Area/Objectives
Business | http://www.google.com | Web | 1 | Develop skills in Accounting
Finance | http://www.yahoo.com | Web | 1 | Develop skills in Finance
Science |  | Web | 1 | Develop Skills in Science
Accounting |  | Class | 1 | Develop Skills in Accounting
Marketing |  | Class | 1 | Develop Skills in Marketing
Operations |  | Web | 1 | Develop Skills in Operations
Investments |  | Class | 1 | Develop skills in Invensments
Risk |  | Web | 1 | Develop Skills in Risk
Product Pricing |  | Class | 1 | Develop Skills in Product Pricing
Economics |  | Web | 1 | Develop skills in economics
Defined name range for column A and B I used "MENU"
this side is pure text no hyperlink
 | this side is the helper columnB
 | you can enter the links like this in B2 (existing)
 | HYPERLINK("http://www.google.com")
 | DON’T PUT A FRIENDLY NAME ( just plain link)
 | then hide this column