tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: 889074d1739784940-vlookup-not-calculating-correctly-ms-08-agl-tkr-047-wk-08-ppe-inventory
Sheet: Names

ISSUED STATUS
 | Issued to date
 |  |  | Impact Gloves | Paint Mask | Safety Glasses | FRC Coveralls | Safety Boots
1 | ABDEGAR SACRAMENTO
2 | ABRAAO CANGUANGUA
3 | ADAO MAVUNGO
4 | AFONSO NARCISCO
5 | [NAME]
6 | ALLAN BREDENKAMP
7 | AMERICO NETO
8 | ANDRE ANTONIO
9 | [NAME]
10 | [NAME]
11 | ANTONIO MATUVANGA
12 | ARAO SAMUEL
13 | AUGUSTO JOAO
14 | AVELINO KATEKWA
15 | AVELINO RUFINO
16 | BALO MATEUS
17 | BANGANGA MACONDA
18 | BUMBA LOURENCO
19 | CHELA JOAO
20 | DA COSTA YANNICK
21 | DANIEL DOMINGOS
22 | [NAME]
23 | EDUARDO DA SILVA
24 | ELIAS TIAGO
25 | [NAME]
26 | [NAME]
27 | FRANCISCO BANDUMBA
28 | FRANCOIS SWART
29 | FREDERICO MUEDI
30 | GARCIA GERVASIO
31 | GERMINO POBA
32 | GIMBI LUCIO
33 | GIME BERNARDO
34 | ISAAC MARIA
35 | ISAAC NDONGA
36 | [NAME]
37 | JEREMIAS NDONGANI
38 | JERONIMO BRAS
39 | JOAO CABRAL
40 | JOAO MARIA
41 | JOAO NGUNZA
42 | [NAME]
43 | [NAME]
44 | [NAME]
45 | KIALA FABRICIO
46 | KURT STOGER
47 | LUCIANO JANEIRO
48 | LUIS DA SILVA
49 | MABUZA MALUSI
50 | MALONDA PEDRO
51 | MANUEL POMBOLO
52 | MASIAMINA SIMÃO
53 | [NAME]
54 | MAVUNGO RAFAEL
55 | [NAME]
56 | MIGUEL KALAWAKU
57 | MIGUEL TOKO ZASALA
58 | MOSES MEPHI
59 | [NAME]
60 | NHEMBO PEDRO
61 | NZINGA ALBERTO
62 | OLIMPIO CESAR
63 | OSVALDO JOSE
64 | PAULINO BINDA
65 | PAULO LUKIBI
66 | PEDRITO GOMES SITA
67 | PEDRO JUSTINO
68 | [NAME]
69 | QUIBILA PANDA
70 | RAFAEL MATUNTA
71 | RICHTER [NAME]
72 | RODRIGO RODRIGUES
73 | SAKHUMZI NGUBO
74 | SAMI JLAIEL
75 | SHANE VAN RENSBURG
76 | [NAME]
77 | TIAGO GOMA
78 | TUMBA ALMEIDA
79 | [NAME]
80 | LUIS FRANQUE
81 | JOAO CHELA
82 | CARLOS WALTER AFONSO
83 | LUIS JOSÉ
84 | SHANE JANSE VAN RENSBURG
86 | PEDRO MALUNDA
87 | MIGUEL ZASALA
88 | BERNADO GIME
89 | MOISES MEPHI
90 | PEDRO BINDA
91 | ANTONIO MAVUNGO
92 | PEDRITO SITA
93 | PAULO CAPITA
94 | RAMOS DA SILVA
96 | GREGORIO PITULA
97 | ALFREDO D SILVA
101 | [NAME]
102 | CEDRIC TOTAL HSE
103 | OIM
104 | JAIME PASCOAL MARINE
Spreadsheet: 197355d1354306376-new-excel-user-need-help-creating-list-that-populates-different-information-calendar-sample
Sheet: Feb

 | Sunday | Monday | Tuesday | Wednesday | Thursday | Friday | Saturday
 | Notes:
Spreadsheet: 233747d1367920649-formula-for-advace-filter-data-new
Sheet: Data Base

Cost Centre | GL Code | Company | Title | Amount
11 | 11 | PPL | A | 5000
22 | 6520 | PPL | B | 20000
33 | 6530 | PPL | C | 30000
44 | 6540 | OGDC | D | 40000
11 | 22 | OGDC | B | 5000
11 | 33 | NRL | B | 5000
11 | 44 | PSO | B | 5000
22 | 6520 | PSO | B | 20000
22 | 6511 | PSO | B | 30000
11 | 55 | PSO | A | 5000
22 | 66 | PPL | B | 5000
22 | 77 | PPL | B | 5000
22 | 88 | PPL | B | 5000
Spreadsheet: aada0c7c-fc30-471e-b2b0-1ced79088dd2
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
CORTC | Test | CORTC | Corticosterone, Serum | Corticosterone, S | Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) | Plain, Red-Top or serum gel tube: Red |  |  | 0.3 | mL | Container/Tube:  Preferred: Red top  Acceptable: Serum gel  [NAME]: 0.3 mL Collection Instructions: Morning (8 a.m.) specimen is preferred. | 0.25 mL | Hemolysis	Mild OK; Gross reject Thawing	Warm OK; Cold OK Lipemia	Mild reject; Gross reject Icterus	NA Other	NA | < or =18 years: 18-1,970 ng/dL >18 years: 53-1,560 ng/dL | Tuesday; 2 p.m. | 3 days | 9 days | 1 | 82528 |  |  |  |  | Rochester
CORTC | [NAME] | SERUM | Serum |  |  |  | Refrigerated | 7 days
CORTC | Result | 88221 | Corticosterone, S | Corticosterone, S | Numeric |  |  |  |  | ng/dL |  |  |  |  |  |  |  |  |  | 2139-4 | Corticosterone:MCnc:Pt:Ser/Plas:Qn:
Spreadsheet: 166342d1341559305-help-with-multiple-answers-in-model-oil-and-gasexcelsample
Sheet: Inputs

 | 2009 Data | 2010 Data | 2011 Data
Depreciation rate | 0.03 | 0.03 | 0.03
Boe/d | 600 | 700 | 800
tax rate | 0.3 | 0.4 | 0.25
royality | 0.1 | 0.1 | 0.05
variable cost | 5 | 6 | 4.75
operating cost per Boe | 0.5 | 1 | 1.25
Price per Boe | 40 | 42 | 35
Spreadsheet: 850643d1701057710-convert-list-into-lower-triangular-matrix-book1-2-
Sheet: Sheet1

1 | 4 | 5 | 7
Spreadsheet: 274979d1383301749-sumproduct-indirect-array-containing-both-ors-and-ands-example
Sheet: example2

 | THIS WOULD BE THE IDEAL TABLE CONFIGURATION |  |  |  |  |  |  |  |  |  |  | BUT THIS IS HOW I ENDED UP CREATING THE TABLE FOR THE SUMPRODUCT
 | OR |  |  |  | AND | AND | Result of Values that meet criteria to be included in INDIRECT TEST sumproduct |  |  |  |  | OR 1 |  | OR 2 |  | OR 3 |  | OR 4 |  | AND | AND | Result of Values that meet criteria to be included in INDIRECT TEST sumproduct
 | 22222 | EFGHI | 11111 | 99999 | YEAR | Random Number |  |  |  |  |  |  |  |  |  |  |  |  |  | YEAR | Random Number
 | 0 | 0.6 | 0 | 0 | 2016 | 400 |  |  |  |  |  | 22222 | 0 | EFGHI | 0.6 | 11111 | 0 | 99999 | 0 | 2016 | 400
 | 0 | 0 | 0.5 | 0 | 2017 | 600 | 300 |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0.5 | 99999 | 0 | 2017 | 600 | 300
 | 0.5 | 0 | 0 | 0 | 2014 | 300 |  |  |  |  |  | 22222 | 0.5 | EFGHI | 0 | 11111 | 0 | 99999 | 0 | 2014 | 300
 | 0 | 0.4 | 0.4 | 0 | 2017 | 800 | 320 |  |  |  |  | 22222 | 0 | EFGHI | 0.4 | 11111 | 0.4 | 99999 | 0 | 2017 | 800 | 320
 | 0 | 0 | 0 | 0.5 | 2014 | 600 |  |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0 | 99999 | 0.5 | 2014 | 600
 | 1 | 0 | 0 | 0 | 2013 | 600 |  |  |  |  |  | 22222 | 1 | EFGHI | 0 | 11111 | 0 | 99999 | 0 | 2013 | 600
 | 0 | 0 | 0 | 0 | 2014 | 350 |  |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0 | 99999 | 0 | 2014 | 350
 | 0 | 0.5 | 0.4 | 0 | 2013 | 4000 |  |  |  |  |  | 22222 | 0 | EFGHI | 0.5 | 11111 | 0.4 | 99999 | 0 | 2013 | 4000
 | 0.4 | 0 | 0 | 0 | 2017 | 1000 | 0 |  |  |  |  | 22222 | 0.4 | EFGHI | 0 | 11111 | 0 | 99999 | 0 | 2017 | 1000 | 0
 | 0 | 0 | 0.8 | 0 | 2014 | 600 |  |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0.8 | 99999 | 0 | 2014 | 600
 | 0 | 0 | 0 | 0 | 2013 | 600 |  |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0 | 99999 | 0 | 2013 | 600
 | 0 | 0 | 0 | 0 | 2015 | 350 |  |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0 | 99999 | 0 | 2015 | 350
 | 0 | 0 | 0.4 | 0 | 2017 | 600 | 240 |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0.4 | 99999 | 0 | 2017 | 600 | 240
 | 0.2 | 0 | 0 | 0 | 2018 | 600 |  |  |  |  |  | 22222 | 0.2 | EFGHI | 0 | 11111 | 0 | 99999 | 0 | 2018 | 600
 | 0 | 0 | 0 | 0.4 | 2014 | 350 |  |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0 | 99999 | 0.4 | 2014 | 350
 | 0 | 0 | 0 | 0.3 | 2012 | 4000 |  |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0 | 99999 | 0.3 | 2012 | 4000
 | 0 | 0 | 0 | 0.2 | 2017 | 1000 | 0 |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0 | 99999 | 0.2 | 2017 | 1000 | 0
 | 0 | 0 | 0.4 | 0 | 2015 | 600 |  |  |  |  |  | 22222 | 0 | EFGHI | 0 | 11111 | 0.4 | 99999 | 0 | 2015 | 600
 | 0 | 0.5 | 0 | 0 | 2018 | 4 |  |  |  |  |  | 22222 | 0 | EFGHI | 0.5 | 11111 | 0 | 99999 | 0 | 2018 | 4
 | Blue cells meet criteria within sumproduct but green is whole rows that meet all criteria on Overview sheet
Spreadsheet: 27800d1221470262-holdings-checking-checking-holdings-1-
Sheet: 180808

Date | FROM | SecCode
2008-08-29 00:00:00 | LON | QQCAAA
2008-08-29 00:00:00 | LON | QQZBBB
2008-08-29 00:00:00 | LON | QQHCCC
2008-08-29 00:00:00 | LON | [NAME]
2008-08-29 00:00:00 | LON | QQREEE
2008-08-29 00:00:00 | LON | QQSFFF
2008-08-29 00:00:00 | LON | QQTGGG
2008-08-29 00:00:00 | LON | QQXHHH
2008-08-29 00:00:00 | LON | QQZPBIII
2008-08-29 00:00:00 | LON | QBBJJJ
2008-08-29 00:00:00 | LON | QBCKKK
2008-08-29 00:00:00 | LON | QBILLL
2008-08-29 00:00:00 | LON | QBJMMM
2008-08-29 00:00:00 | LON | [NAME]
2008-08-29 00:00:00 | LON | QBQOOO
2008-08-29 00:00:00 | LON | QBQOPPP
2008-08-29 00:00:00 | LON | QBQQQQ
2008-08-29 00:00:00 | LON | QBSSMWRRR
2008-08-29 00:00:00 | LON | QBUSSSS
2008-08-29 00:00:00 | LON | QBVTTTTTT
2008-08-29 00:00:00 | LON | QBWUUUU
2008-08-29 00:00:00 | LON | QBYVVVVVV
2008-08-29 00:00:00 | LON | QCBWWWWW
2008-08-29 00:00:00 | LON | QCKXXXXX
2008-08-29 00:00:00 | LON | QCQYYYYYY
2008-08-29 00:00:00 | LON | QCRZZZZZ
Spreadsheet: darrell_schoolcraft__7816__imbalsumm0109
Sheet: Citizens

Citizens Communications
 | Measured | Scheduled | Imbalance
56659 | -5328 | -630
500046 | -102 |  |  |  |  |  |  |  |  | 2000-01-06 00:00:00 | paper | 0.5
500086 |  |  |  |  |  |  |  |  |  |  | lunch | 7.6
500134 | -10935
500528
500529
500619
INDEX
2001-08-31 00:00:00 |  |  | -757792.37
2001-09-05 00:00:00
CBS Volume
 |  |  | -152176
Spreadsheet: 806891d1669652439-help-converting-an-attendance-tracker-from-days-to-hrs-attendance-pbi
Sheet: Leave

 | Overview | Detailed View | Employees | [NAME] | Reports | Settings | How to Use
 | ID | Name | Position | Role | Shift | Start Date | End Date | Leave | Pass Out | Days | Hours | Total Hrs | Comments
 |  | An Other |  |  |  | 2023-01-03 00:00:00 | 2023-02-03 00:00:00 | Holiday |  |  | 7.75
 |  | A N Other |  |  |  | 2023-01-03 00:00:00 | 2023-01-30 00:00:00 | Holiday |  |  | 7.75
 |  | Other |  |  |  | 2023-01-03 00:00:00 | 2023-02-05 00:00:00 | Holiday |  |  | 8
 |  | [NAME] |  |  |  | 2023-01-03 00:00:00 | 2023-01-28 00:00:00 | Holiday |  |  | 7.75
 |  | George |  |  |  | 2023-01-03 00:00:00 | 2023-02-01 00:00:00 | Holiday |  |  | 8
 |  | Betty |  |  |  | 2023-01-03 00:00:00 | 2023-01-25 00:00:00 | Holiday |  |  | 8
 |  | [NAME] |  |  |  | 2023-01-03 00:00:00 | 2023-01-20 00:00:00 | Holiday |  |  | 7.75
 |  | Other |  |  |  | 2023-02-06 00:00:00 | 2023-02-06 00:00:00 | Holiday |  |  | 4
Spreadsheet: 854932d1704696700-filter-without-result-to-show-blank-for-vstack-filter-without-result
Sheet: Sheet2

Code | Start | End |  | 2023-06-30 00:00:00 |  | Code | Start | End
#1 | 2023-05-12 00:00:00 |  |  |  |  |  | 2023-06-11 00:00:00 |  |  | Basically, I want the top to be Code that start in the Month (E1) and bottom to show Code that end in the Month (E1)
#2 | 2023-05-27 00:00:00 | 2023-06-01 00:00:00 |  |  |  | #4 | 2023-06-26 00:00:00 | 2023-09-16 00:00:00 |  | However, the formula only work nicely if the filter is a valid for both Start and End.
#3 | 2023-06-11 00:00:00 |  |  |  |  | #2 | 2023-05-27 00:00:00 | 2023-06-01 00:00:00 |  | How do I make a Iferror, then it will show blank?
#4 | 2023-06-26 00:00:00 | 2023-09-16 00:00:00
#5 | 2023-07-11 00:00:00
#6 | 2023-09-01 00:00:00
#7 | 2023-09-16 00:00:00
#8 | 2023-10-01 00:00:00
#9 | 2023-10-16 00:00:00 | 2023-12-31 00:00:00
#10 | 2023-10-31 00:00:00
Spreadsheet: 124565d1318465866-autofilter-greed-autofilter-for-nonblank-rows-test-1
Sheet: P1 - Jan 1 - Jan 10

 |  | Pay Period 1 - January 1, 2012 to January 10, 2012
SENIORITY | EMPLOYEE | STAT +  Over Time  @  ½ Time ACCT# | Over Time  @  Straight Time -  ACCT# | Over Time  @  1½ Time ACCT# | Over Time + Acting Time @  1½ + $Acting Pay ACCT# | Acting Time @  $ Acting Pay ACCT# | STAT +  Acting Time @  $ Acting Pay ACCT# | Tech Pay  @  1.5 -  ACCT# | Acting Tech Pay  @  $ -  ACCT# | 1
111 | Employee 1 |  |  |  |  |  |  | 10 | 0 | 1
112 | Employee 2 |  | 10 |  |  |  |  | 0 | 0 | 1
113 | Employee 3 |  |  | 10 |  |  |  | 0 | 0 | 1
114 | Employee 4 | 10 |  |  | 10 |  |  | 0 | 0 | 1
115 | Employee 5 | 10 |  |  |  |  |  | 0 | 0 | 1
116 | Employee 6 |  |  |  |  |  |  | 0 | 0 | 0
117 | Employee 7 |  | 10 |  |  | 10 |  | 0 | 0 | 1
118 | Employee 8 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0 | 1
119 | Employee 9 | 10 | 0 | 0 | 0 | 0 | 10 | 0 | 0 | 1
120 | Employee 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
121 | Employee 11 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1
122 | Employee 12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
123 | Employee 13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
124 | Employee 14 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
125 | Employee 15 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
126 | Employee 16 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0
0 | 0
0 | 0
0 | 0
0 | 0
0 | 0
0 | 0
0 | 0
0 | 0
Spreadsheet: 755623d1636997265-if-formula-to-ignore-result-if-both-index-functions-return-from-the-same-cell-example
Sheet: Sheet1

Respondent |  | How often do you go to the cinema? |  |  |  |  |  |  | Difference between most recent answer and the answer before that
 | Answer in: | January | July | January | July |  |  |  | Previous | Most recent | Difference
A |  | Often | Sometimes | Sometimes
B |  | Sometimes | Sometimes
C |  | Often | Often | No data
D |  | Hardly ever or never | No data | Hardly ever or never | Sometimes
E |  | No data | Hardly ever or never | Sometimes
F |  | Sometimes | Often
Spreadsheet: 861317d1709216174-write-off-report-monthly-ytd-automation-scrapping-report
Sheet: YTD 2024

 | Month | Total Scrapping QAR. 2024 | YTD 2024 | Total Scrapping QAR. 2023 | YTD 2023 |  | 2023 vs 2022 Changes |  | Top 20 Brands - January '24
 | January | 71842.09300000001 | 71842.09300000001 | 131118.09 | 131118.09 |  |  |  | Brand Name | Commerce | Brand Name | Retail
 | February |  |  |  |  |  |  |  | UFC | 9873.199999999992 | HAJMOLA | 2136.05
 | March |  |  |  |  |  |  |  | DABUR-VATIKA NATURAL | 4604.980000000002 | KELLOGGS | 1615.67
 | April |  |  |  |  |  |  |  | PURINA | 3299.67 | BIONA | 716.12
 | May |  |  |  |  |  |  |  | KOPIKO | 3053.12 | FRITOLAY | 481.08
 | June |  |  |  |  |  |  |  | ALPRO | 3047.2 | KIKKOMAN | 476.7
 | July |  |  |  |  |  |  |  | DABUR | 2747.82 | DR OETEKER | 408.71
 | August |  |  |  |  |  |  |  | M.Y.SAN | 2350.639999999999 | BALAJI | 380.11
 | September |  |  |  |  |  |  |  | MAMA SITAS | 2077.34 | KARO | 353.11
 | October |  |  |  |  |  |  |  | DABUR-AMLA | 1756.740000000001 | CERELAC | 351.1
 | November |  |  |  |  |  |  |  | MOTHER'S RECIPE | 1746.5 | GATORADE | 289.41
 | December |  |  |  |  |  |  |  | NATCO | 1389.370000000001 | BETTY CROCER | 257.18
 |  |  |  |  |  |  |  |  | CHINA ITEM | 1375.28 | PLANTERS | 249.29
 |  |  |  |  |  |  |  |  | PUREFOOD | 1322.77 | CLINIC PLUS | 238.82
 |  |  |  |  |  |  |  |  | MAGNOLIA | 1245.51 | INFINITY FOODS | 236.26
 |  |  |  |  |  |  |  |  | MEOW MIX | 981.1299999999999 | CAMPBELLS | 149.92
 |  |  |  |  |  |  |  |  | BESUTO | 957.42 | SUNMAID | 143.6
 |  |  |  |  |  |  |  |  | FAMILY | 942.8499999999998 | OATLY | 139.57
 |  |  |  |  |  |  |  |  | MARA | 897.0400000000003 | EVEREST | 138.36
 |  |  |  |  |  |  |  |  | CERES | 877.75 | FRY & POP | 135.54
 |  |  |  |  |  |  |  |  | LA MING | 848.61 | APTAMIL | 128.13
 |  |  |  |  |  |  |  |  | Others |  | Others
 |  |  |  |  |  |  |  |  | Total of Top 20 Brands |  | Total of Top 20 Brands
 |  |  |  |  |  |  |  |  | Total >>>>>> | 60236.82299999999 | Total >>>>>> | 11605.27
 |  |  |  |  |  |  |  |  | Grand Total >>>>>
Spreadsheet: 730229d1619610163-cumulative-amount-excel-formula-cumulative-amount-
Sheet: Sheet2

I'm kindly asking for excel formula for cumulative amount: column K on the desired result. The current formula does not produce good results.
Current formula |  |  |  |  |  |  | DESIRED OUTCOME
 | [NAME] REPORT |  |  |  |  |  |  | [NAME] REPORT
Revenue |  | 2021-01-01 00:00:00 | Cumulative | % |  |  | Revenue |  | 2021-01-01 00:00:00 | Cumulative | %
Total Funds Received |  |  |  | 0 |  |  | Total Funds Received |  |  | 58968 | 0
TRUST / CONFERENCE FUNDS |  |  |  |  |  |  | TRUST / CONFERENCE FUNDS
Tithe |  |  |  |  |  |  | Tithe |  |  | 47284
Trust Funds |  |  |  |  |  |  | Trust Funds |  |  | 4971
Charity : Trust |  |  |  |  |  |  | Charity : Trust |  |  | 0
Insurance |  |  |  |  |  |  | Insurance |  |  | 0
 |  |  |  |  |  |  |  |  |  | 0
Total Trust Funds |  |  |  |  |  |  | Total Trust Funds |  |  | 52255
Current formula |  |  |  |  |  |  | DESIRED OUTCOME
 | [NAME] REPORT |  |  |  |  |  |  | [NAME] REPORT
Revenue |  | 2021-02-01 00:00:00 | Cumulative | % |  |  | Revenue |  | 2021-02-01 00:00:00 | Cumulative | %
Total Funds Received |  |  |  |  |  |  | Total Funds Received |  |  | 164338
TRUST / CONFERENCE FUNDS |  |  |  |  |  |  | TRUST / CONFERENCE FUNDS
Tithe |  |  |  |  |  |  | Tithe |  |  | 124174
Trust Funds |  |  |  |  |  |  | Trust Funds |  |  | 13611
Charity : Trust |  |  |  |  |  |  | Charity : Trust |  |  | 0
Insurance |  |  |  |  |  |  | Insurance |  |  | 0
 |  |  |  |  |  |  |  |  |  | 0
Total Trust Funds |  |  |  |  |  |  | Total Trust Funds |  |  | 137785
Spreadsheet: 84107d1284106728-sum-across-variable-columns-variable-column-example
Sheet: Sheet1

Item | Week 1 | Week 2 | Week 3 | Week 4
Book | 10 |  | 5 | 3
Pencil | 3 | 3 | 3 | 3
Rubber | 1 | 4 | 6 | 9
Week No
Book
Pencil
Rubber
Spreadsheet: 122c8652-1426-49e1-aa8b-24d0570703c8
Sheet: 2000-2013-Cash Receipts

GAVI Alliance
Cash received 2000-2013
as of 31 March 2013
millions US$
 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | Total
Australia |  |  |  |  |  |  | 5 | 5 | 5 | 5 | 8.6 | 48.844 | 56.4855 | 20.61
Canada |  |  | 1.88035602 | 4.75542135 | 9.06273425 | 130.8686406 | 5.19031142 |  |  |  |  | 20.736 | 15.12859304
Denmark |  | 1.14740743 |  |  | 3.33887922 | 3.41610739 | 4.41126234 | 4.73754 |  | 9.098395589999999 | 1.807207 | 8.798 | 4.351625
European Commission (EC) |  |  |  | 1.26 |  |  |  | 4.84964 | 23.129114 | 28.63013 |  |  | 12.54732252
France |  |  |  |  | 6.02911392 |  | 12.63 |  |  |  |  | 34.5 | 20.10215
Germany |  |  |  |  |  |  | 5.2604 | 5.948 |  | 5.72138 | 5.13598 | 8.5 | 34.69248328 | 3.24125
Ireland |  |  | 0.51075 | 0.62375 | 0.65 | 0.83146 | 7.902 | 8.3112 | 3.84132 | 3.54 | 3.630863 | 4.913 | 3.491585
Japan |  |  |  |  |  |  |  |  |  |  |  | 9.348 | 9.067392
Luxembourg |  |  |  |  |  | 0.64515 | 1.318775 | 0.81184 | 1.4229 | 1.19124 | 1.10044 | 1.186 | 1.0752701 | 1.060424
Netherlands |  | 24.06033462 | 13.37517187 | 16.49264195 | 17.32986645 | 15.85941435 |  | 33.547469 | 38.885301 | 31.20579 | 25.1113845 | 26.3 | 14.2065
Norway |  | 17.89468975 | 21.32565609 | 21.79108674 | 40.92459264 | 39.53459411 | 67.37931370000001 | 86.156761 | 65.44948326 | 82.80032471 | 76.483608 | 79.2 | 106.8762334
Republic of Korea |  |  |  |  |  |  |  |  |  |  | 0.4 | 0.3 | 0.3
Spain |  |  |  |  |  |  |  |  | 40.5362 |  |  | 2.666 | 0
Sweden |  | 1.89213259 | 1.11479998 | 2.38518169 | 4.93142988 | 12.66340061 | 14.59397503 | 15.514976 | 19.151976 | 13.80099952 | 36.4874975 | 92.7 | 0
United Kingdom | 4.4634 |  | 15.04825 | 5.60595 | 18.491535 | 6.625149 | 23.214072 | 48.113952 |  |  | 15.883044 | 85.1 | 206.88
United States |  | 48.092 | 53 | 58 | 59.64 | 64.48 | 69.3 | 69.3 | 71.913 | 75 | 78 | 89.8 | 130
Donor Governments and EC
Anglo Amercian plc |  |  |  |  |  |  |  |  |  |  |  | 1 | 1
Absolute Return for Kids (ARK) |  |  |  |  |  |  |  |  |  |  |  |  | 1.6104
Bill & Melinda Gates Foundation | 325 | 425 |  | 3.5 | 5 | 154.338 |  | 75 | 75 | 75 | 75 | 264.1 | 268.8 | 185.1
[NAME] |  |  |  |  |  |  |  |  |  |  |  |  | 3.2 | 0.7447
His Highness Sheikh [NAME] |  |  |  |  |  |  |  |  |  |  |  | 14.1 | 8.8254855
"la Caixa" Foundation |  |  |  |  |  |  |  |  | 5.8 | 5.9 | 4 | 3.1 | 2.841215
LDS Charities |  |  |  |  |  |  |  |  |  |  |  |  | 1.5
JP Morgan |  |  |  |  |  |  |  |  |  |  |  | 2.361 | 0
The Children’s Investment Fund Foundation (UK) |  |  |  |  |  |  |  |  |  |  |  |  | 4.3
Other private | 0.02 |  | 1.630361 | 2.580847 | 1.805051 | 0.47348 | 1.904352 | 1.1 | 0.8 | 1 | 1 | 0.8 | 0.7589999999999999
Private Contributions
Sub-total
IFFIm to GFA transfers |  |  |  |  |  |  | 524.749285 | 428.268866 | 272.638133 | 330.027 | 320 | 300 | 100 | 0
AMC funds |  |  |  |  |  |  |  |  |  |  | 42.87705 |  | 223.5 | 90
Total contributions
Donations recorded on a cash basis
Spreadsheet: 00defd8b-bf65-47c1-82e2-eb699b26c111
Sheet: BLS-Jul2012

Consumer Price Index - All Urban Consumers
Original Data Value
Series Id: | CUUR0000SA0
Not Seasonally Adjusted
Area: | U.S. city average
Item: | All items
Base Period: | 1982-84=100
Years: | 2000 to 2012
Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Annual | HALF1 | HALF2
2000 | 168.8 | 169.8 | 171.2 | 171.3 | 171.5 | 172.4 | 172.8 | 172.8 | 173.7 | 174 | 174.1 | 174 | 172.2 | 170.8 | 173.6
2001 | 175.1 | 175.8 | 176.2 | 176.9 | 177.7 | 178 | 177.5 | 177.5 | 178.3 | 177.7 | 177.4 | 176.7 | 177.1 | 176.6 | 177.5
2002 | 177.1 | 177.8 | 178.8 | 179.8 | 179.8 | 179.9 | 180.1 | 180.7 | 181 | 181.3 | 181.3 | 180.9 | 179.9 | 178.9 | 180.9
2003 | 181.7 | 183.1 | 184.2 | 183.8 | 183.5 | 183.7 | 183.9 | 184.6 | 185.2 | 185 | 184.5 | 184.3 | 184 | 183.3 | 184.6
2004 | 185.2 | 186.2 | 187.4 | 188 | 189.1 | 189.7 | 189.4 | 189.5 | 189.9 | 190.9 | 191 | 190.3 | 188.9 | 187.6 | 190.2
2005 | 190.7 | 191.8 | 193.3 | 194.6 | 194.4 | 194.5 | 195.4 | 196.4 | 198.8 | 199.2 | 197.6 | 196.8 | 195.3 | 193.2 | 197.4
2006 | 198.3 | 198.7 | 199.8 | 201.5 | 202.5 | 202.9 | 203.5 | 203.9 | 202.9 | 201.8 | 201.5 | 201.8 | 201.6 | 200.6 | 202.6
2007 | 202.416 | 203.499 | 205.352 | 206.686 | 207.949 | 208.352 | 208.299 | 207.917 | 208.49 | 208.936 | 210.177 | 210.036 | 207.342 | 205.709 | 208.976
2008 | 211.08 | 211.693 | 213.528 | 214.823 | 216.632 | 218.815 | 219.964 | 219.086 | 218.783 | 216.573 | 212.425 | 210.228 | 215.303 | 214.429 | 216.177
2009 | 211.143 | 212.193 | 212.709 | 213.24 | 213.856 | 215.693 | 215.351 | 215.834 | 215.969 | 216.177 | 216.33 | 215.949 | 214.537 | 213.139 | 215.935
2010 | 216.687 | 216.741 | 217.631 | 218.009 | 218.178 | 217.965 | 218.011 | 218.312 | 218.439 | 218.711 | 218.803 | 219.179 | 218.056 | 217.535 | 218.576
2011 | 220.223 | 221.309 | 223.467 | 224.906 | 225.964 | 225.722 | 225.922 | 226.545 | 226.889 | 226.421 | 226.23 | 225.672 | 224.939 | 223.598 | 226.28
2012 | 226.665 | 227.663 | 229.392 | 230.085 | 229.815 | 229.478 |  |  |  |  |  |  |  | 228.85
Source:
U.S. Department of Labor
Bureau of Labor Statistics
Data extracted on: July 17, 2012 (12:44:46 PM)
Spreadsheet: 657293d1578679557-canadian-postal-code-validation-data-validation-needed2-aligw
Sheet: data-validation-needed2 AliGW

postal_code |  |  | HELPER COLUMNS
T3A 6E1
VOj 1eo
V0J1X0
V0J1E1
V0v 1c0
V0V-1B
V8G-1K8
T3a6e1
T3A6EI
T3A
T3A 6E11
T3A6E11
T3A6E1,
T3A  6E1
t3A6e1
t3A 6E1
Spreadsheet: 65950d1266576356-lookup-formula-demo-v2
Sheet: Array Formula Explain

date | address | job details |  | date | address | job details
2007-03-01 00:00:00 | 45 mountain lane | gutters |  | 2007-04-23 00:00:00 | england 1 | painting |  | Example
 | 6 daffodil close | driveway |  | 2007-04-23 00:00:00 | england 5 | roofing |  | Adjust the ROW offset to when the formula starts
 | 5 leek st | window fix |  | 2007-03-17 00:00:00 | 43 ireland st | roof repair |  | eg if this was place at B20 the Row offset will be -19 |  |  |  |  |  | The column of information you want retrieved
 |  |  |  | 2007-03-17 00:00:00 | 17 ireland st | window fix
 |  |  |  | 2007-03-17 00:00:00 | 85 ireland st | renew fence
 |  |  |  | 2007-11-30 00:00:00 | hilly road | general painting |  | The second last ROW in the formula an offset must be add
 |  |  |  | 2007-03-01 00:00:00 | 45 mountain lane | gutters |  | eg if the look up information started at D6. The Row offset will be -5
 |  |  |  | 2007-04-23 00:00:00 | england 2 | renew fence
 |  |  |  | 2007-04-23 00:00:00 | england 3 | doors
 |  |  |  | 2007-03-01 00:00:00 | 6 daffodil close | driveway
 |  |  |  | 2007-11-30 00:00:00 | 15 glen close | tree felling
 |  |  |  | 2007-03-01 00:00:00 | 5 leek st | window fix
 |  |  |  | 2007-04-23 00:00:00 | england 4 | window fix
 | Another lookup formula that auto the cell
 | Another lookup formula by columns not rows