tianzl66/Sheetpedia huggingface dataset:
Spreadsheet: gstorey__12107__Mar01
Sheet: Table2a

NATURAL GAS EXPORTS BY TERM, REGION, AND CUSTOMER TYPE |  |  |  |  |  |  |  |  |  |  |  | TABLE 2
EXPORTATIONS DE GAZ NATUREL PAR TERME, RÉGION, ET CLIENT
 |  |  |  | AVERAGE PRICE |  |  |  |  |  | AVERAGE PRICE
 | VOLUME |  |  | PRIX MOYEN |  |  | VOLUME |  |  | PRIX MOYEN
 | (BCF) |  |  | ($US/MMBTU) |  |  | (BCF) |  |  | ($US/MMBTU)
 |  |  | % CHANGE |  |  | % CHANGE |  |  | % CHANGE |  |  | % CHANGE
 |  |  | VARIATION |  |  | VARIATION | 1999/11 | 2000/11 | VARIATION | 1999/11 | 2000/11 | VARIATION
 | 2000-03-01 00:00:00 | 2001-03-01 00:00:00 | EN % | 2000-03-01 00:00:00 | 2001-03-01 00:00:00 | EN % | 2000-03-01 00:00:00 | 2001-03-01 00:00:00 | EN % | 2000-03-01 00:00:00 | 2001-03-01 00:00:00 | EN %
TERM/TERME
LONG-TERM (FIRM)/LONG TERME (GARANTI) | 86.5 | 67.2 | -22.3 | 2.51 | 4.83 | 92.2 | 405.2 | 332.9 | -17.8 | 2.6 | 5.6 | 115.7
SHORT-TERM (FIRM)/COURT TERME (GARANTI) | 127.4 | 166 | 30.3 | 2.47 | 5.09 | 106.1 | 676 | 807.2 | 19.4 | 2.43 | 6.62 | 171.9
SHORT-TERM/COURT TERME (INTERRUPTIBLE) | 86.6 | 88.2 | 1.8 | 2.69 | 5.4 | 101 | 413.9 | 537.4 | 29.8 | 2.53 | 7.13 | 182.2
TOTAL - TERM/TERME | 300.5 | 321.4 | 7 | 2.55 | 5.13 | 101.3 | 1495.2 | 1677.6 | 12.2 | 2.5 | 6.58 | 162.9
REGION/RÉGION
CALIFORNIA/CALIFORNIE | 57.6 | 48.2 | -16.3 | 2.3 | 6.24 | 171.9 | 305.5 | 265.6 | -13 | 2.35 | 7.15 | 204.1
MIDWEST/MIDWEST | 106.6 | 121.4 | 13.9 | 2.41 | 4.83 | 100.7 | 544.9 | 629.4 | 15.5 | 2.38 | 6.26 | 163.2
MOUNTAIN/ROCHEUSES | 3 | 1 | -65.7 | 2.47 | 2.98 | 20.6 | 15.2 | 6.4 | -58.1 | 2.29 | 4.44 | 93.5
NORTHEAST/NORD-EST | 88.5 | 92.1 | 4 | 2.99 | 5.09 | 70 | 409.1 | 527.8 | 29 | 2.87 | 6.35 | 121
PACIFIC NORTHWEST/NORD-OUEST PACIFIQUE | 44.7 | 58.7 | 31.3 | 2.33 | 4.91 | 111.2 | 220.5 | 248.5 | 12.7 | 2.36 | 7.33 | 210.6
TOTAL - REGION/RÉGION | 300.5 | 321.4 | 7 | 2.55 | 5.13 | 101.3 | 1495.2 | 1677.6 | 12.2 | 2.5 | 6.58 | 162.9
CUSTOMER TYPE/CLIENT
END-USER/UTILISATEURS ULTIMES | 23.6 | 24.1 | 2 | 2.87 | 4.22 | 47.21 | 118.5 | 107.6 | -9.2 | 2.79 | 4.77 | 70.6
LDC/SDL | 80.1 | 61.9 | -22.8 | 2.62 | 5.05 | 92.93 | 393.8 | 357.2 | -9.3 | 2.56 | 6.31 | 146.7
MARKETING CO./DISTRIBUTEURS | 187.3 | 222.1 | 18.6 | 2.52 | 5.29 | 110.34 | 930.1 | 1142.8 | 22.9 | 2.46 | 6.92 | 181.1
PIPELINE/PIPELINES | 9.4 | 13.4 | 41.7 | 1.75 | 4.32 | 147.34 | 52.9 | 70 | 32.3 | 2.15 | 5.13 | 138.2
TOTAL - CUSTOMER TYPE/CLIENT | 300.5 | 321.4 | 7 | 2.55 | 5.13 | 101.3 | 1495.2 | 1677.6 | 12.2 | 2.5 | 6.58 | 162.9
NOTE: | THE AVERAGE PRICE IS THE WEIGHTED AVERAGE |  |  |  |  |  | NOTA: | LE PRIX MOYEN EST LE PRIX MOYEN PONDÉRÉ
 | PRICE AT THE INTERNATIONAL BORDER |  |  |  |  |  |  | À LA FRONTIÈRE INTERNATIONALE
Spreadsheet: 113487d1309368756-conditional-formatting-if-cell-blank-on-sheet-2-i-want-another-cell-on-sheet-1-red-782213-conditional-formatting-test
Sheet: Sheet1

2011-07-01 00:00:00
2011-07-02 00:00:00
2011-07-03 00:00:00
2011-07-04 00:00:00
2011-07-05 00:00:00
2011-07-06 00:00:00
2011-07-07 00:00:00
2011-07-08 00:00:00
2011-07-09 00:00:00
2011-07-10 00:00:00
2011-07-11 00:00:00
2011-07-12 00:00:00
2011-07-13 00:00:00
2011-07-14 00:00:00
2011-07-15 00:00:00
2011-07-16 00:00:00
2011-07-17 00:00:00
2011-07-18 00:00:00
2011-07-19 00:00:00
2011-07-20 00:00:00
2011-07-21 00:00:00
2011-07-22 00:00:00
2011-07-23 00:00:00
Spreadsheet: 5e2e4d85-13c9-44d5-b624-19ffd8ae93e5
Sheet: Table 5.4

Monthly Statistical Bulletin
5.4 Home loan affordability
Quarter | 2009-10 | 2010-11 | 2011-12 | 2012-13 | 2013-14
Average size of new home loan (a) – $
September | 292795 | 326733 | 323572 | 320495 | 321619
December | 308764 | 329159 | 317044 | 325949
March | 316134 | 323183 | 311420 | 322193
June | 325553 | 328979 | 321127 | 321423
Annual average | 309110.9720611516 | 327143.2771327381 | 318375.3964364378 | 322531.4568968021
Average monthly repayment on new home loans – $
September | 1746.653815210925 | 2205.178528061062 | 2258.474188097593 | 2176 | 1993
December | 1960.555475668386 | 2271.914192157253 | 2226.791504535607 | 2131
March | 2019.69439471878 | 2239.838466872784 | 2196 | 2106
June | 2174.679556442804 | 2290.488099812118 | 2155 | 2050
Annual average | 1975.395810510224 | 2251.854821725804 | 2209.0664231583 | 2115.75
Loan repayments as a proportion of family income – per cent
September | 29.5 | 35.5 | 34.4 | 33.3 | 29.8
December | 32.4 | 36 | 33.5 | 30.4
March | 33 | 35 | 32.7 | 29.9
June | 35.2 | 35.4 | 31.9 | 31
Annual average | 32.6 | 35.5 | 33.1 | 31.1
(a) Excludes alterations and additions and refinancing.
Sources: Real Estate Institute of Australia and Adelaide Bank | http://www.reiaustralia.com.au/ | http://www.reiaustralia.com.au/ | http://www.reiaustralia.com.au/
ABS, Housing Finance, Cat. no. 5609.0 | http://www.abs.gov.au/AUSSTATS/abs@.nsf/second+level+view?ReadForm&prodno=5609.0&viewtitle=Housing%20Finance,%20Australia~Jan%202008~Latest~11/03/2008&&tabname=Past%20Future%20Issues&prodno=5609.0&issue=Jan%202008&num=&view=& | http://www.abs.gov.au/AUSSTATS/abs@.nsf/second+level+view?ReadForm&prodno=5609.0&viewtitle=Housing%20Finance,%20Australia~Jan%202008~Latest~11/03/2008&&tabname=Past%20Future%20Issues&prodno=5609.0&issue=Jan%202008&num=&view=& | http://www.abs.gov.au/AUSSTATS/abs@.nsf/second+level+view?ReadForm&prodno=5609.0&viewtitle=Housing%20Finance,%20Australia~Jan%202008~Latest~11/03/2008&&tabname=Past%20Future%20Issues&prodno=5609.0&issue=Jan%202008&num=&view=&
 |  |  |  |  |  |  |  | Update
 |  |  |  |  |  |  |  | 12 March 2014 for lending
Spreadsheet: 155311d1336757414-excel-2007-help-with-links-test-estimate
Sheet: Sheet1

 | [NAME] (stock description) | Qty | Stock Price | Total Price
 |  | 0 | 0
 |  | 0 | 0
 |  | 0 | 0
 |  | 0 | 0
 |  | 0 | 0
 |  | 0 | 0
 |  | 0 | 0
 |  | 0 | 0
Spreadsheet: 377985d1424236171-how-to-lock-cells-in-a-protected-worksheet-analyst-appraisal-form
Sheet: APM

 | 6) | Relationships with clients
 |  |  |  | Self | Manager 1 | Manager 2 | Manager 3 | Manager 4 |  | Self | Manager
 |  | Project Name |  | Score | Score | Score | Score | Score |  | Comments | Comments | 3 | Very Good
 |  |  |  |  |  |  |  |  |  |  |  | 2 | Good
 |  |  |  |  |  |  |  |  |  |  |  | 1 | Average
 |  |  |  |  |  |  |  |  |  |  |  | NA | Not Applicable
 | 7) | Quality Monitoring
 |  |  |  | Self | Manager 1 | Manager 2 | Manager 3 | Manager 4 |  | Self | Manager
 |  | Project Name |  | Score | Score | Score | Score | Score |  | Comments | Comments | 3 | Very Good
 |  |  |  |  |  |  |  |  |  |  |  | 2 | Good
 |  |  |  |  |  |  |  |  |  |  |  | 1 | Average
 |  |  |  |  |  |  |  |  |  |  |  | NA | Not Applicable
 | 8) | Teams handled (independently or within team)
 |  |  |  | Self | Manager 1 | Manager 2 | Manager 3 | Manager 4 |  | Self | Manager
 |  | Project Name | Size | Score | Score | Score | Score | Score |  | Comments | Comments | 4 | Very Good
 |  |  |  |  |  |  |  |  |  |  |  | 3 | Good
 |  |  |  |  |  |  |  |  |  |  |  | 2 | Average
 |  |  |  |  |  |  |  |  |  |  |  | 1 | Needs Improvement
 | 9) | Support to manager (eg - presentations made, regular feeback provided, trainings, con calls, etc.)
 |  |  |  | Self | Manager 1 | Manager 2 | Manager 3 | Manager 4 |  | Self | Manager
 |  | Project Name |  | Score | Score | Score | Score | Score |  | Comments | Comments | 4 | Very Good
 |  |  |  |  |  |  |  |  |  |  |  | 3 | Good
 |  |  |  |  |  |  |  |  |  |  |  | 2 | Average
 |  |  |  |  |  |  |  |  |  |  |  | 1 | Needs Improvement
Spreadsheet: darrell_schoolcraft__7802__imbalsumm0108
Sheet: Amoco Abo

 | [NAME] |  | Amoco Abo fuel del
Day | Measured | Scheduled | Measured | Scheduled | Imbal
1 | 12222 | 11345
2 | 12888 | 11487
3 | 11891 | 11488
4 | 11899 | 11090
5 | 11842 | 11492
6 | 11356 | 11494
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
2001-07-31 00:00:00 |  |  |  |  | 444350.97
2001-08-06 00:00:00
CBS Volume
 |  |  | -234993
Spreadsheet: 92278d1291900645-array-formula-help-counting-size-of-a-dataset-count-dataseries-no
Sheet: Sheet1

Data set 1
Data 1 | Data 2 | Sum | Rank
12 | 69 |  |  |  | 10 |  |  | I need help with a formulae which counts the number of pieces of data in each data set, each spreadsheet may contain hundereds of data sets with up to 30 pieces of data in each. Also i need the anser to be returned in the same row as the rank "1." For instance the first dataset would yeild 10 in "F5," the second dataset would yeild "5" in "519" etc. I have a feeling this can be done with array formulae, but these are very new to me, and could require some assistance.
15 | 59
16 | 57
17 | 45
25 | 30
46 | 5
45 | 5
47 | 1
14 | 10
13 | 5
Data set two
Data 1 | Data 2 | Sum | Rank
12 | 69 |  |  |  |  | <- | Should be 5
15 | 59
16 | 57
17 | 45
25 | 30
Data set three
Data 1 | Data 2 | Sum | Rank
25 | 30 |  |  |  |  | <- | Should be 4
46 | 5
45 | 5
47 | 1
Spreadsheet: 27448d1220628231-a-two-part-summation-pivot
Sheet: Sheet1

Product | Quantity
Product A | 2
Product A | 4 |  | Sum of Quantity
Product A | 3 |  | Product | Total
Product B | 7 |  | Product A | 9
Product C | 1 |  | Product B | 7
Product C | 1 |  | Product C | 2
Product D | 9 |  | Product D | 30
Product D | 2 |  | Grand Total | 48
Product D | 3
Product D | 5
Product D | 6
Product D | 5
Spreadsheet: 713183d1610576597-pull-data-from-one-cell-on-multiple-sheets-to-one-column-test
Sheet: 32013

Vehicle Block | Pull-out Dep. | Pull-in Dep. | Depot | Revenues Miles | [NAME]
32013 | ECP | ECP | ECP | 164.037 | 8.6
Line | Pattern | Trip Code | Duty ID | Node1 | Time1 | Node2 | Time2 | Node3 | Time3 | Node4 | [NAME]
DH |  |  |  | ECP | 06:12:00 | AK | 06:27:00
AKPGF | AK_PL |  |  | AK | 06:27:00 | PL | 06:52:00
AKPGF | PL_AK |  |  | PL | 06:52:00 | AK | 07:15:00
AKSDB | AK_BW |  |  | AK | 07:22:00 | BW | 07:40:00
AKSDB | BW_AK |  |  | BW | 07:40:00 | AK | 07:54:00
AKKW | AK_PN_SP_TP_MR_HH |  |  | AK | 07:58:00 | KW_PN | 08:19:00 | [NAME] | 08:30:00 | KW_HH | 08:34:00
DH |  |  |  | KW_HH | 08:34:00 | ECP | 08:45:00
DH |  |  |  | ECP | 13:23:00 | MK | 13:38:00
MKST | MK_ST |  |  | MK | 13:38:00 | ST | 13:55:00
MKST | ST_MK |  |  | ST | 13:58:00 | MK | 14:15:00
MKST | MK_ST |  |  | MK | 14:18:00 | ST | 14:35:00
MKST | ST_MK |  |  | ST | 14:38:00 | MK | 14:55:00
MKST | MK_ST |  |  | MK | 14:58:00 | ST | 15:15:00
MKST | ST_MK |  |  | ST | 15:18:00 | MK | 15:35:00
MKST | MK_ST |  |  | MK | 15:38:00 | ST | 15:55:00
MKST | ST_MK |  |  | ST | 15:58:00 | MK | 16:15:00
MKST | MK_ST |  |  | MK | 16:18:00 | ST | 16:35:00
MKST | ST_MK |  |  | ST | 16:38:00 | MK | 16:55:00
MKST | MK_ST |  |  | MK | 16:58:00 | ST | 17:15:00
MKST | ST_MK |  |  | ST | 17:18:00 | MK | 17:35:00
MKST | MK_ST |  |  | MK | 17:38:00 | ST | 17:55:00
MKST | ST_MK |  |  | ST | 17:58:00 | MK | 18:15:00
MKST | MK_ST |  |  | MK | 18:18:00 | ST | 18:35:00
MKST | ST_MK |  |  | ST | 18:38:00 | MK | 18:55:00
MKST | MK_ST |  |  | MK | 18:58:00 | ST | 19:15:00
MKST | ST_MK |  |  | ST | 19:18:00 | MK | 19:35:00
MKST | MK_ST |  |  | MK | 19:38:00 | ST | 19:55:00
MKST | ST_MK |  |  | ST | 19:58:00 | MK | 20:15:00
MKST | MK_ST |  |  | MK | 20:18:00 | ST | 20:35:00
MKST | ST_MK |  |  | ST | 20:38:00 | MK | 20:55:00
MKST | MK_ST |  |  | MK | 20:58:00 | ST | 21:15:00
DH |  |  |  | ST | 21:15:00 | ECP | 21:26:00
DH |  |  |  | ECP | 21:28:00 | EC | 21:29:00
ECCS | EC_CA_EL |  |  | EC | 21:29:00 | CS_CA | 21:50:00 | [NAME] | 21:53:00
ECCS | EL_EC |  |  | [NAME] | 21:53:00 | EC | 22:08:00
DH |  |  |  | EC | 22:08:00 | ECP | 22:09:00
Spreadsheet: thomas_martin__39857__Texas - Trading
Sheet: Texas - Trading

 | Texas - Trading
 | 2002 Plan
 |  |  |  |  |  |  |  |  | Per HC | New HC | Adjust Comp
 |  | 2001-09-01 00:00:00 |  | 2001 |  | % | 2002
 |  | YTD Actual |  | Forecast |  | of Total | Plan
ENACOMP | Compensation |  |  |  |  |  |  | Compensation | 0
 | Special Pays |  |  | 0 |  |  | 0
 | Analyst & Associates |  |  |  |  |  |  |  |  |  |  |  | [NAME], [NAME] | ASSOCIATE | ENA NG TEXAS REGION G&A
ENABENTX | Benefits & Payroll Taxes |  |  |  |  |  |  | Other |  |  |  |  | [NAME], [NAME] | ASSOCIATE | ENA NG TEXAS REGION G&A
ENAEMPEX | Employee Expense |  |  |  |  |  |  |  |  |  |  |  | Martin, Thomas A | VICE PRESIDENT | ENA NG TEXAS REGION G&A
ENAT&EEX | Travel & Entertainment Expense |  |  |  |  |  |  | Total |  |  |  |  | Schwieger, [NAME] | VICE PRESIDENT | ENA NG TEXAS REGION G&A
ENAOUTSV | Outside Services |  |  |  |  |  |  |  |  |  |  |  | [NAME], [NAME] R | MANAGER | ENW-ENERGY OPS TEXAS RISK MGMT
ENASUPP | Supplies Expense
ENAMKTEX | Marketing |  |  |  |  |  |  | Intern | 33000
ENACONTR | Charitable Contributions |  |  |  |  |  |  | [NAME] | 48400 | 0
ENARENT | Rent |  |  |  |  |  |  | Staff | 49500 | 0
ENATECH | Technology |  |  |  |  |  |  | Specialist | 57750 | 0
ENATRANS | Transportation |  |  |  |  |  |  | Sr. Specialist | 71500 | 0
ENAOTHEX | Other Expenses |  |  |  |  |  |  | Analyst | 60500 | 0
ENATAXES | Taxes Other than Income |  |  |  |  |  | 0 | Associate | 89100 | 2
ENATOTDR | Total Direct Expenses |  |  |  |  |  |  | Manager | 110000 | 1
 |  |  |  |  |  |  |  | Director | 143000 | 0
 | Headcount |  |  |  |  |  |  | Sr. Director | 165000 | 0
 |  |  |  |  |  |  |  | VP | 198000 | 2
 | A&A Headcount |  |  |  |  |  |  | MD | 220000 | 0
 | Total Headcount |  |  |  |  |  |  |  |  |  | 0.2
 |  |  |  |  |  |  | Other Expense Calculation
 | Outside Services | 254512
 |  |  |  |  |  |  | Total Misc Exp | Old HC | Exp/Old HC | New HC | Exp/New HC
Spreadsheet: 08688de9-7591-437f-b361-5cf25a09ce50
Sheet: Project Summary

PROJECT SUMMARY
Project Name:
Date:
County
SOURCES
OHCS Grants & Equity
OHCS Loans
PHB Sources
Other Loans
Other Grants
Applicant Contributions
Other Funds
TOTAL FUNDING SOURCE
USES
Acquisition
Construction/Rehab
Development Costs
Total
FIRST YEAR INCOME & EXPENSES
 | Without OAHTC | With OAHTC
Rental Income
Other Income
Gross Potential Income
Less Vacancy
Effective Gross Income
Annual Operating Expenses
Net Operating Income
Annual Debt Service
Primary Debt Coverage
Spreadsheet: 809850d1671374303-how-to-only-show-data-on-page-soa-mo-10-lf-there-is-data-in-gl-mo-10-oktober-2022-nuut-01-1-
Sheet: SOA Q1

Statement of Activity
YTD End of 1st Qtr
 | Cash Beginning of Period
 | Revenue:
 |  | Total Revenue:
 | Expenses:
 |  | Total Expenses:
 | Net : Income Gain / (Loss)
 | Cash End of Period
Spreadsheet: 020c62bf-b155-4263-a37e-3678e7a9ec26
Sheet: example

Microsoft® Office SharePoint® Server 2010
Term sets worksheet
Fill this worksheet by using the following topics:
Plan terms and term sets
Prepared by:
Date:
Term set | Description | Owner | Group
cost center | All valid cost centers in the company | [NAME] | HR term sets
product name | The names of all products the company sells. For released products, this is the official name from Marketing. For pre-release products, this can be a code name. | [NAME] | marketing term sets
job title | Official job titles | [NAME] | HR term sets
company offices | The name of every facility at which the company maintains a presence. | Facilities | facilities term sets
Spreadsheet: 122014d1316551995-indirect-erep_1gb-tigrovi_bkp
Sheet: xxxx xxxx

Ambient on/off
eRepublik – Online Strategy Game
Sep20 Day 1,400 of the New World
Home
My Land
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Invite friends
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Get Gold & Extras
[NAME]
[NAME]
27
60
Eat food
Gold2.24 Gold
BAM411 BAM
HRK1625 HRK
Missions
X
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Completed!
2011-10-03 00:00:00
2011-10-03 00:00:00
2011-10-03 00:00:00
Reward
Ok
Congratulations, your rank is now
Rank Bonus on attack +5%
Energy bar
Ok
Strength
Experience points
Health
Rank points
Gold
Energy bar
[NAME]
Free Lands
Scope
Bazooka
Weapons
Weapons
Weapons
Food units
Food units
Food units
Grain Farms
0 0
Logout
Experience level: 27
Experience points: 10027
Next level at: 15000
• Working, training and fighting decreases health
[NAME], health boxes, food, hospitals restore health.
This action restores as much health as possible by eating Food from your Storage.
You can recover up to: 450 / 450 Health
100 more recoverable Health in: 00:59:59
Food limit reached
You have reached your food consumption limit.
You can recover 100 health every hour.
100 more recoverable Health in: [NAME]
Buy health kit Close
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offlinexxxx xxxx
Add as a friend Send message Donate
Experience level 27
11,392 / 15,000
Location: PolandPoland, Lower Saxony and Bremen Citizenship: USAUSA
eRepublik birthday
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National rank: 993
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HV 1.GB Tigrovi HV 1.GB Tigrovi
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Friends(104)
Kokach
[NAME]
webstartm
[NAME]
Zion I
Sucko
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view all
Land of xxxx xxxx: 16 buildings
Visit
Achievements
hard worker
10
Hard Worker
Worked 30 days in a row
congressman
Congress Member
Win the Congress elections
president
Country President
Win the Presidential elections
media mogul
Media Mogul
Reach 1000 subscribers to your newspaper
battle hero
1
Battle Hero
Reach the highest war influence in a battle
campaign hero
Campaign hero
Reach the highest war influence in a campaign
resistance hero
Resistance Hero
Start a resistance war and liberate that region
super soldier
15
Super Soldier
Advance 250 strength points
society builder
Society Builder
Invite 10 people to eRepublik and help them reach level 10
mercenary
Mercenary
Defeat 25 enemies for 50 different countries
Coming soon
Coming soon
Military Skills
Strength
3,802.66
Super soldier:3,802 / 4,000
Rank
General General
Rank points:
789,239 / 800,000
Forum   |   [NAME]   |   Blog   |   Press   |   Contact   |   [NAME]   |   Terms of Service   |   Privacy  |   Affiliates  |   [NAME]
Follow us: FacebookFacebook TwitterTwitter
Copyright © 2007-2011 eRepublik
Spreadsheet: 58006d1258315934-calculate-according-to-the-values-of-adjacent-boxes-copy-of-book1-1-
Sheet: Sheet1

 |  |  | Product per worker | Total investment | Depreciation on capital |  | Consumption per worker | Growth in prudct per worker
 | period | Capital per worker | f(k) | sf(k)=0.1f(k) | (dk=0.025k) | Net investment per worker | (1-s)f(k)=0.9f(k) | gyn =
 | t | [NAME] |  |  |  | Dk=sf(k)-dk |  | (yt-yt-1)/yt-1
 | 1 | 8 | 4 | 0.4 | 0.2 | 0.2 | 3.6 | #N/A
 | 2 | 8.2 | 4.033059350436209 | 0.4033059350436209 | 0.205 | 0.1983059350436209 | 3.629753415392588 | 0.02439024390243894
 | 3 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 4 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 5 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 6 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 7 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 8 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 9 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 10 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 11 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 12 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 13 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 14 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 15 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 16 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 17 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 18 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 19 |  | 0 | 0 | 0 | 0 | 0 | #N/A
 | 20 |  | 0 | 0 | 0 | 0 | 0 | #N/A
Spreadsheet: 870544d1717051039-formula-for-a-table-book1
Sheet: Sheet1

 | Value (000 RON) | Value Share (%) | Average Price (RON/(L/kg))
TOTAL FMCG | 21007786 | 100 | 7.140594482421875
AFTER EPILATION PRODUCTS | 128.7474365234375 | 100 | 85.2431411743164
BRANDED | 128.7474365234375 | 100 | 85.2431411743164
Elmiplant | 46.9742546081543 | 36.48558807373047 | 69.1700439453125
[PHONE] | 46.9742546081543 | 36.48558807373047 | 69.1700439453125
Farmec | 81.77317810058594 | 63.51441192626953 | 98.37460327148438
[PHONE] | 81.77317810058594 | 63.51441192626953 | 98.37460327148438
AFTER SHAVING PRODUCTS | 11563.0283203125 | 100 | 135.4113311767578
BRANDED | 10885.1943359375 | 100 | 139.5795745849609
Adidas | 507.5125122070312 | 4.662411212921143 | 191.5464324951172
[PHONE] | 28.33832740783691 | 0.260338306427002 | 150
[PHONE] | 115.4087066650391 | 1.060235738754272 | 150
[PHONE] | 304.5484313964844 | 2.797822713851929 | 209.6818542480469
[PHONE] | 44.4845085144043 | 0.4086698889732361 | 199.8999938964844
[PHONE] | 43.07088088989258 | 0.3956831693649292 | 209.8999938964844
Avon | 65.8121337890625 | 0.6046022772789001 | 101.6295394897461
AVO0000000003475 | 30.19927787780762 | 0.2774344384670258 | 119.8999938964844
AVO0000000024729 | 35.61285400390625 | 0.3271678388118744 | 90
Brut | 44.60462188720703 | 0.4097733199596405 | 150
[PHONE] | 44.60462188720703 | 0.4097733199596405 | 150
Coral | 20.76680564880371 | 0.1907803118228912 | 39.89999771118164
[PHONE] | 20.76680564880371 | 0.1907803118228912 | 39.89999771118164
D'Amaris | 28.33832740783691 | 0.260338306427002 | 150
[PHONE] | 28.33832740783691 | 0.260338306427002 | 150
[NAME] | 880.108154296875 | 8.085369110107422 | 151.7235260009766
[PHONE] | 199.6584930419922 | 1.834220886230469 | 194.6495666503906
[PHONE] | 273.5282897949219 | 2.512847185134888 | 134.0671081542969
[PHONE] | 265.9579162597656 | 2.443299770355225 | 129.1683654785156
[PHONE] | 121.8371810913086 | 1.119292736053467 | 222.225830078125
[PHONE] | 19.12627983093262 | 0.1757091283798218 | 150
Spreadsheet: 51884d1251472370-rearrange-data-supplied-by-others-book1
Sheet: Sheet1

I need to rearrange the raw data supplied by others to fit into the table below, as indicated by the arrows
~ | The raw data has about 300 entries.
~ | Is there a way to rearrange the data using macros
~ | The address field on the raw data needs seperating into address1, addrerss2,ect.
 | RAW DATA SUPPLIED BY OTHERS
 | Location | Region | LocNo | TradingName | Address | Postcode | OfficeTelNo | FaxNo | Manager | EMail
 | ABERDEEN | S | 152 | Company 1 | 9 Abbotswell Road, [NAME], Aberdeen. | AB12 3AD | 01224 894050 | 01224 877642 | manager 1 | email 1
 | ABERDEEN | S | 570 | Company 2 | 41 Castle Street, Aberdeen | AB11 5EA | 01224 591809 | 01224 578198 | manager 2 | [NAME]
 | ABERYSTWYTH | M | 315 | Company 3 | Unit 5.03,Glanyrafon Industrial Estate, [NAME], Ceredigion. | SY23 3HJ | 01970 627050 | 01970 624175 | manager 3 | [NAME]
 | Customer Business Name | Address 1 | Address 2 | Address 3 | Address 4 | County | Post Code | [NAME]. | Fax No. | [NAME]
Spreadsheet: eric_saibi__9846__100801
Sheet: Onondaga 02

Owner Name | Aquila Energy Corporation
Station Name | [NAME]
Unit Name | Unit 02 ST
NERC Region | NPCC
State | NY
Fuel Type | Steam
Capacity | 25 MW
Start Date | 2001-09-21 00:00:00
End Date | 2001-10-18 00:00:00
Prv. Start Date | 2001-09-21 00:00:00
Prv. End Date | 2001-10-04 00:00:00
Comments | Comb Insp. / Maintenance
SIC | 4931
Plant ID | 1013844
Unit ID | 1011793
Outage ID | 18101
Spreadsheet: 809652d1671200871-wrap-columns-formula-returns-value-wrapcols
Sheet: Imported Data

Date | InvoiceNumber | JobNumber | Labour | Dept
2021-11-01 00:00:00 | 99828 | LK-2328 | 3695.65 | Sales1 | #N/A
2021-11-02 00:00:00 | 28244 | LK-2329 | 445 | Sales1
2021-11-03 00:00:00 | 282861 | LK-2330 | 1072 | Sales1
2021-11-04 00:00:00 | 284328 | LK-2331 | 895 | Sales1
2021-11-05 00:00:00 | 28245 | LK-2332 | 665 | Sales2
2021-11-06 00:00:00 | 282857 | LK-2333 | 1376.01 | Sales2
2021-11-07 00:00:00 | 28495 | LK-2334 | 925 | Sales2
2021-11-08 00:00:00 | 28257 | LK-2335 | 14782.6 | Sales2
2021-11-09 00:00:00 | 282892 | LK-2336 | 3695.65 | Sales2
2021-11-10 00:00:00 | 28599 | LK-2337 | 495 | Sales2
2021-11-11 00:00:00 | 28795 | LK-2338 | 2050.92 | Sales2
2021-11-12 00:00:00 | 9894 | LK-2339 | 3400.01 | Sales3
2021-11-13 00:00:00 | 282829 | LK-2340 | 739.13 | Sales3
2021-11-14 00:00:00 | 9881 | LK-2341 | 2660.87 | Sales3
2021-11-15 00:00:00 | 99288 | LK-2342 | 1847.83 | Sales3
2021-11-16 00:00:00 | 9879 | LK-2343 | 147.83 | Sales3
2021-11-17 00:00:00 | 9877 | LK-2344 | 2365.22 | Sales3
2021-11-18 00:00:00 | 9851 | LK-2345 | 1847.83 | Sales4
2021-11-19 00:00:00 | 99286 | LK-2346 | 3769.57 | Sales4
2021-11-20 00:00:00 | 9924 | LK-2347 | 1847.83 | Sales4
2021-11-21 00:00:00 | 98928 | LK-2348 | 1478.26 | Sales4
Spreadsheet: 792719d1661098486-summarizing-weeklies-into-a-monthly-2022-08-21-oeldere2-ryba-testrunyearxls
Sheet: KW01

ID | Name | Mon | Tue | Wed | Thu | Fri | Sat | Sun
Week01
100 | [NAME] | 8 | 5 | 6 | 8 | 10 | 0 | 0
101 | [NAME] | 5 | 5 | 5 | 5 | 5 | 5 | 5
102 | Fredericson | 8 | 4 | 8 | 4 | 6 | 6 | 0
103 | [NAME] | 6 | 6 | 6 | 6 | 6 | 0 | 0