Ayushnangia/finbench-data huggingface dataset:
|(In Millions)|Dec 29, 2018|Acquisitions|Transfers|Other|Dec 28, 2019|
|Data Center Group|$5,424|$1,758|$—|$—|$7,155|
|Internet of Things Group|1,579|—|—|—|1,579|
|Mobileye|10,290|—|—|—|10,290|
|Programmable Solutions Group|2,579|67|—|8|2,681|
|Client Computing Group|4,403|—|—|(70)|4,333|
|All other|238|—|—|—|238|
|Total|$24,513|$1,825|$—|$(62)|$26,276|
|(In Millions)|Dec 30, 2017|Acquisitions|Transfers|Other|Dec 29, 2018|
|Data Center Group|$5,421|$3|$—|$—|$5,424|
|Internet of Things Group|1,126|16|480|(43)|1,579|
|Mobileye|10,278|7|—|5|10,290|
|Programmable Solutions Group|2,490|89|—|—|2,579|
|Client Computing Group|4,356|47|—|—|4,403|
|All other|718|—|(480)|—|238|
|Total|$24,389|$162|$—|$(38)|$24,513|
 Goodwill activity for each period was as follows: During the third quarter of 2018, we made an organizational change to combine our AI investments in edge computing with IOTG; accordingly, approximately $480 million of goodwill was reallocated from “all other” to the IOTG operating segment. During the fourth quarters of 2019 and 2018, we completed our annual impairment assessments and we concluded that goodwill was not impaired in either of these years. The accumulated impairment loss as of December 28, 2019 was $719 million: $365 million associated with CCG, $275 million associated with DCG, and $79 million associated with IOTG.


Question: How much is the percentage change of total goodwill amount from 2017 to 2018? (in percent)

Python solution:
def solution():
    # Define variables name and value
    total_goodwill_2017 = 24389
    total_goodwill_2018 = 24513
    
    # Do math calculation to get the answer
    answer = (total_goodwill_2018 - total_goodwill_2017) / total_goodwill_2017 * 100
    
    return answer

Answer: 0.5084259297
|||Fiscal|
||2019|2018|
|||(in millions)|
|Acquisition-related charges:|||
|Acquisition and integration costs|$  27|$  14|
|Charges associated with the amortization of acquisition related fair value adjustments|3|8|
||30|22|
|Restructuring and other charges, net|255|126|
|Other items(1)|17|—|
|Total|$  302|$  148|
 Operating income included the following: (1) Represents the write-off of certain spare parts. See discussion of operating income below under “Segment Results.”


Question: What was the change in Total operating income in 2019 from 2018? (in million)

Python solution:
def solution():
    # Define variables name and value
    operating_income_2019 = 302
    operating_income_2018 = 148
    
    # Do math calculation to get the answer
    answer = operating_income_2019 - operating_income_2018
    
    return answer

Answer: 154
||2019||2018||
||NUMBER||NUMBER||
|SHARE CAPITAL|M|$M|M|$M|
|1,258,690,067 fully paid ordinary shares (2018: 1,313,323,941)|||||
|Movement:|||||
|Balance at start of period|1,313.3|6,201|1,294.4|5,719|
|Share buy-back|(58.7)|(282)|–|–|
|Issue of shares to satisfy the dividend reinvestment plan|4.1|114|18.9|482|
|Balance at end of period|1,258.7|6,033|1,313.3|6,201|
|SHARES HELD IN TRUST|||||
|Movement:|||||
|Balance at start of period|(4.9)|(146)|(3.4)|(104)|
|Issue of shares to satisfy employee long-term incentive plans|0.2|6|0.6|21|
|Issue of shares to satisfy the dividend reinvestment plan|(0.2)|(5)|(0.1)|(3)|
|Purchase of shares by the Woolworths Employee Share Trust|(2.0)|(60)|(2.0)|(60)|
|Balance at end of period|(6.9)|(205)|(4.9)|(146)|
|Contributed equity at end of period|1,251.8|5,828|1,308.4|6,055|
 Contributed equity represents the number of ordinary shares on issue less shares held by the Group. A reconciliation is presented to show the total number of ordinary shares held by the Group which reduces the amount of total shares traded on-market. On 27 May 2019, the Group completed an off-market share buy-back of 58,733,844 ordinary shares. The ordinary shares were bought back at $28.94, representing a 14% discount to the Group’s market price of $33.64 (being the volume weighted average price of the Group’s ordinary shares over the five trading days up to and including the closing date of 24 May 2019), and comprised a fully franked dividend component of $24.15 per share ($1,419 million) and a capital component of $4.79 per share ($282 million), including $1 million of associated transaction costs (net of tax). The shares bought back were subsequently cancelled. Holders of ordinary shares are entitled to receive dividends as declared and are entitled to one vote per share at shareholders’ meetings. In the event of winding up of the Company, ordinary shareholders rank after creditors and are fully entitled to any proceeds of liquidation. Refer to Note 6.2 for further details of outstanding options and performance rights. Performance rights carry no rights to dividends and no voting rights.


Question: What is the nominal difference in contributed equity between 2018 and 2019 in terms of $M ? (in million)

Python solution:
def solution():
    # Define variables name and value
    contributed_equity_2018 = 6055
    contributed_equity_2019 = 5828
    
    # Do math calculation to get the answer
    answer = contributed_equity_2018 - contributed_equity_2019
    
    return answer

Answer: 227
|December 31, 2019|||||
||Quoted Prices in Active Markets (Level 1)|Significant Other Observable Inputs (Level 2)|Significant Unobservable Inputs (Level 3)|Total Fair Value|
|Assets:|||||
|Money market funds|$—|$2,010|$—|$2,010|
|U.S. treasury bonds|—|116,835|—|116,835|
|Commercial paper|—|44,300|—|44,300|
|Certificates of deposit|—|24,539|—|24,539|
|Asset-backed securities|—|73,499|—|73,499|
|Corporate debt securities|—|181,079|—|181,079|
|Total|$—|442,262|—|442,262|
 FAIR VALUE MEASUREMENT The Company measures certain financial assets and liabilities at fair value. Fair value is determined based upon the exit price that would be received to sell an asset or paid to transfer a liability in an orderly transaction between market participants, as determined by either the principal market or the most advantageous market. Inputs used in the valuation techniques to derive fair values are classified based on a three-level hierarchy, as follows: Level 1—Quoted prices (unadjusted) in active markets for identical assets or liabilities. Level 2—Observable inputs other than Level 1 prices such as quoted prices for similar assets or liabilities, quoted prices in markets with insufficient volume or infrequent transactions (less active markets), or model-derived valuations in which all significant inputs are observable or can be derived principally from or
corroborated by observable market data for substantially the full term of the assets or liabilities. Level 3—Unobservable inputs to the valuation methodology that are significant to the measurement of fair value of assets or liabilities. The Company considers all highly liquid investments purchased with an original maturity of three months or less to be cash equivalents. The Company’s investments are in money market funds, U.S. treasury bonds, commercial paper, certificates of deposit, asset-backed securities and corporate debt securities, which are classified as Level 2 within the fair value hierarchy, and were initially valued at the transaction price and subsequently valued at each reporting date utilizing market-observable data. The market-observable data included reportable trades, benchmark yields, credit spreads, broker/dealer quotes, bids, offers, current spot rates and other industry and economic events. The fair value of these assets measured on a recurring basis was determined using the following inputs as ofDecember 31, 2019 and 2018 (in thousands):


Question: What proportion of level 2 inputs is made up of money market funds?  (in percent)

Python solution:
def solution():
    # Define variables name and value
    money_market_funds = 2010
    total_level_2 = 442262

    # Do math calculation to get the answer
    answer = (money_market_funds / total_level_2) * 100
    
    return answer

Answer: 0.4544817325
|||Years Ended March 31,||
||2019|2018|2017|
|Swiss|$212,986|$177,935|$161,544|
|Non-Swiss|58,147|54,330|53,445|
|Income before taxes|$271,133|$232,265|$214,989|
 Note 7—Income Taxes The
Company
is
incorporated
in
Switzerland
but
operates
in
various
countries
with
differing
tax
laws
and
rates.
Further,
a
portion
of
the
Company's
income
(loss)
before
taxes
and
the
provision
for
(benefit
from)
income
taxes
is
generated
outside
of
Switzerland. Income
from
continuing
operations
before
income
taxes
for
fiscal
years
2019
,
2018
and
2017
is
summarized
as
follows
(in
thousands):


Question: What is the average of the Non-Swiss income from 2017 to 2019 (in thousand)

Python solution:
def solution():
    # Define variables name and value
    non_swiss_2019 = 58147
    non_swiss_2018 = 54330
    non_swiss_2017 = 53445

    # Do math calculation to get the average Non-Swiss income
    answer = (non_swiss_2019 + non_swiss_2018 + non_swiss_2017) / 3

    return answer

Answer: 55307.3333333333
||December 31,||
||2019|2018|
|Accounted for at cost, adjusted for observable price changes|$1,750|$1,250|
|Accounted for using the equity method|8,000|—|
|Total non-marketable investments|$9,750|$1,250|
 Strategic Investments In December 2019, the Company made a minority investment in a privately-held company, Talespin, Inc., for $8.0 million, representing approximately 13% equity ownership. The investment is accounted for using the equity method of accounting due to the Company’s ability to exercise significant influence. The Company’s non-marketable investments are composed of the following (in thousands):


Question: What percentage of total non-marketable investments were accounted for using the equity method in 2019? (in percent)

Python solution:
def solution():
    # Define variables name and value
    equity_method_investment = 8000
    total_non_marketable_investments = 9750
    
    # Do math calculation to get the answer
    answer = (equity_method_investment / total_non_marketable_investments) * 100
    
    return answer

Answer: 82.0512820513
|(In thousands)|2019|2018|2017|
|United States|$300,853|$288,843|$508,178|
|Mexico|90,795|12,186|2,246|
|Germany|78,062|167,251|119,502|
|Other international|60,351|60,997|36,974|
|Total|$530,061|$529,277|$666,900|
 Additional Information The following table presents sales information by geographic area for the years ended December 31, 2019, 2018 and 2017: Customers comprising more than 10% of revenue can change from year to year. Single customers comprising more than 10% of our revenue in 2019 included three customers at 19%, 17% and 13%. Single customers comprising more than 10% of our revenue in 2018 included two customers at 27% and 17%. Single customers comprising more than 10% of our revenue in 2017 included two customers at 40% and 16%. Other than those with more than 10% of revenues disclosed above, and excluding distributors, our next five largest customers can change, and has historically changed, from year-to-year. These combined customers represented 15%, 18% and 15% of total revenue in 2019, 2018 and 2017, respectively. As of December 31, 2019, property, plant and equipment, net totaled $73.7 million, which included $69.9 million held in the U.S. and $3.9 million held outside the U.S. As of December 31, 2018, property, plant and equipment, net totaled $80.6 million, which included $77.3 million held in the U.S. and $3.3 million held outside the U.S. Property, plant and equipment, net is reported on a company-wide, functional basis only.


Question: What was the percentage change in total sales between 2018 and 2019? (in percent)

Python solution:
def solution():
    # Define variables name and value
    sales_2019 = 530061
    sales_2018 = 529277
    
    # Do math calculation to get the answer
    answer = (sales_2019 - sales_2018) / sales_2018 * 100
    
    return answer

Answer: 0.1481265953
||December 31,||
||2018|2019|
|Wages and salaries|158,371|191,459|
|Social security|14,802|17,214|
|Pension expenses|6,937|8,408|
|Share-based payment expenses|8,215|10,538|
|Restructuring expenses|178|108|
|Total|188,503|227,727|
 Personnel expenses for employees were as follows: Personnel expenses are included in cost of sales and in operating expenses in the consolidated statement of profit or loss.


Question: What is the change in total personnel expenses from 2018 to 2019?

Python solution:
def solution():
    # Define variables name and value
    total_personnel_expenses_2018 = 188503
    total_personnel_expenses_2019 = 227727

    # Do math calculation to get the answer
    answer = total_personnel_expenses_2019 - total_personnel_expenses_2018
    
    return answer

Answer: 39224
the fair value of the psu award at the date of grant is amortized to expense over the performance period , which is typically three years after the date of the award , or upon death , disability or reaching the age of 58 . as of december 31 , 2017 , pmi had $ 34 million of total unrecognized compensation cost related to non-vested psu awards . this cost is recognized over a weighted-average performance cycle period of two years , or upon death , disability or reaching the age of 58 . during the years ended december 31 , 2017 , and 2016 , there were no psu awards that vested . pmi did not grant any psu awards during note 10 . earnings per share : unvested share-based payment awards that contain non-forfeitable rights to dividends or dividend equivalents are participating securities and therefore are included in pmi 2019s earnings per share calculation pursuant to the two-class method . basic and diluted earnings per share ( 201ceps 201d ) were calculated using the following: . 
||For the Years Ended December 31,|
|(in millions)|2017|2016|2015|
|Net earnings attributable to PMI|$6,035|$6,967|$6,873|
|Less distributed and undistributed earnings attributable to share-based payment awards|14|19|24|
|Net earnings for basic and diluted EPS|$6,021|$6,948|$6,849|
|Weighted-average shares for basic EPS|1,552|1,551|1,549|
|Plus contingently issuable performance stock units (PSUs)|1|—|—|
|Weighted-average shares for diluted EPS|1,553|1,551|1,549|
 for the 2017 , 2016 and 2015 computations , there were no antidilutive stock options. .


Question: what is the growth rate of the net earnings for basic and diluted eps? (in percentage)

Python solution:
def solution():
    # Define variables name and value
    net_earnings_2016 = 6948
    net_earnings_2017 = 6021
    
    # Do math calculation to get the answer
    growth_rate_net_earnings = ((net_earnings_2017 - net_earnings_2016) / net_earnings_2016) * 100
    
    return growth_rate_net_earnings

Answer: -13.3419689119
in the ordinary course of business , based on our evaluations of certain geologic trends and prospective economics , we have allowed certain lease acreage to expire and may allow additional acreage to expire in the future . if production is not established or we take no other action to extend the terms of the leases , licenses or concessions , undeveloped acreage listed in the table below will expire over the next three years . we plan to continue the terms of certain of these licenses and concession areas or retain leases through operational or administrative actions ; however , the majority of the undeveloped acres associated with other africa as listed in the table below pertains to our licenses in ethiopia and kenya , for which we executed agreements in 2015 to sell . the kenya transaction closed in february 2016 and the ethiopia transaction is expected to close in the first quarter of 2016 . see item 8 . financial statements and supplementary data - note 5 to the consolidated financial statements for additional information about this disposition . net undeveloped acres expiring year ended december 31 . 
||Net Undeveloped Acres Expiring Year Ended December 31,|
|(In thousands)|2016|2017|2018|
|U.S.|68|89|128|
|E.G.|—|92|36|
|Other Africa|189|4,352|854|
|Total Africa|189|4,444|890|
|Other International|—|—|—|
|Total|257|4,533|1,018|
 .


Question: what was total net undeveloped acres expiring for the three year period , in thousands? (in thousand)

Python solution:
def solution():
    # Define variables name and value
    total_2016 = 257
    total_2017 = 4533
    total_2018 = 1018
    
    # Do math calculation to get the answer
    answer = total_2016 + total_2017 + total_2018
    
    return answer

Answer: 5808
|||Payments due by period||||
||Up to 1 year|1 to 3 years|3 to 5 years|More than 5 years|Total|
|Operating lease obligations|16,164|19,812|6,551|5,883|48,410|
|Financing obligations|2,956|5,912|—|—|8,868|
|Long-term debt|—|—|460,000|—|460,000|
|Purchase obligations|55,755|16,220|7,595|17,649|97,219|
|Total|74,875|41,944|474,146|23,532|614,497|
 Contractual Obligations The following summarizes our contractual obligations as of December 31, 2019 (in thousands): Purchase obligations represent an estimate of open purchase orders and contractual obligations in the normal course of business for which we have not received the goods or services as of December 31, 2019. Although open purchase orders are considered enforceable and legally binding, except for our purchase orders with our inventory suppliers, the terms generally allow us the option to cancel, reschedule, and adjust our requirements based on our business needs prior to the delivery of goods or performance of services. Our purchase orders with our inventory suppliers are non-cancellable. In addition, we have other obligations for goods and services that we enter into in the normal course of business. These obligations, however, are either not enforceable or legally binding, or are subject to change based on our business decisions. The aggregate of these items represents our estimate of purchase obligations.


Question: What is the value of the company's total financing obligations as a percentage of its total purchase obligations? (in percent)

Python solution:
def solution():
    # Define variables name and value
    financing_obligations = 8868
    purchase_obligations = 97219
    
    # Do math calculation to get the answer
    answer = (financing_obligations / purchase_obligations) * 100
    
    return answer

Answer: 9.1216737469
||For the Twelve Months Ended December 31,||
||2019|2018|
||(Dollars in thousands)||
|Cash and cash equivalents|9,472|7,554|
|Accounts receivable, net of allowance for doubtful accounts|18,581|12,327|
|Inventories, net|12,542|9,317|
|Prepaid expenses|3,276|1,078|
|Other current assets|10,453|682|
|Accounts payable|(18,668)|(9,166)|
|Accrued expenses|(22,133)|(9,051)|
|Current operating lease liabilities|(1,185)|—|
|Total Working Capital|$12,338|$12,741|
 The following table sets forth, for the periods indicated, our working capital: Working Capital consists of current assets net of current liabilities. Working capital decreased $0.4 million to $12.3 million at December 31, 2019 compared with $12.7 million at December 31, 2018. The decrease was primarily a result of an increase of cash, accounts receivable, and inventory offset by an increase in accounts payable, accrued expenses and current operating lease liabilities. We normally carry three to four weeks of finished goods inventory. The average duration of our accounts receivable is approximately 25 days. For the year ended December 31, 2019 our capital resources consisted of primarily $9.5 million cash on hand and $33.0 million available under our credit facilities, net of $2.0 million reserved for two letters of credit. For the year ended December 31, 2018, our capital resources consisted primarily of $7.5 million cash on hand and $30.0 million available under our credit facilities. The Credit Facilities will mature in May 2024. We borrowed $72.3 million under our credit facilities during 2019, of which $18.5 million was repaid prior to the end of the year. As of December 31, 2019, we had $54.5 million of debt outstanding (including $0.7 million of debt issuance costs) under our credit facilities. There was no debt outstanding under the credit facilities as of December 31, 2018.


Question: What was the percentage change in accounts payables from 2018 to 2019 year end? (in percent)

Python solution:
def solution():
    # Define variables name and value
    accounts_payable_2019 = -18668
    accounts_payable_2018 = -9166
    
    # Do math calculation to get the answer
    answer = (accounts_payable_2019 - accounts_payable_2018) / accounts_payable_2018 * 100
    
    return answer

Answer: 103.6657211434
|||Net additions (losses)||% of penetration(2)(3)||
||August 31, 2019|August 31, 2019|August 31, 2018 (1)|August 31, 2019|August 31, 2018 (3)|
|Primary service units|901,446|16,981|20,251|||
|Internet service customers|446,137|21,189|21,417|50.8|49.7|
|Video service customers|312,555|(4,697)|(6,760)|35.6|37.1|
|Telephony service customers|142,754|489|5,594|16.2|16.6|
 CUSTOMER STATISTICS (1) Excludes 251,379 primary services units (130,404 Internet services, 87,873 video services and 33,102 telephony services) from the MetroCast acquisition completed in the second quarter of fiscal 2018. (2) As a percentage of homes passed. (3) In the first quarter of fiscal 2019, the number of homes passed in the American broadband services segment have been adjusted upwards in order to reflect the number of non-served multi-dwelling unit passings within the footprint and consequently, the penetration as a percentage of homes passed for fiscal 2018 have also been adjusted. INTERNET Fiscal 2019 Internet service customers net additions stood at 21,189 compared to 21,417 for the prior year as a result of: • additional connects related to the Florida expansion initiatives and in the MetroCast footprint; • our customers' ongoing interest in high speed offerings; and • growth in both the residential and business sectors. VIDEO Fiscal 2019 video service customers net losses stood at 4,697 compared to 6,760 for the prior year mainly from: • competitive offers in the industry; and • a changing video consumption environment; partly offset by • our customers' ongoing interest in TiVo's digital advanced video services; and • the activation of bulk properties in Florida during the fourth quarter of fiscal 2019. TELEPHONY Fiscal 2019 telephony service customers net additions stood at 489 compared to 5,594 for the prior year mainly as a result of the growth in the business sector, partly offset by a decline in the residential sector. DISTRIBUTION OF CUSTOMERS At August 31, 2019, 52% of the American broadband services segment's customers enjoyed "double play" or "triple play" bundled services.


Question: What is the increase / (decrease) in the primary service units  in net additions(losses) from 2018 to 2019?

Python solution:
def solution():
    # Define variables name and value
    net_additions_2019 = 16981
    net_additions_2018 = 20251
    
    # Do math calculation to get the answer
    answer = net_additions_2019 - net_additions_2018
    
    return answer

Answer: -3270