Ayushnangia/finbench-data huggingface dataset:
||APAC|||
|Sales Mix|2019|2018|%Change|
|Hardware|$34,965|$29,496|19%|
|Software|92,988|107,363|(13%)|
|Services|52,288|50,055|4%|
||$180,241|$186,914|(4%)|
 Our net sales by offering category for APAC for 2019 and 2018, were as follows (dollars in thousands): Net sales in APAC decreased 4% (increased 2% excluding the effects of fluctuating foreign currency rates), or $6.7 million, in 2019 compared to 2018. In APAC, increases in hardware and services net sales year over year were offset by a decrease in software net sales during 2019 compared to 2018. The changes were the result of the following: • Continued expansion of hardware offerings in the APAC market resulted in higher net sales in this category. • Continued trend toward higher sales of cloud solution offerings that are recorded on a net sales recognition basis in the services net sales category resulted in declines in the software net sales category. • Higher volume of net sales of cloud solution offerings and software referral fees that are recorded on a net sales recognition basis positively impacted services net sales. Additionally, there were contributions from Insight delivered services from increased net sales of our digital innovation solutions offering.


Question: If the Sales Mix of Hardware in 2019 increased to 65,674 thousand, what would be the revised change between 2018 and 2019? (in thousand)

Python solution:
def solution():
    # Define variables name and value
    hardware_sales_2019 = 65674
    hardware_sales_2018 = 29496
    
    # Do math calculation to get the answer
    answer = hardware_sales_2019 - hardware_sales_2018
    
    return answer

Answer: 36178
||Year-ended 31 March 2019||Year-ended 31 March 2018||
||Number|WASP|Number|WASP|
|Restricted share units|000’s|£ pence|000’s|£ pence|
|Outstanding at the start of the year|14,840|316.09|15,350|215.92|
|Awarded|8,749|478.44|6,337|453.14|
|Forfeited|(1,421)|426.11|(1,421)|284.15|
|Released|(6,822)|309.77|(5,426)|218.49|
|Outstanding at the end of the year|15,346|401.27|14,840|316.09|
 Restricted Share Units The following table illustrates the number and WASP on date of award, and movements in, restricted share units (“RSUs”) and cash-based awards granted under the 2015 LTIP: RSUs and cash-based awards have a vesting period between two to five years, with no award vesting within the first 12 months of the grant.


Question: What would the percentage change in the number of RSUs and cash-based awards outstanding at the end of the year in 2019 from 2018 be if the amount in 2019 was 15,340 thousand instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    num_2019 = 15340
    num_2018 = 14840
    
    # Do math calculation to get the answer
    answer = (num_2019 - num_2018) / num_2018 * 100
    
    return answer

Answer: 3.3692722372
|($ in millions)||||
|For the year ended December 31:|2019|2018|Yr.-to-Yr. Percent Change|
|Retirement-related plans—cost||||
|Service cost|$385|$431|(10.7)%|
|Multi-employer plans|32|38|(16.9)|
|Cost of defined contribution plans|1,040|1,024|1.5|
|Total operating costs/ (income)|$1,457|$1,494|(2.5)%|
|Interest cost|$2,929|$2,726|7.4%|
|Expected return on plan assets|(4,192)|(4,049)|3.5|
|Recognized actuarial losses|1,819|2,941|(38.2)|
|Amortization of prior service costs/(credits)|(9)|(73)|(87.6)|
|Curtailments/settlements|41|11|262.2|
|Other costs|28|16|76.2|
|Total non-operating costs/(income)|$615|$1,572|(60.9)%|
|Total retirement-related plans—cost|$2,072|$3,066|(32.4)%|
 Retirement-Related Plans The following table provides the total pre-tax cost for all retirement-related plans. Total operating costs/(income) are included in the Consolidated Income Statement within the caption (e.g., Cost, SG&A, RD&E) relating to the job function of the plan participants. Total pre-tax retirement-related plan cost decreased by $994 million compared to 2018, primarily driven by a decrease in recognized actuarial losses ($1,123 million), primarily due to the change in the amortization period in the U.S. Qualified Personal Pension Plan and higher expected return on plan assets ($143 million), partially offset by higher interest costs ($203 million). As discussed in the “Operating (non-GAAP) Earnings” section, we characterize certain retirement-related costs as operating and others as non-operating. Utilizing this characterization, operating retirement-related costs in 2019 were $1,457 million, a decrease of $37 million compared to 2018. Non-operating costs of $615 million in 2019 decreased $957 million year to year, driven primarily by the same factors as above.


Question: If interest cost in 2019 increased to 3,000 million, what was the revised average? (in million)

Python solution:
def solution():
    # Define variables name and value
    interest_cost_2019 = 3000
    interest_cost_2018 = 2726
    
    # Do math calculation to get the answer
    answer = (interest_cost_2019 + interest_cost_2018) / 2
    
    return answer

Answer: 2863
||||Year Ended December 31|||
||2019|% Change|2018|% Change|2017|
||||(In thousands, except percentage data)|||
|Cost of revenue|$704,535|(1.8)%|$717,118|(2.0)%|$731,453|
|Gross margin percentage|29.5%||32.3%||29.6%|
 2019 vs 2018 Cost of revenue decreased for the year ended December 31, 2019, compared to the prior year, primarily due to net revenue declining. Gross margin decreased for the year ended December 31, 2019 compared to the prior year. Gross margin was negatively impacted by the imposition of Section 301 tariffs originally announced in late 2018 and cost inefficiencies experienced in our new manufacturing locations outside of China, an increase in channel promotional activities relative to revenue as well as foreign exchange headwinds due to the strengthening of the U.S. dollar. 2018 vs 2017 Cost of revenue decreased for the year ended December 31, 2018 primarily due to improved product margin performance, lower proportionate provisions for warranty expense, and lower air freight costs compared to the prior year. Gross margin increased for the year ended December 31, 2018 compared to the prior year primarily due to improved product margin performance, lower proportionate provisions for sales returns and warranty expense, favorable foreign exchange rate movements and lower air freight costs compared to the prior year. For fiscal 2020, we expect gross margins to improve from fiscal 2019 primarily as our U.S. bound inventory will primarily not be subject to Section 301 tariffs in fiscal 2020. Forecasting gross margin percentages is difficult, and there are a number of risks related to our ability to maintain or improve our current gross margin levels. Our cost of revenue as a percentage of net revenue can vary significantly based upon factors such as: uncertainties surrounding revenue levels, including future pricing and/or potential discounts as a result of the economy or in response to the strengthening of the U.S. dollar in our international markets, and related production level variances; import customs duties and imposed tariffs; competition; changes in technology; changes in product mix; variability of stockbased compensation costs; royalties to third parties; fluctuations in freight and repair costs; manufacturing and purchase price variances; changes in prices on commodity components; warranty costs; and the timing of sales, particularly to service provider customers. We expect that revenue derived from paid subscription service plans will increase in the future, which may have a positive impact on our gross margin. From time to time, however, we may experience fluctuations in our gross margin as a result of the factors discussed above.


Question: What was the percentage change in cost of revenue from 2017 to 2019 if the cost of revenue is 742,365 in 2019? (in percent)

Python solution:
def solution():
    # Define variables name and value
    cost_of_revenue_2019 = 742365
    cost_of_revenue_2017 = 731453
    
    # Do math calculation to get the answer
    answer = (cost_of_revenue_2019 - cost_of_revenue_2017) / cost_of_revenue_2017 * 100
    
    return answer

Answer: 1.4918251754
|At/for the year ended 31 March|2019|2018|2017|2016|2015|
|Consolidated income statement data (€m)||||||
|Revenue|43,666|46,571|47,631|49,810|48,385|
|Operating (loss)/profit|(951)|4,299|3,725|1,320|2,073|
|(Loss)/profit before taxation|(2,613)|3,878|2,792|(190)|1,734|
|(Loss)/profit for financial year from continuing operations|(4,109)|4,757|(1,972)|(5,127)|7,805|
|(Loss)/profit for the financial year|(7,644)|2,788|(6,079)|(5,122)|7,477|
|Consolidated statement of financial position data (€m)||||||
|Total assets|142,862|145,611|154,684|169,107|169,579|
|Total equity|63,445|68,607|73,719|85,136|93,708|
|Total equity shareholders’ funds|62,218|67,640|72,200|83,325|91,510|
|Earnings per share1,2||||||
|Weighted average number of shares (millions)||||||
|– Basic|27,607|27,770|27,971|26,692|26,489|
|– Diluted|27,607|27,857|27,971|26,692|26,629|
|Basic (loss)/earnings per ordinary share|(29.05)c|8.78c|(22.51)c|(20.25)c|27.48c|
|Diluted (loss)/earnings per ordinary share|(29.05)c|8.76c|(22.51)c|(20.25)c|27.33c|
|Basic (loss)/earnings per share from continuing operations|(16.25)c|15.87c|(7.83)c|(20.27)c|28.72c|
|Cash dividends1,3||||||
|Amount per ordinary share (eurocents)|9.00c|15.07c|14.77c|–|–|
|Amount per ADS (eurocents)|9.00c|15.07c|147.7c|–|–|
|Amount per ordinary share (pence)|–|–|–|11.45p|11.22p|
|Amount per ADS (pence)|–|–|–|114.5p|111.2p|
|Amount per ordinary share (US cents)|10.10c|17.93c|18.52c|16.49c|16.65c|
|Amount per ADS (US cents)|10.10c|179.3c|182.5c|164.9c|166.5c|
 Selected financial data Unaudited information The selected financial data shown below include the results of Vodafone India as discontinued operations in all years following the agreement to combine it with Idea Cellular. Notes: 1 See note 8 to the consolidated financial statements, “Earnings per share”. Earnings and dividends per ADS is calculated by multiplying earnings per ordinary share by ten, the number of ordinary shares per ADS. 2 On 19 February 2014, we announced a “6 for 11” share consolidation effective 24 February 2014. This had the effect of reducing the number of shares in issue from 52,821,751,216 ordinary shares (including 4,351,833,492 ordinary shares held in Treasury) as at the close of business on 18 February 2014 to 28,811,864,298 new ordinary shares in issue immediately after the share consolidation on 24 February 2014. 3 The final dividend for the year ended 31 March 2019 was proposed by the Directors on 14 May 2019 and is payable on 2 August 2019 to holders of record as of 7 June 2019. The total dividends have been translated into US dollars at 31 March 2019 for purposes of the above disclosure but the dividends are payable in US dollars under the terms of the ADS depositary agreement.


Question: What would be the average revenue for 2017 and 2018 if 2017 revenue was 47,000 €m? (in million)

Python solution:
def solution():
    # Define variables name and value
    revenue_2017 = 47000
    revenue_2018 = 46571
    
    # Do math calculation to get the answer
    answer = (revenue_2017 + revenue_2018) / 2
    
    return answer

Answer: 46785.5
||June 1, 2019|June 2, 2018|
|Land and improvements|$93,046|$90,757|
|Buildings and improvements|370,451|360,030|
|Machinery and equipment|496,166|478,997|
|Construction-in-progress|52,551|9,307|
||1,012,214|939,091|
|Less: accumulated depreciation|555,920|513,707|
||$456,294|$425,384|
 6. Property, Plant and Equipment Property, plant and equipment consisted of the following (in thousands): Depreciation expense was $51.7 million, $51.1 million and $48.8 million in fiscal years 2019, 2018 and 2017, respectively. The Company maintains insurance for both property damage and business interruption relating to catastrophic events, such as fires. Insurance recoveries received for property damage and business interruption in excess of the net book value of damaged assets, clean-up and demolition costs, and post-event costs are recognized as income in the period received or committed when all contingencies associated with the recoveries are resolved. Gains on insurance recoveries related to business interruption are recorded within “Cost of sales” and any gains or losses related to property damage are recorded within “Other income (expense).” Insurance recoveries related to business interruption are classified as operating cash flows and recoveries related to property damage are classified as investing cash flows in the statement of cash flows. Insurance claims incurred or finalized during the fiscal years ended 2019, 2018, and 2017 did not have a material affect on the Company's consolidated financial statements.


Question: If the building and improvements increases by 10% in 2019, what is the revised average? (in thousand)

Python solution:
def solution():
    # Define variables name and value
    buildings_and_improvements_2019 = 370451
    buildings_and_improvements_2018 = 360030
    increase_percentage = 0.1

    # Do math calculation to get the answer
    revised_building_and_improvements_2019 = buildings_and_improvements_2019 * (1 + increase_percentage)
    answer = (revised_building_and_improvements_2019 + buildings_and_improvements_2018) / 2

    return answer

Answer: 383763.05
|All amounts in USD ‘000 |2019|2018|2017|
|Spot charter revenues*|283,007|259,978|257,495|
|Time charter revenues  |34,213|29,038|39,646|
|Total Voyage Revenues  |317,220|289,016|297,141|
 3. VOYAGE REVENUES Our voyage revenues consist of time charter revenues and spot charter revenues with the following split: *Spot charter revenues for 2019 and 2018 are presented in accordance we ASC 606 Revenue from Contracts with Customers. The comparative information for 2017 has not been restated.


Question: What would be the value of the 2019 total voyage revenue as a percentage of the 2018 total voyage revenues if the 2018 total voyage revenue is instead $300,000,000? (in percent)

Python solution:
def solution():
    # Define variables name and value
    voyage_revenue_2019 = 317220
    adjusted_voyage_revenue_2018 = 300000
    
    # Do math calculation to get the answer
    answer = (voyage_revenue_2019 / adjusted_voyage_revenue_2018) * 100
    
    return answer

Answer: 105.74
|||As of December 31,||
||Useful life in years|2019|2018|
|Furniture and equipment|5|$1,785|$1,189|
|Leasehold improvements (1)|5|4,074|2,776|
|System hardware|5|1,596|1,404|
|Office computers|3|5,309|3,745|
|Computer and system software|3|1,451|1,385|
|||14,215|10,499|
|Less accumulated depreciation and amortization||(7,931)|(5,849)|
|Property and equipment, net||$6,284|$4,650|
 Property and equipment consist of the following (in thousands): (1) Lesser of the lease term or the estimated useful lives of the improvements, which generally may be up to 5 years. Depreciation and amortization expense for the years ended December 31, 2019, 2018 and 2017 was $2.2 million, $1.8 million and $1.9 million, respectively.


Question: If the Furniture and equipment in December 31, 2019 increased to 1,914 thousand, what would be the revised change? (in thousand)

Python solution:
def solution():
    # Define variables name and value
    furniture_equipment_2019 = 1914
    furniture_equipment_2018 = 1189
    
    # Do math calculation to get the answer
    answer = furniture_equipment_2019 - furniture_equipment_2018
    
    return answer

Answer: 725
||APAC|||
|Sales Mix|2019|2018|%Change|
|Hardware|$34,965|$29,496|19%|
|Software|92,988|107,363|(13%)|
|Services|52,288|50,055|4%|
||$180,241|$186,914|(4%)|
 Our net sales by offering category for APAC for 2019 and 2018, were as follows (dollars in thousands): Net sales in APAC decreased 4% (increased 2% excluding the effects of fluctuating foreign currency rates), or $6.7 million, in 2019 compared to 2018. In APAC, increases in hardware and services net sales year over year were offset by a decrease in software net sales during 2019 compared to 2018. The changes were the result of the following: • Continued expansion of hardware offerings in the APAC market resulted in higher net sales in this category. • Continued trend toward higher sales of cloud solution offerings that are recorded on a net sales recognition basis in the services net sales category resulted in declines in the software net sales category. • Higher volume of net sales of cloud solution offerings and software referral fees that are recorded on a net sales recognition basis positively impacted services net sales. Additionally, there were contributions from Insight delivered services from increased net sales of our digital innovation solutions offering.


Question: If the Sales Mix of Hardware in 2019 increased to 65,674 thousand, what would be the revised average for 2018 and 2019? (in thousand)

Python solution:
def solution():
    # Define variables name and value
    hardware_sales_2019 = 65674
    hardware_sales_2018 = 29496
    
    # Do math calculation to get the answer
    answer = (hardware_sales_2019 + hardware_sales_2018) / 2
    
    return answer

Answer: 47585
|Name|No. of Securities Underlying Unexercised Options (#) Exercisable No. of Securities Underlying Unexercised|No. of Securities Underlying Unexercised Options (#) Unexercisable No. of Securities Underlying Unexercised|Option Exercise Price|Option Expiration Date|
|Garo H. Armen (1)|500,000|-|$1.25|April 16, 2026|
|Garo H. Armen (2)|184,028|65,972|$1.75|October 16, 2027|
|Alexander K. Arrow (3)|100,000|-|$1.25|February 12, 2026|
|Alexander K. Arrow (3)|140,000|-|$1.25|April 15, 2026|
|Alexander K. Arrow (4)|55,208|19,792|$1.75|October 16, 2027|
|Alexander K. Arrow (5)|41,667|-|$1.00|February 1, 2029|
 Outstanding Equity Awards at Fiscal Year End The following table summarizes the equity awards made to our named executive officers that were outstanding at December 31, 2019


Question: How many unexercised options would Garo H. Armen have as at December 31, 2019 after exercising 20% of the options expiring on April 15, 2026?

Python solution:
def solution():
    # Define variables name and value
    initial_options = 500000
    exercise_percentage = 0.2
    remaining_options = 184028
    
    # Do math calculation to get the answer
    answer = initial_options * (1 - exercise_percentage) + remaining_options
    
    return answer

Answer: 584028
|(In millions)|Blue Coat|LifeLock|Total|
|Goodwill|$4,084|$1,397|$5,481|
|Intangible assets|1,608|1,247|2,855|
|Net liabilities assumed|(1,019)|(361)|(1,380)|
|Total purchase price|$4,673|$2,283|$6,956|
 Fiscal 2017 acquisitions On August 1, 2016, we acquired all of the outstanding common stock of Blue Coat, Inc. (Blue Coat), a provider of advanced web security solutions for global enterprises and governments. The addition of Blue Coat’s suite of network and cloud security products to our innovative Enterprise Security product portfolio has enhanced our threat protection and information protection products while providing us with complementary products, such as advanced web and cloud security solutions, that address the network and cloud security needs of enterprises. On February 9, 2017, we completed the acquisition of LifeLock, Inc. (LifeLock) a provider of proactive identity theft protection services for consumers and consumer risk management services for enterprises. LifeLock’s services are provided on a monthly or annual subscription basis and provide identification and notification of identity-related and other events and assist users in remediating their impact. The total consideration for the acquisitions, net of cash acquired, consisted of the following:


Question: If the total purchase price for Blue Coat is $5,000 million, What would be the Goodwill for Blue Coat expressed as a percentage of Total purchase price? (in percent)

Python solution:
def solution():
    # Define variables name and value
    goodwill_blue_coat = 4084
    total_purchase_price_blue_coat = 5000
    
    # Do math calculation to get the answer
    answer = (goodwill_blue_coat / total_purchase_price_blue_coat) * 100
    
    return answer

Answer: 81.68
||2019 Goodwill|2018 Goodwill|
||£m|£m|
|Steam Specialties|113.0|119.3|
|Electric Thermal Solutions|244.7|183.0|
|Watson-Marlow|60.0|65.7|
|Total goodwill|417.7|368.0|
 15 Goodwill and other intangible assets continued Impairment In accordance with the requirements of IAS 36 (Impairment of Assets), goodwill is allocated to the Group’s cash-generating units, or groups of cash-generating units, that are expected to benefit from the synergies of the business combination that gave rise to the goodwill. During 2019, we performed a review on the basis of identification of our individual CGUs. As a result of this review, we have consolidated a number of our current individual CGUs into groups of CGUs that represent the lowest level to which goodwill is monitored for internal management purposes, being each operating segment as disclosed in Note 3. As a result, we performed an impairment review at an operating segment CGU level, the breakdown of the goodwill value at 31st December across these is shown below: In order to complete the transition to performing goodwill impairment reviews at an operating segment level, we also performed a goodwill impairment review as at 31st December 2019 under the historical CGU basis. The result of this impairment review led to an impairment of £4.2m being recognised in respect of Watson-Marlow FlowSmart. No other impairment was recognised. The goodwill balance has been tested for annual impairment on the following basis: • the carrying values of goodwill have been assessed by reference to value in use. These have been estimated using cash flows based on forecast information for the next financial year which have been approved by the Board and then extended up to a further 9 years based on the most recent forecasts prepared by management; • pre-tax discount rates range from 11-12% (2018: 10-15%); • short to medium-term growth rates vary between 3-8% depending on detailed forecasts (2018: 2-8%). The range in rates excludes the annualised impact of owning Thermocoax for a first full year in 2020. The short to medium-term is defined as not more than 10 years; and • long-term growth rates are set using IMF forecasts and vary between 1.8-2.5% (2018: 0.8-3.0%).


Question: What would the percentage change in total goodwill in 2019 from 2018 be if the amount in 2019 was 420.0 million instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    goodwill_2019 = 420.0
    goodwill_2018 = 368.0
    
    # Do math calculation to get the answer
    answer = (goodwill_2019 - goodwill_2018) / goodwill_2018 * 100
    
    return answer

Answer: 14.1304347826
|||Years Ended December 31,||
||2019|2018|2017|
|Average daily utilization|$87,800|$106,189|$268,775|
|Interest expense (1)|$3,465|$3,817|$6,668|
|Weighted average interest rate (1)|3.9%|3.6%|2.5%|
 The following table presents information related to our credit agreements (dollars in thousands): (1) Excludes the amortization of deferred loan fees and includes the commitment fee. In January 2018, the Company repaid $175.0 million of long-term debt outstanding under its 2015 Credit Agreement, primarily using funds repatriated from its foreign subsidiaries.


Question: What would the percentage change in Interest expense in 2019 from 2018 be if the amount in 2019 was $3,417 thousand instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    interest_expense_2019 = 3417
    interest_expense_2018 = 3817
    
    # Do math calculation to get the answer
    answer = (interest_expense_2019 - interest_expense_2018) / interest_expense_2018 * 100
    
    return answer

Answer: -10.4794341106