Ayushnangia/finbench-data huggingface dataset:
||Fair Value|Useful Life|
||(U.S. $ in thousands)|(years)|
|Developed technology|$34,600|5|
|Customer relationships|16,900|7|
|Backlog|1,400|3|
|Total intangible assets subject to amortization|$52,900||
 The following table sets forth the components of identifiable intangible assets acquired and their estimated useful lives as of the date of acquisition. The amount recorded for developed technology represents the estimated fair value of AgileCraft’s enterprise agile planning technology. The amount recorded for customer relationships represents the fair value of the underlying relationships with AgileCraft’s customers. The amount recorded for backlog represents the fair value of AgileCraft’s backlog as of acquisition date.


Question: For fair value, what would be the percentage constitution of customer relationships among the total intangible assets subject to amortization if the fair value of customer relationships was $30,000 thousand instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    customer_relationships = 30000
    total_intangible_assets = 52900
    original_customer_relationships = 16900
    
    # Do math calculation to get the answer
    answer = (customer_relationships / (total_intangible_assets + (customer_relationships - original_customer_relationships))) * 100
    
    return answer

Answer: 45.4545454545
||March 31,||
|(amounts in thousands)|2019|2018|
|Accounts receivable:|||
|Trade|$176,715|$166,459|
|Allowance for doubtful accounts reserve|(1,206)|(1,210)|
|Ship-from-stock and debit (“SFSD”) reserve|(18,862)|(17,362)|
|Returns reserves (1)|(964)|(131)|
|Rebates reserves|(967)|(446)|
|Price protection reserves|(657)|(420)|
|Other|—|(329)|
|Accounts receivable, net (1)|$154,059|$146,561|
 Note 13: Supplemental Balance Sheets and Statements of Operations Detail (1) Fiscal year ended March 31, 2018 adjusted due to the adoption of ASC 606.


Question: What would be the change in the Returns reserves between 2018 and 2019 if the returns reserves in 2019 was -$500 thousand instead? (in thousand)

Python solution:
def solution():
    # Define variables name and value
    returns_reserves_2019 = -500
    returns_reserves_2018 = -131
    
    # Do math calculation to get the answer
    answer = returns_reserves_2019 - returns_reserves_2018
    
    return answer

Answer: -369
|Year Ended December 31,|||
||2019|2018|
|(In thousands)|||
|Revenues|$6,490|$7,859|
|(Loss) from operations|$(7,488)|$(6,322)|
|(Loss) from operations as a % of revenues|(115)%|(80)%|
 Asia Pacific Asia Pacific net revenues decreased $1.4 million in 2019 compared to 2018 (see “Revenues” above). Asia Pacific expenses decreased $203,000 from 2018 to 2019. This decrease was primarily due to a $503,000 decrease of salary expense, offset partially by a $303,000 increase in member acquisition costs. Foreign currency movements relative to the U.S. dollar negatively impacted our local currency loss from our operations in Asia Pacific by approximately $136,000 for 2019. Foreign currency movements relative to the U.S. dollar positively impacted our local currency loss from our operations in Asia Pacific by approximately $127,000 for 2018.


Question: What would be the percentage change in revenue from 2018 to 2019 if the value in 2019 was $8,000 thousand instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    revenue_2018 = 7859
    revenue_2019_modified = 8000
    
    # Do math calculation to get the answer
    answer = (revenue_2019_modified - revenue_2018) / revenue_2018 * 100
    
    return answer

Answer: 1.7941213895
||2019|2018|
|Computer equipment|$137,763|$94,384|
|Furniture and fixtures|187,167|159,648|
|Subtotal|324,930|254,032|
|Less accumulated depreciation|148,916|104,702|
|Property and equipment, net|$176,014|$149,330|
 NOTE 5 – PROPERTY AND EQUIPMENT The Company owned equipment recorded at cost, which consisted of the following as of December 31, 2019 and 2018: Depreciation expense was $80,206 and $58,423 for the years ended December 31, 2019 and 2018, respectively


Question: What would be the average subtotal cost of property and equipment that the Company owned from 2018 to 2019 if the subtotal cost of property and equipment in 2018 was $300,000?

Python solution:
def solution():
    # Define variables name and value
    subtotal_cost_2019 = 324930
    subtotal_cost_2018 = 300000
    
    # Do math calculation to get the answer
    answer = (subtotal_cost_2019 + subtotal_cost_2018) / 2
    
    return answer

Answer: 312465
||Automotive and Discrete Group (ADG)|Microcontrollers and Digital ICs Group (MDG)|Analog, MEMS & Sensors Group AMS)|Total|
|December 31, 2017|—|121|2|123|
|Foreign currency translation|—|(2)|—|(2)|
|December 31, 2018|—|119|2|121|
|Business combination|43|—|—|43|
|Foreign currency translation|—|(2)|—|(2)|
|December 31, 2019|43|117|2|162|
 As described in Note 7, the acquisition of Norstel resulted in the recognition of $43 million in goodwill which has been included in the ADG segment to align the goodwill of the acquired Company with the segment under which the related activities will be reported. As of the end of the third quarters of 2019 and 2018, the Company performed its annual impairment test. The Company did not elect to perform a qualitative assessment. The impairment test was conducted following a two-step process. In the first step, the Company compared the fair value of the reporting units tested to their carrying value. Based upon the first step of the goodwill impairment test, no impairment was recorded since the fair value of the reporting units exceeded their carrying value. Goodwill as at December 31, 2019 and 2018 is net of accumulated impairment losses of $102 million, of which $96 million relates to the MDG segment and $6 million to Others. In 2019, 2018 and 2017, no impairment loss was recorded by the Company.


Question: If the goodwill of Analog, MEMS & Sensors Group (AMS) is increased to 9 million, what is the revised average? (in million)

Python solution:
def solution():
    # Define variables name and value
    new_goodwill = 9
    initial_total_goodwill = 121

    # Do math calculation to get the answer
    answer = (initial_total_goodwill + new_goodwill) / 2

    return answer

Answer: 65
|||Three Months Ended||||
||March 31,|June 30,|September 30,|December 31,|Year Ended December 31,|
|2018:||||||
|Operating revenues|$1,741.8|$1,780.9|$1,785.5|$2,131.9|$7,440.1|
|Costs of operations (1)|519.9|560.3|556.7|540.9|2,177.8|
|Operating income|402.9|546.0|567.2|388.9|1,905.0|
|Net income|280.3|314.4|377.3|292.7|1,264.7|
|Net income attributable to American Tower Corporation stockholders|285.2|306.7|366.9|277.6|1,236.4|
|Dividends on preferred stock|(9.4)|—|—|—|(9.4)|
|Net income attributable to American Tower Corporation common stockholders|275.8|306.7|366.9|277.6|1,227.0|
|Basic net income per share attributable to American Tower Corporation common stockholders|0.63|0.69|0.83|0.63|2.79|
|Diluted net income per share attributable to American Tower Corporation common stockholders|0.63|0.69|0.83|0.62|2.77|
 AMERICAN TOWER CORPORATION AND SUBSIDIARIES NOTES TO CONSOLIDATED FINANCIAL STATEMENTS (Tabular amounts in millions, unless otherwise disclosed) 23. SELECTED QUARTERLY FINANCIAL DATA (UNAUDITED) Selected quarterly financial data for the years ended December 31, 2019 and 2018 is as follows (in millions, except per share data): (1) Represents Operating expenses, exclusive of Depreciation, amortization and accretion, Selling, general, administrative and development expense, and Other operating expenses.


Question: What was the percentage change in operating revenues between Three Months Ended  September and December if the operating revenue in Three Months Ended  December was $2,000 million instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    operating_revenues_september = 1785.5
    operating_revenues_december = 2000

    # Do math calculation to get the answer
    answer = ((operating_revenues_december - operating_revenues_september) / operating_revenues_september) * 100

    return answer

Answer: 12.013441613
||2019|2018|
|Weighted-average fair value of options granted per share|$8.78|$6.63|
|Historical volatility|60%|46%|
|Risk-free interest rate|2.10%|2.84%|
|Dividend yield|—|—|
|Expected life in years|3.6|5.7|
 The Company utilized the Black-Scholes option pricing model to value the stock options. The Company used an expected life as defined under the simplified method, which is using an average of the contractual term and vesting period of the stock options. The risk-free interest rate used for the award is based on the U.S. Treasury yield curve in effect at the time of grant. The Company accounted for forfeitures as they occur. The historical volatility was calculated based upon implied volatility of the Company's historical stock prices. The fair value of 2019 and 2018 stock options was estimated using the Black-Scholes option pricing model with the following weighted-average assumptions: As of December 31, 2019, there was approximately $419,000 of unrecognized stock-based compensation expense related to outstanding 2019 stock options, expected to be recognized over 3.4 and approximately $418,000 of unrecognized stock-based compensation expense related to outstanding 2018 stock options, expected to be recognized over 2.4 years. There was no unrecognized stock-based compensation expense relating stock options granted prior to 2018.


Question: What would be the average risk-free interest rate used in 2018 and 2019 if the value in 2019 decreased by 0.50%? (in percent)

Python solution:
def solution():
    # Define variables name and value
    risk_free_interest_rate_2019 = 2.1
    risk_free_interest_rate_2018 = 2.84
    decrease_percent = 0.5
    
    # Do math calculation to get the answer
    answer = (risk_free_interest_rate_2019 - decrease_percent + risk_free_interest_rate_2018) / 2
    
    return answer

Answer: 2.22
||December 31, 2019|December 31, 2018|
||(in thousands)||
|Cash, cash equivalents and marketable securities|$2,455,194|$1,969,670|
|Total assets|3,489,479|2,254,785|
|Total liabilities|473,745|164,017|
|Total non-current liabilities|157,363|25,329|
 Key Balance Sheet Information Total assets increased $1,234.7 million as at December 31, 2019 compared to December 31, 2018, principally due to a $485.5 million increase in cash, cash equivalents and marketable securities mainly as a result of the public offering in September 2019, which resulted in net proceeds of $688.0 million. Business acquisitions during the year, largely due to the acquisition of 6RS, further impacted total assets through an increase in goodwill of $273.8 million, a $141.2 million increase in intangible assets and a resulting decrease in cash due to the consideration paid. The remainder of the increase is due to: the adoption of the new lease accounting standard, further discussed in the "Critical Accounting Policies and Estimates" section below, which resulted in the addition of right-of-use assets totaling $134.8 million as at December 31, 2019; a $58.3 million increase in merchant cash advances and loans receivable; a $49.8 million increase in property and equipment, largely related to leaseholds for our offices; a $49.2 million increase in trade and other receivables largely due to an increase in indirect taxes receivable, unbilled revenue related to subscription fees for Plus merchants, transaction fees and shipping charges; and a $19.4 million increase in deferred tax assets. Total liabilities increased by $309.7 million, principally as a result of the adoption of the new leasing standard, which resulted in $126.8 million of additional lease liabilities related to obtaining right-of-use assets. Accounts payable and accrued liabilities increased by $84.2 million, which was due to an increase in indirect taxes payable, payroll liabilities, and payment processing and interchange fees, partly offset by a decrease in foreign exchange forward contract liabilities. The increase was also due to income taxes payable of $69.4 million driven largely by the one-time capital gain recognized in the period. Deferred tax liabilities increased by $7.6 million, due to the acquisition of 6RS. The growth in sales of our subscription solutions offering, along with the acquisition of 6RS, resulted in an increase of deferred revenue of $21.6 million.


Question: What would be the average cash, cash equivalents and marketable securities for 2018 and 2019 if cash, cash equivalents and marketable securities as at 2018 year end was $2,100,000 thousands)? (in thousand)

Python solution:
def solution():
    # Define variables name and value
    cash_equivalents_2019 = 2455194
    cash_equivalents_2018 = 2100000
    
    # Do math calculation to get the answer
    answer = (cash_equivalents_2019 + cash_equivalents_2018) / 2
    
    return answer

Answer: 2277597
||Balance at Beginning of Year|Additions Charged to Costs and Expenses|Additions Charged to Other Accounts|Deductions|Balance at End of Year|
|Valuation allowance for deferred tax assets:||||||
|Fiscal 2019|$204.5|$16.2|$175.8|$(64.4)|$332.1|
|Fiscal 2018|$210.1|$36.2|$—|$(41.8)|$204.5|
|Fiscal 2017|$161.8|$15.2|$37.6|$(4.5)|$210.1|
 Note 22. Supplemental Financial Information Cash paid for income taxes amounted to $77.6 million, $25.9 million and $48.4 million during fiscal 2019, 2018 and 2017, respectively. Cash paid for interest on borrowings amounted to $347.9 million, $85.3 million and $82.5 million during fiscal 2019, 2018 and 2017, respectively. A summary of additions and deductions related to the valuation allowance for deferred tax asset accounts for the years ended March 31, 2019, 2018 and 2017 follows (amounts in millions):


Question: What would be the percentage change in the Balance at End of Year between 2018 and 2019 if the Balance at End of Year in 2019 was $500 million instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    balance_2018 = 204.5
    balance_2019_modified = 500

    # Do math calculation to get the answer
    answer = (balance_2019_modified - balance_2018) / balance_2018 * 100

    return answer

Answer: 144.4987775061
|Year Ended May 31,|||||
||||Percent Change||
|(Dollars in millions)|2019|Actual|Constant|2018|
|Research and development (1)|$5,063|-2%|0%|$5,163|
|Stock-based compensation|963|5%|5%|921|
|Total expenses|$6,026|-1%|0%|$6,084|
|% of Total Revenues|15%|||15%|
 Research and Development Expenses: research and development expenses consist primarily of personnel related expenditures. We intend to continue to invest significantly in our research and development efforts because, in our judgment, they are essential to maintaining our competitive position. (1) Excluding stock-based compensation On a constant currency basis, total research and development expenses were flat in fiscal 2019, as lower employee related expenses including lower variable compensation were offset by an increase in stock-based compensation expenses .


Question: Given that the amount of stock-based compensation in 2019 was 810 million instead, what was the percentage of expenses that went towards it in 2019? (in percent)

Python solution:
def solution():
    # Define variables name and value
    stock_based_compensation = 810
    research_and_development = 5063
    
    # Do math calculation to get the answer
    answer = (stock_based_compensation / (stock_based_compensation + research_and_development)) * 100
    
    return answer

Answer: 13.7919291674
|2019|Americas|Europe|Asia|Total|% of total|
|||(Amounts in thousands)||||
|TS|$67,728|$3,285|$646|$71,159|90%|
|HPP|5,294|771|1,837|7,902|10%|
|Total|$72,522|$4,056|$2,483|$79,061|100%|
|% of total|92%|5%|3%|100%||
|2018||||||
|TS|$52,034|$9,059|$1,344|$62,437|86%|
|HPP|8,424|1,266|789|10,479|14%|
|Total|$60,458|$10,325|$2,133|$72,916|100%|
|% of total|83%|14%|3%|100%||
 The following table details the Company’s sales by operating segment for fiscal years ended September 30, 2019 and 2018. The Company’s sales by geographic area based on the location of where the products were shipped or services rendered are as follows: Substantially all Americas amounts are United States.


Question: What is the percentage change in Asia sales between 2018 and 2019 if the 2019 sales is doubled and increased by another 400 thousand? (in percent)

Python solution:
def solution():
    # Define variables name and value
    asia_sales_2019 = 2483
    asia_sales_2018 = 2133
    doubling_sales = 2
    additional_amount = 400

    # Do math calculation to get the answer
    answer = ((asia_sales_2019 * doubling_sales + additional_amount) - asia_sales_2018) / asia_sales_2018 * 100
    
    return answer

Answer: 151.5705578997
||2019|2018|
|Cash flows provided by operating activities|$115.3|$66.8|
|Payments for property, plant and equipment|(90.6)|(62.8)|
|Free cash flow|24.7|4.0|
 Free Cash Flow. We define free cash flow ("FCF"), a non-GAAP financial measure, as cash flow provided by operations less capital expenditures. FCF was$ 24.7 million for fiscal 2019 compared to $4.0 million for fiscal 2018, an increase of $20.7 million. Non-GAAP financial measures, including FCF, are used for internal management assessments because such measures provide additional insight to investors into ongoing financial performance. In particular, we provide FCF because we believe it offers insight into the metrics that are driving management decisions. We view FCF as an important financial metric as it demonstrates our ability to generate cash and can allow us to pursue opportunities that enhance shareholder value. FCF is a non-GAAP financial measure that should be considered in addition to, not as a substitute for, measures of our financial performance prepared in accordance with GAAP. A reconciliation of FCF to our financial statements that were prepared using GAAP follows (in millions):


Question: What would be the percentage change in the free cash flow between 2018 and 2019 if the free cash flow in 2019 was $10 million instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    fcf_2018 = 4.0
    fcf_2019_new = 10

    # Do math calculation to get the answer
    answer = (fcf_2019_new - fcf_2018) / fcf_2018 * 100
    
    return answer

Answer: 150
||2019|2018|
||£m|£m|
|Total equity|826.3|766.9|
|Net debt|334.1|235.8|
|Total invested capital|1,160.4|1,002.7|
|Average invested capital|1,081.6|992.9|
|Average invested capital (excluding IFRS 16)|1,061.2|992.9|
|Operating profit as reported under IFRS|245.0|299.1|
|Adjustments (see adjusted operating profit)|37.7|(34.2)|
|Adjusted operating profit|282.7|264.9|
|Taxation|(80.6)|(73.1)|
|Adjusted operating profit after tax|202.1|191.8|
|Adjusted operating profit after tax (excluding IFRS 16)|201.2|191.8|
|Return in invested capital|18.7%|19.3%|
|Return in invested capital (excluding IFRS 16)|19.0%|19.3%|
 Return on invested capital (ROIC) ROIC measures the after tax return on the total capital invested in the business. It is calculated as adjusted operating profit after tax divided by average invested capital. An analysis of the components is as follows:


Question: What would the change in net debt in 2019 from 2018 be if the amount in 2019 was 330.0 million instead? (in million)

Python solution:
def solution():
    # Define variables name and value
    net_debt_2019 = 330.0
    net_debt_2018 = 235.8

    # Do math calculation to get the answer
    answer = net_debt_2019 - net_debt_2018

    return answer

Answer: 94.2
|||Years Ended||2019 vs. 2018||
||July 27, 2019|July 28, 2018|July 29, 2017|Variance in Dollars|Variance in Percent|
|Product revenue:||||||
|Americas|$22,754|$21,088|$20,487|$1,666|8%|
|Percentage of product revenue|58.3%|57.5%|57.4%|||
|EMEA|10,246|9,671|9,369|575|6%|
|Percentage of product revenue|26.3%|26.3%|26.2%|||
|APJC|6,005|5,950|5,849|55|1%|
|Percentage of product revenue|15.4%|16.2%|16.4%|||
|Total|$39,005|$36,709|$35,705|$2,296|6%|
 Product Revenue by Segment The following table presents the breakdown of product revenue by segment (in millions, except percentages): Amounts may not sum and percentages may not recalculate due to rounding. Americas Product revenue in the Americas segment increased by 8%, driven by growth in the enterprise, public sector and commercial markets. These increases were partially offset by a product revenue decline in the service provider market. From a country perspective, product revenue increased by 9% in the United States, 26% in Mexico and 6% in Canada, partially offset by a product revenue decrease of 1% in Brazil. EMEA The increase in product revenue in the EMEA segment of 6% was driven by growth in the public sector and enterprise markets, partially offset by a decline in the service provider market. Product revenue in the commercial market was flat. Product revenue from emerging countries within EMEA increased by 9%, and product revenue for the remainder of the EMEA segment increased by 5%. APJC Product revenue in the APJC segment increased by 1%, driven by growth in the public sector and enterprise markets, partially offset by declines in the service provider and commercial markets. From a country perspective, product revenue increased by 9% in Japan and 5% in India, partially offset by a product revenue decrease of 16% in China.


Question: What would be the percentage change in the total revenue from all segments between 2017 and 2018 if total revenue in 2018 was $50,000 million instead? (in percent)

Python solution:
def solution():
    # Define variables name and value
    total_revenue_2018 = 50000
    total_revenue_2017 = 35705
    
    # Do math calculation to get the answer
    answer = (total_revenue_2018 - total_revenue_2017) / total_revenue_2017 * 100
    
    return answer

Answer: 40.0364094665
|||Year ended December 31,||
||2019|2018|2017|
|Revenues|$1,177.2|$1,114.0|$1,051.6|
|Expenses:||||
|Operating expenses|646.0|625.4|569.5|
|Depreciation and amortization|236.2|217.0|206.5|
|Transition and integration costs|5.4|6.6|13.1|
|Total expenses|887.6|849.0|789.1|
|Operating income|289.6|265.0|262.5|
|Operating margin|24.6%|23.8%|25.0%|
|Interest expense, net|(63.5)|(51.7)|(57.5)|
|Other expense, net|(1.4)|(7.1)|(12.6)|
|Earnings before income taxes and equity in losses of unconsolidated affiliates|224.7|206.2|192.4|
|Income tax expense (benefit)|41.9|37.7|(61.8)|
|Earnings before equity in losses of unconsolidated affiliates|182.8|168.5|254.2|
|Equity in losses of unconsolidated affiliates, net of tax|(74.0)|—|—|
|Net earnings|$108.8|$168.5|$254.2|
|Earnings per share:||||
|Net earnings per share attributable to Black Knight common shareholders:||||
|Diluted|$0.73|$1.14|$1.47|
|Weighted average shares of common stock outstanding:||||
|Diluted|148.6|148.2|152.4|
 Results of Operations Consolidated Results of Operations The following tables present certain financial data for the periods indicated (dollars in millions):


Question: What would be the change in operating income between 2017 and 2018 if the operating income in 2017 was $200 million instead? (in million)

Python solution:
def solution():
    # Define variables name and value
    operating_income_2018 = 265.0
    operating_income_2017 = 200.0
    
    # Do calculation to get the change in operating income
    change_in_operating_income = operating_income_2018 - operating_income_2017
    
    return change_in_operating_income

Answer: 65