Task: Table-QA (source dataset: FinQA)

Task: 
You are given a table containing structured data and a natural language question referring to the table. Your goal is to analyze the table and provide an accurate and concise answer based on the given data.

Instructions:
1. Understand the Table: Examine the structure, headers, and data in the table. Identify relevant columns and rows related to the question.
2. Interpret the Question: Determine whether the question requires direct retrieval, aggregation, comparison, sorting, filtering, or inference.
3. Extract the Answer: Use logical reasoning and numerical operations (if necessary) to derive the correct response from the table.
4. Format the Answer: No explanation, return the answer in a structured JSON format: {"answer": <answer>}. If the question cannot be answered due to missing or ambiguous data, return a JSON response with {"answer": null}.

Table:
| Unnamed: 0                                              | 2017             | 2016             |
|:--------------------------------------------------------|:-----------------|:-----------------|
| average borrowings                                      | $ 779            | $ 850            |
| maximum borrowings outstanding                          | 1135             | 1016             |
| weighted average interest rates computed on daily basis | 1.24% ( 1.24 % ) | 0.78% ( 0.78 % ) |
| weighted average interest rates as of december 31       | 1.61% ( 1.61 % ) | 0.98% ( 0.98 % ) |

Question:
by what percentage did maximum borrowings outstanding increase from 2016 to 2017?


pre_text: the following table summarizes the short-term borrowing activity for awcc for the years ended december 31: .
post_text: the credit facility requires the company to maintain a ratio of consolidated debt to consolidated capitalization of not more than 0.70 to 1.00 .
the ratio as of december 31 , 2017 was 0.59 to 1.00 .
none of the company 2019s borrowings are subject to default or prepayment as a result of a downgrading of securities , although such a downgrading could increase fees and interest charges under the company 2019s credit facility .
as part of the normal course of business , the company routinely enters contracts for the purchase and sale of water , energy , fuels and other services .
these contracts either contain express provisions or otherwise permit the company and its counterparties to demand adequate assurance of future performance when there are reasonable grounds for doing so .
in accordance with the contracts and applicable contract law , if the company is downgraded by a credit rating agency , especially if such downgrade is to a level below investment grade , it is possible that a counterparty would attempt to rely on such a downgrade as a basis for making a demand for adequate assurance of future performance .
depending on the company 2019s net position with the counterparty , the demand could be for the posting of collateral .
in the absence of expressly agreed provisions that specify the collateral that must be provided , the obligation to supply the collateral requested will be a function of the facts and circumstances of the company 2019s situation at the time of the demand .
if the company can reasonably claim that it is willing and financially able to perform its obligations , it may be possible that no collateral would need to be posted or that only an amount equal to two or three months of future payments should be sufficient .
the company does not expect to post any collateral which will have a material adverse impact on the company 2019s results of operations , financial position or cash flows .
note 12 : general taxes the following table summarizes the components of general tax expense for the years ended december 31 : 2017 2016 2015 gross receipts and franchise .
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$ 110 $ 106 $ 99 property and capital stock .
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105 106 98 payroll .
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31 32 31 other general .
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13 14 15 total general taxes .
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$ 259 $ 258 $ 243 .
label: 0.11713000000000001
qa: answer: 11.7%
ann_table_rows: 2
steps: op: minus2-1
arg1: 1135
arg2: 1016
res: 119
op: divide2-2
arg1: #0
arg2: 1016
res: 11.7%
program: subtract(1135, 1016), divide(#0, 1016)
gold_inds: table_2: the maximum borrowings outstanding of 2017 is 1135 ; the maximum borrowings outstanding of 2016 is 1016 ;
exe_ans: 0.11713000000000001
tfidftopn: table_1: The average borrowings of 2017 is $ 779 ; The average borrowings of 2016 is $ 850 ;
text_3: none of the company 2019s borrowings are subject to default or prepayment as a result of a downgrading of securities , although such a downgrading could increase fees and interest charges under the company 2019s credit facility .
program_re: divide(subtract(1135, 1016), 1016)
model_input: text_0
the following table summarizes the short-term borrowing activity for awcc for the years ended december 31: .
table_1
the average borrowings of 2017 is $ 779 ; the average borrowings of 2016 is $ 850 ;
table_2
the maximum borrowings outstanding of 2017 is 1135 ; the maximum borrowings outstanding of 2016 is 1016 ;