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:
| millions except percentages                      | 2011             | 2010             | 2009             |
|:-------------------------------------------------|:-----------------|:-----------------|:-----------------|
| net income                                       | $ 3292           | $ 2780           | $ 1890           |
| average equity                                   | $ 18171          | $ 17282          | $ 16058          |
| return on average commonshareholders 2019 equity | 18.1% ( 18.1 % ) | 16.1% ( 16.1 % ) | 11.8% ( 11.8 % ) |

Question:
what was the change in millions of average equity from 2009 to 2010?


pre_text: 2011 , effectively handling the 3% ( 3 % ) increase in carloads .
maintenance activities and weather disruptions , combined with higher volume levels , led to a 4% ( 4 % ) decrease in average train speed in 2010 compared to a record set in 2009 .
average terminal dwell time 2013 average terminal dwell time is the average time that a rail car spends at our terminals .
lower average terminal dwell time improves asset utilization and service .
average terminal dwell time increased 3% ( 3 % ) in 2011 compared to 2010 .
additional volume , weather challenges , track replacement programs , and a shift of traffic mix to more manifest shipments , which require additional terminal processing , all contributed to the increase .
average terminal dwell time increased 2% ( 2 % ) in 2010 compared to 2009 , driven in part by our network plan to increase the length of numerous trains to improve overall efficiency , which resulted in higher terminal dwell time for some cars .
average rail car inventory 2013 average rail car inventory is the daily average number of rail cars on our lines , including rail cars in storage .
lower average rail car inventory reduces congestion in our yards and sidings , which increases train speed , reduces average terminal dwell time , and improves rail car utilization .
average rail car inventory decreased slightly in 2011 compared to 2010 , as we continued to adjust the size of our freight car fleet .
average rail car inventory decreased 3% ( 3 % ) in 2010 compared to 2009 , while we handled a 13% ( 13 % ) increase in carloads during the period compared to 2009 .
we maintained more freight cars off-line and retired a number of old freight cars , which drove the decrease .
gross and revenue ton-miles 2013 gross ton-miles are calculated by multiplying the weight of loaded and empty freight cars by the number of miles hauled .
revenue ton-miles are calculated by multiplying the weight of freight by the number of tariff miles .
gross and revenue-ton-miles increased 5% ( 5 % ) in 2011 compared to 2010 , driven by a 3% ( 3 % ) increase in carloads and mix changes to heavier commodity groups , notably a 5% ( 5 % ) increase in energy shipments .
gross and revenue-ton-miles increased 10% ( 10 % ) and 9% ( 9 % ) , respectively , in 2010 compared to 2009 due to a 13% ( 13 % ) increase in carloads .
commodity mix changes ( notably automotive shipments ) drove the variance in year-over-year growth between gross ton-miles , revenue ton-miles and carloads .
operating ratio 2013 operating ratio is our operating expenses reflected as a percentage of operating revenue .
our operating ratio increased 0.1 points to 70.7% ( 70.7 % ) in 2011 versus 2010 .
higher fuel prices , inflation and weather related costs , partially offset by core pricing gains and productivity initiatives , drove the increase .
our operating ratio improved 5.5 points to 70.6% ( 70.6 % ) in 2010 and 1.3 points to 76.1% ( 76.1 % ) in 2009 .
efficiently leveraging volume increases , core pricing gains , and productivity initiatives drove the improvement in 2010 and more than offset the impact of higher fuel prices during the year .
employees 2013 employee levels were up 5% ( 5 % ) in 2011 versus 2010 , driven by a 3% ( 3 % ) increase in volume levels , a higher number of trainmen , engineers , and yard employees receiving training during the year , and increased work on capital projects .
employee levels were down 1% ( 1 % ) in 2010 compared to 2009 despite a 13% ( 13 % ) increase in volume levels .
we leveraged the additional volumes through network efficiencies and other productivity initiatives .
in addition , we successfully managed the growth of our full- time-equivalent train and engine force levels at a rate less than half of our carload growth in 2010 .
all other operating functions and support organizations reduced their full-time-equivalent force levels , benefiting from continued productivity initiatives .
customer satisfaction index 2013 our customer satisfaction survey asks customers to rate how satisfied they are with our performance over the last 12 months on a variety of attributes .
a higher score indicates higher customer satisfaction .
we believe that improvement in survey results in 2011 generally reflects customer recognition of our service quality supported by our capital investment program .
return on average common shareholders 2019 equity millions , except percentages 2011 2010 2009 .
post_text: .
label: 1224
qa: answer: 1224
ann_table_rows: 2
steps: op: minus1-1
arg1: 17282
arg2: 16058
res: 1224
program: subtract(17282, 16058)
gold_inds: table_2: millions except percentages the average equity of 2011 is $ 18171 ; the average equity of 2010 is $ 17282 ; the average equity of 2009 is $ 16058 ;
exe_ans: 1224
tfidftopn: text_30: return on average common shareholders 2019 equity millions , except percentages 2011 2010 2009 .
table_3: millions except percentages The return on average commonshareholders 2019 equity of 2011 is 18.1% ( 18.1 % ) ; The return on average commonshareholders 2019 equity of 2010 is 16.1% ( 16.1 % ) ; The return on average commonshareholders 2019 equity of 2009 is 11.8% ( 11.8 % ) ;
program_re: subtract(17282, 16058)
model_input: text_30
return on average common shareholders 2019 equity millions , except percentages 2011 2010 2009 .
table_2
millions except percentages the average equity of 2011 is $ 18171 ; the average equity of 2010 is $ 17282 ; the average equity of 2009 is $ 16058 ;
table_3
millions except percentages the return on average commonshareholders 2019 equity of 2011 is 18.1% ( 18.1 % ) ; the return on average commonshareholders 2019 equity of 2010 is 16.1% ( 16.1 % ) ; the return on average commonshareholders 2019 equity of 2009 is 11.8% ( 11.8 % ) ;