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:
| december 31 , ( in millions )                                              | december 31 , 2010   | december 31 , 2009   | 2010         | 2009           |
|:---------------------------------------------------------------------------|:---------------------|:---------------------|:-------------|:---------------|
| loans retained                                                             | $ 222510             | $ 200077             | $ 5510       | $ 6559         |
| loans held-for-sale                                                        | 3147                 | 2734                 | 341          | 234            |
| loans at fair value                                                        | 1976                 | 1364                 | 155          | 111            |
| loans 2013 reported                                                        | 227633               | 204175               | 6006         | 6904           |
| derivative receivables                                                     | 80481                | 80210                | 34           | 529            |
| receivables from customers ( a )                                           | 32541                | 15745                | 2014         | 2014           |
| interests in purchased receivables ( b )                                   | 391                  | 2927                 | 2014         | 2014           |
| total wholesale credit-related assets                                      | 341046               | 303057               | 6040         | 7433           |
| lending-related commitments ( c )                                          | 346079               | 347155               | 1005         | 1577           |
| total wholesale credit exposure                                            | $ 687125             | $ 650212             | $ 7045       | $ 9010         |
| net credit derivative hedges notional ( d )                                | $ -23108 ( 23108 )   | $ -48376 ( 48376 )   | $ -55 ( 55 ) | $ -139 ( 139 ) |
| liquid securities and other cash collateral held against derivatives ( e ) | -16486 ( 16486 )     | -15519 ( 15519 )     | na           | na             |

Question:
what was the percentage change in loans retained from 2009 to 2010?


pre_text: management 2019s discussion and analysis 120 jpmorgan chase & co./2010 annual report wholesale credit portfolio as of december 31 , 2010 , wholesale exposure ( ib , cb , tss and am ) increased by $ 36.9 billion from december 31 , 2009 .
the overall increase was primarily driven by increases of $ 23.5 billion in loans and $ 16.8 billion of receivables from customers , partially offset by decreases in interests in purchase receivables and lending-related commitments of $ 2.5 billion and $ 1.1 billion , respectively .
the de- crease in lending-related commitments and the increase in loans were primarily related to the january 1 , 2010 , adoption of the accounting guidance related to vies , which resulted in the elimination of a net $ 17.7 billion of lending-related commitments between the firm and its administrated multi-seller conduits upon consolidation .
assets of the consolidated conduits included $ 15.1 billion of wholesale loans at january 1 , 2010 .
excluding the effect of the accounting guidance , lending-related commitments and loans would have increased by $ 16.6 billion and $ 8.4 billion , respectively , mainly related to in- creased client activity .
the increase in loans also included the pur- chase of a $ 3.5 billion loan portfolio in cb during the third quarter of 2010 .
the increase of $ 16.8 billion in receivables from customers was due to increased client activity , predominantly in prime services .
wholesale .
post_text: net credit derivative hedges notional ( d ) $ ( 23108 ) $ ( 48376 ) $ ( 55 ) $ ( 139 ) liquid securities and other cash collateral held against derivatives ( e ) ( 16486 ) ( 15519 ) na na ( a ) represents primarily margin loans to prime and retail brokerage customers , which are included in accrued interest and accounts receivable on the consolidated balance sheets .
( b ) represents an ownership interest in cash flows of a pool of receivables transferred by a third-party seller into a bankruptcy-remote entity , generally a trust .
( c ) the amounts in nonperforming represent unfunded commitments that are risk rated as nonaccrual .
( d ) represents the net notional amount of protection purchased and sold of single-name and portfolio credit derivatives used to manage both performing and nonperform- ing credit exposures ; these derivatives do not qualify for hedge accounting under u.s .
gaap .
for additional information , see credit derivatives on pages 126 2013128 , and note 6 on pages 191 2013199 of this annual report .
( e ) represents other liquid securities collateral and other cash collateral held by the firm .
( f ) excludes assets acquired in loan satisfactions .
the following table presents summaries of the maturity and ratings profiles of the wholesale portfolio as of december 31 , 2010 and 2009 .
the ratings scale is based on the firm 2019s internal risk ratings , which generally correspond to the ratings as defined by s&p and moody 2019s .
also included in this table is the notional value of net credit derivative hedges ; the counterparties to these hedges are predominantly investment grade banks and finance companies. .
label: 0.11212000000000001
qa: steps: op: minus2-1
arg1: 222510
arg2: 200077
res: 22433
op: divide2-2
arg1: #0
arg2: 200077
res: 11%
program: subtract(222510, 200077), divide(#0, 200077)
gold_inds: table_1: december 31 , ( in millions ) the loans retained of december 31 , 2010 is $ 222510 ; the loans retained of december 31 , 2009 is $ 200077 ; the loans retained of 2010 is $ 5510 ; the loans retained of 2009 is $ 6559 ;
exe_ans: 0.11212000000000001
tfidftopn: table_2: december 31 , ( in millions ) The loans held-for-sale of december 31 , 2010 is 3147 ; The loans held-for-sale of december 31 , 2009 is 2734 ; The loans held-for-sale of 2010 is 341 ; The loans held-for-sale of 2009 is 234 ;
table_3: december 31 , ( in millions ) The loans at fair value of december 31 , 2010 is 1976 ; The loans at fair value of december 31 , 2009 is 1364 ; The loans at fair value of 2010 is 155 ; The loans at fair value of 2009 is 111 ;
program_re: divide(subtract(222510, 200077), 200077)
model_input: table_1
december 31 , ( in millions ) the loans retained of december 31 , 2010 is $ 222510 ; the loans retained of december 31 , 2009 is $ 200077 ; the loans retained of 2010 is $ 5510 ; the loans retained of 2009 is $ 6559 ;
table_2
december 31 , ( in millions ) the loans held-for-sale of december 31 , 2010 is 3147 ; the loans held-for-sale of december 31 , 2009 is 2734 ; the loans held-for-sale of 2010 is 341 ; the loans held-for-sale of 2009 is 234 ;
table_4
december 31 , ( in millions ) the loans 2013 reported of december 31 , 2010 is 227633 ; the loans 2013 reported of december 31 , 2009 is 204175 ; the loans 2013 reported of 2010 is 6006 ; the loans 2013 reported of 2009 is 6904 ;