Task: Table-QA (source dataset: TableBench)

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:
|   rank |   rank fortune 500 | name                                    | headquarters         |   revenue (millions) |   profit (millions) |   employees | industry           |
|-------:|-------------------:|:----------------------------------------|:---------------------|---------------------:|--------------------:|------------:|:-------------------|
|      1 |                 17 | sinopec                                 | beijing              |             131636   |              3703.1 |      681900 | oil                |
|      2 |                 24 | china national petroleum                | beijing              |             110520   |             13265.3 |     1086966 | oil                |
|      3 |                 29 | state grid corporation                  | beijing              |             107186   |              2237.7 |     1504000 | utilities          |
|      4 |                170 | industrial and commercial bank of china | beijing              |              36832.9 |              6179.2 |      351448 | banking            |
|      5 |                180 | china mobile limited                    | beijing              |              35913.7 |              6259.7 |      130637 | telecommunications |
|      6 |                192 | china life insurance                    | beijing              |              33711.5 |               173.9 |       77660 | insurance          |
|      7 |                215 | bank of china                           | beijing              |              30750.8 |              5372.3 |      232632 | banking            |
|      8 |                230 | china construction bank                 | beijing              |              28532.3 |              5810.3 |      297506 | banking            |
|      9 |                237 | china southern power grid               | guangzhou            |              27966.1 |              1074.1 |      178053 | utilities          |
|     10 |                275 | china telecom                           | beijing              |              24791.3 |              2279.7 |      400299 | telecommunications |
|     11 |                277 | agricultural bank of china              | beijing              |              24475.5 |               728.4 |      452464 | banking            |
|     12 |                290 | hutchison whampoa                       | hong kong            |              23661   |              2578.3 |      220000 | various sectors    |
|     13 |                299 | sinochem corporation                    | beijing              |              23109.2 |               344.7 |       20343 | various sectors    |
|     14 |                307 | baosteel                                | shanghai             |              22663.4 |              1622.2 |       91308 | steel              |
|     15 |                342 | china railway engineering               | beijing              |              20520.4 |               142.6 |      275866 | railway            |
|     16 |                384 | china railway construction              | beijing              |              18735.7 |                70.2 |      245540 | railway            |
|     17 |                385 | first automotive works                  | changchun            |              18710.7 |                70   |      136010 | automobile         |
|     18 |                396 | china state construction                | beijing              |              18163.2 |               281.3 |      294309 | construction       |
|     19 |                402 | saic motor                              | shanghai             |              18010.1 |                89.7 |       72416 | automobile         |
|     20 |                405 | cofco limited                           | beijing              |              17953.2 |               281   |       82481 | various sectors    |
|     21 |                435 | china minmetals                         | beijing              |              16902.2 |               154.4 |       32594 | metal trading      |
|     22 |                457 | jardine matheson                        | hong kong / hamilton |              16281   |              1348   |      240000 | various sectors    |
|     23 |                469 | china national offshore oil             | beijing              |              16038.9 |              3007.1 |       44000 | oil                |
|     24 |                488 | china ocean shipping                    | beijing              |              15413.5 |              1092.9 |       79616 | shipping           |

Question:
How many companies in the banking industry are listed in the table?


id: 63359e8db2964276d15c92a05ec20ffb
qtype: NumericalReasoning
label: 4