Task: NL2SQL (source dataset: Spider)

Natural language to SQL, also known as NL2SQL, is the problem of generating a SQL query that can be executed on a input table, for a given natural language question.

You will be given an input table called "table" in the markdown format, as well as a question. Your task is to generate an SQL query that can be executed on the input table to answer the question.

Please ensure that the generated SQL only return relevant columns being specifically asked in the question (e.g., in SQL please don't return more than one columns in SELECT if only one column is needed to answer the given question, and similarly please refrain from using SELECT * unless the entire row is needed to answer the question).
 
When generating SQL code, please use the SQLite syntax to ensure that your SQL is executable on SQLite3. Use only columns that are present in the table, always use quotes around your column and table names (some column names have punctuation or special characters), and refer to the columns using the column-names exactly as they appear in the table, do not add or remove punctuation (underscore, slash, etc.)

No explanation, return the code only with the following markdown codeblock format : ```sql<SQL CODE>```. For example, ```sql
SELECT * FROM "table"
``` is a valid format.

Database:
customers_and_orders

Tables:

Table: Products
|   product_id | product_type_code   | product_name   |   product_price |
|-------------:|:--------------------|:---------------|----------------:|
|            1 | Hardware            | Monitor        |  2084.94        |
|            2 | Clothes             | Topping        |     2.60457e+07 |
|            3 | Clothes             | Black Jeans    |     7.31201e+06 |
|            4 | Clothes             | Blue Jeans     |   473.923       |
|            5 | Clothes             | Yellow Jeans   |     3.45295e+07 |
|            6 | Clothes             | Gray Jeans     |     6.89749e+06 |
|            7 | Hardware            | Mouse          |     1.96067e+08 |
|            8 | Clothes             | White Topping  |   705.913       |
|            9 | Hardware            | Keyboard       |   495.993       |
|           10 | Hardware            | Drive          |     3.7993e+07  |


Table: Addresses
|   address_id | address_details                    |
|-------------:|:-----------------------------------|
|            1 | 2632 Ofelia Stream Apt. 537        |
|              | Rueckerborough, NV 78430-4096      |
|            2 | 481 Tyrique Junction               |
|              | West Kali, UT 16070-1379           |
|            3 | 4363 Otilia Hill                   |
|              | Landenshire, ND 45637              |
|            4 | 1734 Klocko Views Suite 840        |
|              | Schusterfort, WY 34067-3366        |
|            5 | 001 Eliza Ferry Suite 929          |
|              | Schillerfurt, WI 60335-2125        |
|            6 | 8013 O'Keefe Harbors               |
|              | New Baronview, AR 57984            |
|            7 | 50445 Gerhold Springs              |
|              | Jaleelstad, IL 16333-3222          |
|            8 | 13460 Rylee Green                  |
|              | South Domenicamouth, NM 36408-2902 |
|            9 | 59479 Eladio Cliff                 |
|              | Wymanside, PA 69696-5826           |
|           10 | 4959 Dixie Oval                    |
|              | North Timothyberg, OK 88659        |


Table: Customers
|   customer_id |   address_id | payment_method_code   |   customer_number | customer_name   | customer_address                | customer_phone      | customer_email              |
|--------------:|-------------:|:----------------------|------------------:|:----------------|:--------------------------------|:--------------------|:----------------------------|
|             1 |            9 | Credit Card           |               601 | Jeromy          | 422 Bode Mount Apt. 688         | 1-968-453-3485      | everett.kautzer@example.com |
|             2 |            8 | Credit Card           |               920 | Edmond          | 0965 Dickens Springs            | +92(8)6677749570    | maegan54@example.net        |
|             3 |            3 | Credit Card           |               990 | Twila           | 878 Joy Fields Apt. 366         | (291)441-3432       | dedric.bailey@example.org   |
|             4 |           11 | Credit Card           |                37 | Madelynn        | 9128 Berry Mountains Suite 608  | 1-909-419-5704x7658 | white.barney@example.net    |
|             5 |            7 | Credit Card           |               949 | Nya             | 689 Wilkinson Coves Apt. 107    | 739-333-7916        | eldred44@example.net        |
|             6 |            1 | Credit Card           |               892 | Kenna           | 5425 Vern Rue Suite 490         | 804-701-9307        | thomas67@example.org        |
|             7 |           10 | Credit Card           |               707 | Katrina         | 73546 Gaylord Harbors Suite 881 | 239.351.4998x35742  | hoyt80@example.org          |
|             8 |            9 | Credit Card           |               979 | Jaylan          | 76957 Kohler Via Suite 315      | +10(8)9243074470    | penelope.koepp@example.com  |
|             9 |            7 | Credit Card           |                25 | Jeremie         | 97464 Greenholt Tunnel          | 1-766-484-5984x4558 | kuhn.mable@example.org      |
|            10 |            9 | Direct Debit          |               319 | Lenny           | 869 Anastasia Knoll Apt. 100    | 457.149.5849        | brooks08@example.org        |


Table: Customer_Orders
|   order_id |   customer_id | order_date          | order_status_code   |
|-----------:|--------------:|:--------------------|:--------------------|
|          1 |            12 | 2016-05-14 22:08:41 | Part                |
|          2 |             3 | 1991-02-26 11:32:39 | Part                |
|          3 |             3 | 2000-06-26 05:17:11 | Part                |
|          4 |             1 | 1987-06-28 09:12:32 | Completed           |
|          5 |            15 | 1994-12-17 22:49:09 | Completed           |
|          6 |            13 | 1978-09-08 23:31:23 | Part                |
|          7 |            15 | 2009-11-20 18:18:29 | Completed           |
|          8 |             9 | 1994-02-07 07:27:57 | Part                |
|          9 |             5 | 2007-11-23 04:32:19 | Completed           |
|         10 |            14 | 1986-01-30 15:27:58 | Part                |


Table: Order_Items
|   order_item_id |   order_id |   product_id |   order_quantity |
|----------------:|-----------:|-------------:|-----------------:|
|               1 |          8 |           13 |                2 |
|               2 |          1 |           10 |                2 |
|               3 |         13 |           11 |                4 |
|               4 |          8 |            1 |                7 |
|               5 |          2 |            7 |                7 |
|               6 |          5 |            5 |                4 |
|               7 |         14 |            2 |                1 |
|               8 |          1 |            1 |                9 |
|               9 |          2 |            8 |                7 |
|              10 |          6 |            4 |                7 |


Question: What is the order status code that is most common?

db_id: customers_and_orders
tables: name: Products
data: Products.csv
name: Addresses
data: Addresses.csv
name: Customers
data: Customers.csv
name: Customer_Orders
data: Customer_Orders.csv
name: Order_Items
data: Order_Items.csv
label: SELECT order_status_code FROM Customer_orders GROUP BY order_status_code ORDER BY count(*) DESC LIMIT 1
sqlite_path: $MMTU_HOME/data_sqlite/spider/spider_data/test_database/customers_and_orders/customers_and_orders.sqlite