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"title": "Big Countries",
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"content": "<p>Table: <code>World</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| name | varchar |\n| continent | varchar |\n| area | int |\n| population | int |\n| gdp | bigint |\n+-------------+---------+\nname is the primary key (column with unique values) for this table.\nEach row of this table gives information about the name of a country, the continent to which it belongs, its area, the population, and its GDP value.\n</pre>\n\n<p> </p>\n\n<p>A country is <strong>big</strong> if:</p>\n\n<ul>\n\t<li>it has an area of at least three million (i.e., <code>3000000 km<sup>2</sup></code>), or</li>\n\t<li>it has a population of at least twenty-five million (i.e., <code>25000000</code>).</li>\n</ul>\n\n<p>Write a solution to find the name, population, and area of the <strong>big countries</strong>.</p>\n\n<p>Return the result table in <strong>any order</strong>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p> </p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:</strong> \nWorld table:\n+-------------+-----------+---------+------------+--------------+\n| name | continent | area | population | gdp |\n+-------------+-----------+---------+------------+--------------+\n| Afghanistan | Asia | 652230 | 25500100 | 20343000000 |\n| Albania | Europe | 28748 | 2831741 | 12960000000 |\n| Algeria | Africa | 2381741 | 37100000 | 188681000000 |\n| Andorra | Europe | 468 | 78115 | 3712000000 |\n| Angola | Africa | 1246700 | 20609294 | 100990000000 |\n+-------------+-----------+---------+------------+--------------+\n<strong>Output:</strong> \n+-------------+------------+---------+\n| name | population | area |\n+-------------+------------+---------+\n| Afghanistan | 25500100 | 652230 |\n| Algeria | 37100000 | 2381741 |\n+-------------+------------+---------+\n</pre>\n",
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"exampleTestcases": "{\"headers\": {\"World\": [\"name\", \"continent\",\t\"area\",\t\"population\", \"gdp\"]}, \"rows\": {\"World\": [[\"Afghanistan\", \"Asia\", 652230, 25500100, 20343000000], [\"Albania\", \"Europe\", 28748, 2831741, 12960000000], [\"Algeria\", \"Africa\", 2381741, 37100000, 188681000000], [\"Andorra\", \"Europe\", 468, 78115,\t3712000000], [\"Angola\", \"Africa\", 1246700, 20609294, 100990000000]]}}",
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"code": "import pandas as pd\n\ndef big_countries(world: pd.DataFrame) -> pd.DataFrame:\n ",
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"sampleTestCase": "{\"headers\": {\"World\": [\"name\", \"continent\",\t\"area\",\t\"population\", \"gdp\"]}, \"rows\": {\"World\": [[\"Afghanistan\", \"Asia\", 652230, 25500100, 20343000000], [\"Albania\", \"Europe\", 28748, 2831741, 12960000000], [\"Algeria\", \"Africa\", 2381741, 37100000, 188681000000], [\"Andorra\", \"Europe\", 468, 78115,\t3712000000], [\"Angola\", \"Africa\", 1246700, 20609294, 100990000000]]}}",
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"insert into World (name, continent, area, population, gdp) values ('Afghanistan', 'Asia', '652230', '25500100', '20343000000')",
"insert into World (name, continent, area, population, gdp) values ('Albania', 'Europe', '28748', '2831741', '12960000000')",
"insert into World (name, continent, area, population, gdp) values ('Algeria', 'Africa', '2381741', '37100000', '188681000000')",
"insert into World (name, continent, area, population, gdp) values ('Andorra', 'Europe', '468', '78115', '3712000000')",
"insert into World (name, continent, area, population, gdp) values ('Angola', 'Africa', '1246700', '20609294', '100990000000')"
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