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47 lines
1.6 KiB
HTML
47 lines
1.6 KiB
HTML
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<pre>
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DataFrame customers
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+-------------+--------+
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| Column Name | Type |
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+-------------+--------+
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| customer_id | int |
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| name | object |
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| email | object |
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+-------------+--------+
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</pre>
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<p>在 DataFrame 中基于 <code>email</code> 列存在一些重复行。</p>
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<p>编写一个解决方案，删除这些重复行，仅保留第一次出现的行。</p>
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<p>返回结果格式如下例所示。</p>
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<p> </p>
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<p><strong>示例 1:</strong></p>
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<pre>
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<b>输入：</b>
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+-------------+---------+---------------------+
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| customer_id | name | email |
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+-------------+---------+---------------------+
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| 1 | Ella | emily@example.com |
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| 2 | David | michael@example.com |
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| 3 | Zachary | sarah@example.com |
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| 4 | Alice | john@example.com |
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| 5 | Finn | john@example.com |
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| 6 | Violet | alice@example.com |
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+-------------+---------+---------------------+
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<b>输出：</b>
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+-------------+---------+---------------------+
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| customer_id | name | email |
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+-------------+---------+---------------------+
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| 1 | Ella | emily@example.com |
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| 2 | David | michael@example.com |
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| 3 | Zachary | sarah@example.com |
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| 4 | Alice | john@example.com |
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| 6 | Violet | alice@example.com |
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+-------------+---------+---------------------+
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<b>解释：</b>
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Alice (customer_id = 4) 和 Finn (customer_id = 5) 都使用 john@example.com，因此只保留该邮箱地址的第一次出现。
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</pre>
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