README.md

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true	简单	https://github.com/doocs/leetcode/edit/main/solution/2800-2899/2887.Fill%20Missing%20Data/README.md	Pandas

2887. 填充缺失值

English Version

题目描述

DataFrame products
+-------------+--------+
| Column Name | Type   |
+-------------+--------+
| name        | object |
| quantity    | int    |
| price       | int    |
+-------------+--------+

编写一个解决方案，在 quantity 列中将缺失的值填充为 0。

返回结果如下示例所示。

 

示例 1：

输入：
+-----------------+----------+-------+
| name            | quantity | price |
+-----------------+----------+-------+
| Wristwatch      | 32       | 135   |
| WirelessEarbuds | None     | 821   |
| GolfClubs       | None     | 9319  |
| Printer         | 849      | 3051  |
+-----------------+----------+-------+
输出：
+-----------------+----------+-------+
| name            | quantity | price |
+-----------------+----------+-------+
| Wristwatch      | 32       | 135   |
| WirelessEarbuds | 0        | 821   |
| GolfClubs       | 0        | 9319  |
| Printer         | 849      | 3051  |
+-----------------+----------+-------+
解释：
Toaster 和 Headphones 的数量被填充为 0。

解法

方法一

Python3

import pandas as pd


def fillMissingValues(products: pd.DataFrame) -> pd.DataFrame:
    products['quantity'] = products['quantity'].fillna(0)
    return products