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2887. Fill Missing Data

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

Write a solution to fill in the missing value as 0 in the quantity column.

The result format is in the following example.

 

Example 1:
Input:+-----------------+----------+-------+
| name            | quantity | price |
+-----------------+----------+-------+
| Wristwatch      | 32       | 135   |
| WirelessEarbuds | None     | 821   |
| GolfClubs       | None     | 9319  |
| Printer         | 849      | 3051  |
+-----------------+----------+-------+
Output:
+-----------------+----------+-------+
| name            | quantity | price |
+-----------------+----------+-------+
| Wristwatch      | 32       | 135   |
| WirelessEarbuds | 0        | 821   |
| GolfClubs       | 0        | 9319  |
| Printer         | 849      | 3051  |
+-----------------+----------+-------+
Explanation: 
The quantity for Toaster and Headphones are filled by 0.

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import pandas as pd def fillMissingValues(products: pd.DataFrame) -> pd.DataFrame:

pythondata 解法, 执行用时: 240 ms, 内存消耗: 59 MB, 提交时间: 2023-10-07 10:36:59

'''
None填充0
'''
import pandas as pd

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

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