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2887. Fill Missing Data
Description
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 | None | 135 | | WirelessEarbuds | None | 821 | | GolfClubs | 779 | 9319 | | Printer | 849 | 3051 | +-----------------+----------+-------+ Output: +-----------------+----------+-------+ | name | quantity | price | +-----------------+----------+-------+ | Wristwatch | 0 | 135 | | WirelessEarbuds | 0 | 821 | | GolfClubs | 779 | 9319 | | Printer | 849 | 3051 | +-----------------+----------+-------+ Explanation: The quantity for Wristwatch and WirelessEarbuds are filled by 0.
Solutions
-
import pandas as pd def fillMissingValues(products: pd.DataFrame) -> pd.DataFrame: products['quantity'] = products['quantity'].fillna(0) return products