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