Skip to content

Latest commit

 

History

History
80 lines (59 loc) · 1.93 KB

File metadata and controls

80 lines (59 loc) · 1.93 KB
comments difficulty edit_url
true
Easy

中文文档

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

Solution 1

Python3

import pandas as pd


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