197. Rising Temperature

Table: Weather

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| id            | int     |
| recordDate    | date    |
| temperature   | int     |
+---------------+---------+
id is the column with unique values for this table.
There are no different rows with the same recordDate.
This table contains information about the temperature on a certain day.

 

Write a solution to find all dates' id with higher temperatures compared to its previous dates (yesterday).

Return the result table in any order.

The result format is in the following example.

 

Example 1:

Input: 
Weather table:
+----+------------+-------------+
| id | recordDate | temperature |
+----+------------+-------------+
| 1  | 2015-01-01 | 10          |
| 2  | 2015-01-02 | 25          |
| 3  | 2015-01-03 | 20          |
| 4  | 2015-01-04 | 30          |
+----+------------+-------------+
Output: 
+----+
| id |
+----+
| 2  |
| 4  |
+----+
Explanation: 
In 2015-01-02, the temperature was higher than the previous day (10 -> 25).
In 2015-01-04, the temperature was higher than the previous day (20 -> 30).

 

id이전 날짜(어제)보다 온도가 더 높은 모든 날짜를 찾는 솔루션을 작성하세요 .

결과 표를 임의의 순서 로 반환합니다 .

결과 형식은 다음 예와 같습니다.

1) 한 테이블 내에 시계열로 데이터가 구성되어 있고, 바로 전행과 현재 행을 비교해야함
2) 먼저 날짜 기준으로 데이터 타입을 바꾸어 오름차순으로 정렬해준다.
( 오래된 -> 최신 순)
3) 이전 행의 값들을 기준 행에 새로운 변수를 만들어 사용한다. 이때 shift를 사용한다.
> shift는 이전행을 한행씩 밑으로 내려주는 역할을한다. shift(1)이면 한줄씩 밑으로 내려온다.
만약 위 행으로 올리고싶다면 shift(-1)을 해주면된다.
> shift를 이용해서 온도와 날짜모두 shift하여 내려준다.

4) 3)에서 shift한 행들과 비교해서 만약 이전날+1일과 같고, 온도가 기준 일이 이전 날 보다 높다면 행을 필터하는 인덱싱 문을 작성한다.
> 이전날+1일은 + pd.Timedelta(days = 1) 으로 표현한다. 

def rising_temperature(weather: pd.DataFrame) -> pd.DataFrame:
    # step 1. Converting recordDate to Datetime Type
    weather['recordDate'] = pd.to_datetime(weather['recordDate']) 
    
    # Step 2: Sorting the DataFrame
    weather.sort_values('recordDate', ascending = True, inplace = True)

    # Step 3: Creating Columns for Previous Day's Data
    weather['before_recordDate'] = weather['recordDate'].shift(1)
    weather['before_temperature'] = weather['temperature'].shift(1)
    # Step 4: Filtering for Days with Higher Temperature than the Previous Day
    result = weather[(weather['recordDate'] == weather['before_recordDate'] + pd.Timedelta(days = 1)) &
           (weather['temperature'] > weather['before_temperature'])
    ][['id']].rename({'id':'Id'})
  
    return result

오늘 알게 된 것
pd.Timedelta(days = 1)
pd.to_datetime(weather['recordDate']) 
weather['before_temperature'] = weather['temperature'].shift(1)