This Leetcode problem Rising Temperature LeetCode Solution is done in SQL.
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Rising Temperature LeetCode Solution
Table of Contents
Problem Statement
Column Name | Type |
id | int |
recordDate | date |
temperature | int |
Weather
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:
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).
Rising Temperature LeetCode Solution MySQL
select
w1.Id
from
Weather as w1,
Weather as w2
where
datediff(w1.RecordDate, w2.RecordDate) = 1
and w1.Temperature > w2.Temperature;
Code language: SQL (Structured Query Language) (sql)
Rising Temperature LeetCode Solution Pandas
import pandas as pd
def rising_temperature(weather: pd.DataFrame) -> pd.DataFrame:
# Ensure the 'recordDate' column is a datetime type
weather['recordDate'] = pd.to_datetime(weather['recordDate'])
# Create a copy of the weather DataFrame with a 1 day shift
weather_shifted = weather.copy()
weather_shifted['recordDate'] = weather_shifted['recordDate'] + pd.to_timedelta(1, unit='D')
# Merging the DataFrames on the 'recordDate' column to find consecutive dates
merged_df = pd.merge(weather, weather_shifted, on='recordDate', suffixes=('_today', '_yesterday'))
# Finding rows where the temperature is greater on the current day compared to the previous day
result = merged_df[merged_df['temperature_today'] > merged_df['temperature_yesterday']][['id_today']].rename(columns={'id_today': 'Id'})
return result
Code language: SQL (Structured Query Language) (sql)