Daily Temperature Increase Detector

EASY10 pts

You are given a table named Weather with daily measurements:

id: unique row identifier
recordDate: calendar date for the reading
temperature: measured value for that date

Return the ids of all days where temperature is strictly higher than the temperature on the previous calendar day.

Important rule:

Comparison is allowed only if yesterday's date exists in the table.
If the previous date is missing, that row must not be included.

Output requirements:

Return exactly one column: id
Row order can be arbitrary unless your local test setup requires deterministic ordering

This problem should be solvable in both:

SQL (SQLite 3.27.2)
Pandas

Example

Input

Weather:
| 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},
  {"id": 4}
]

Explanation

Day 2 is warmer than day 1 (25 > 10), and day 4 is warmer than day 3 (30 > 20). Day 3 is not included because it is cooler than day 2.

Example

Input

Weather:
| id | recordDate | temperature |
|----|------------|-------------|
| 10 | 2024-05-01 | 12          |
| 11 | 2024-05-03 | 18          |
| 12 | 2024-05-04 | 19          |

Output

[
  {"id": 12}
]

Explanation

Id 11 is not compared to id 10 because 2024-05-02 is missing. Id 12 is compared to id 11 and qualifies since 19 > 18.

Example

Input

Weather:
| id | recordDate | temperature |
|----|------------|-------------|
| 21 | 2023-12-31 | -2          |
| 22 | 2024-01-01 | -2          |
| 23 | 2024-01-02 | 1           |

Output

[
  {"id": 23}
]

Explanation

Equal temperatures do not count as an increase. Only id 23 is strictly warmer than the previous day.

Accepted0/0·0% Acceptance

Constraints

1 <= number of rows in Weather <= 10,000
Weather.id is unique
Weather.recordDate is unique
temperature is an integer and may be negative
Use SQLite 3.27.2 semantics for SQL submissions
For Pandas submissions, return a DataFrame with exactly one column: id

Code

Visualizer

Solutions

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Test Cases3

Results

Submissions

weather =

[{"id":1,"recordDate":"2015-01-01","temperature":10},{"id":2,"recordDate":"2015-01-02","temperature":25},{"id":3,"recordDate":"2015-01-03","temperature":20},{"id":4,"recordDate":"2015-01-04","temperature":30}]

Daily Temperature Increase Detector

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Daily Temperature Increase Detector

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