This Leetcode problem Human Traffic of Stadium LeetCode Solution is done in SQL.
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Human Traffic of Stadium LeetCode Solution
Table of Contents
Problem Statement
Column Name | Type |
id | int |
visit_date | date |
people | int |
visit_date is the column with unique values for this table.
Each row of this table contains the visit date and visit id to the stadium with the number of people during the visit.
As the id increases, the date increases as well.
Write a solution to display the records with three or more rows with consecutive id
‘s, and the number of people is greater than or equal to 100 for each.
Return the result table ordered by visit_date
in ascending order.
The result format is in the following example.
Example 1:
id | visit_date | people |
1 | 2017-01-01 | 10 |
2 | 2017-01-02 | 109 |
3 | 2017-01-03 | 150 |
4 | 2017-01-04 | 99 |
5 | 2017-01-05 | 145 |
6 | 2017-01-06 | 1455 |
7 | 2017-01-07 | 199 |
8 | 2017-01-09 | 188 |
id | visit_date | people |
5 | 2017-01-05 | 145 |
6 | 2017-01-06 | 1455 |
7 | 2017-01-07 | 199 |
8 | 2017-01-09 | 188 |
Explanation: The four rows with ids 5, 6, 7, and 8 have consecutive ids and each of them has >= 100 people attended. Note that row 8 was included even though the visit_date was not the next day after row 7. The rows with ids 2 and 3 are not included because we need at least three consecutive ids.
Human Traffic of Stadium LeetCode Solution MySQL
with q1 as (
select
*,
count(*) over(
order by
id range between current row
and 2 following
) following_cnt,
count(*) over(
order by
id range between 2 preceding
and current row
) preceding_cnt,
count(*) over(
order by
id range between 1 preceding
and 1 following
) current_cnt
from
stadium
where
people > 99
)
select
id,
visit_date,
people
from
q1
where
following_cnt = 3
or preceding_cnt = 3
or current_cnt = 3
order by
visit_date
Code language: JavaScript (javascript)
Human Traffic of Stadium LeetCode Solution Pandas
import pandas as pd
def human_traffic(stadium: pd.DataFrame) -> pd.DataFrame:
stadium = stadium.sort_values("id").query("people >= 100")
stadium["row_nb"] = range(len(stadium))
stadium["id_rownb_diff"] = stadium.id - stadium.row_nb
stadium["size_of_consecutive_group"] = stadium.groupby("id_rownb_diff")["id"].transform("count")
return stadium[stadium.size_of_consecutive_group >= 3][["id","visit_date","people"]]
Code language: JavaScript (javascript)