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The Daily Trips Chart

mediumSQLGroupByDates

The ops dashboard at UrbanHop carries a bar per day showing how many bookings came in, and the shape of it is what the on-call team reads for demand spikes and dead days. Both outcomes count towards the bar: a booking that was cancelled was still demand arriving, and a day full of cancellations is exactly the kind of spike the chart exists to make visible.

The chart shows the opening stretch of the period — the seven earliest days on record — and reads left to right in date order. Days with no bookings at all have no bar.

rides — one row per booking. rider_id points at a row in riders and driver_id at a row in drivers. distance_km is the trip length in kilometres and fare the price in dollars; both are recorded when the booking is made, so a booking that never happened still carries them. status is either completed or cancelled. ride_date is the day the ride was booked for.

id rider_id driver_id distance_km fare ride_date status
1 1 1 5.2 12.5 2023-06-01 completed
2 1 4 3.0 8.0 2023-06-03 completed
3 2 2 10.0 22.0 2023-06-02 completed
4 3 1 2.1 6.5 2023-06-05 cancelled
5 3 4 4.4 11.0 2023-06-06 completed
6 4 3 7.8 18.0 2023-06-04 completed
7 5 2 1.5 5.0 2023-06-07 cancelled
8 2 2 12.3 26.5 2023-06-10 completed
9 1 1 6.6 15.0 2023-06-12 completed
10 4 3 3.3 9.0 2023-06-15 completed
11 5 2 8.8 19.5 2023-06-18 completed
12 3 4 2.9 7.5 2023-06-20 cancelled

The table already exists in the database — there is nothing to create or load.

Task: Write a query that returns one row per day, with ride_date and how many bookings fall on that day as rides, counting every booking regardless of status. Earliest day first, keeping only the seven earliest days.

Example output

Shape only — these days and counts are invented:

ride_date rides
2022-09-01 4
2022-09-02 2
2022-09-03 5
2022-09-04 3
2022-09-05 6
2022-09-06 1
2022-09-07 2

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