Scarborough data projectWhat can a 9-year-old drop in to this week in Scarborough? Counting the City’s own file
The City of Toronto publishes its recreation schedule as open data. Our older kids, around ages 10 to 12, join two of its tables, keep only Scarborough, and count the sessions a child of a given age can join. Every number below is our count, not the City’s.
Our count of drop-in sessions at locations whose District is Scarborough, from the City of Toronto file downloaded 22 October 2026 (sessions dated 15 October to 26 November 2026)| Child’s age | Sessions open to that age | Scarborough locations offering one |
|---|
| 6 | 639 | 22 |
| 7 | 1,052 | 23 |
| 8 | 1,052 | 23 |
| 9 | 1,070 | 23 |
| 10 | 1,100 | 23 |
| 11 | 1,125 | 24 |
| 12 | 1,131 | 24 |
The file is Registered Programs and Drop In Courses Offering, published by Parks, Forestry & Recreation and refreshed weekly. Its notes say a drop-in “is a program offered within PFR facilities where registration is not required”. Two of its tabs matter here: Drop-in, one row per session, and Locations, one row per place, with a District column. Our download held 7,039 drop-in rows at Scarborough locations, spread over 39 of them. Here is the script a 10-year-old can type, using nothing but the Python standard library:import csv
district = {}
with open("locations.csv", encoding="utf-8") as f:
for row in csv.DictReader(f):
district[row["Location ID"]] = row["District"]
age = 9
days = {}
with open("dropin.csv", encoding="utf-8") as f:
for row in csv.DictReader(f):
if district.get(row["Location ID"]) != "Scarborough":
continue
low = int(row["Age Min"])
high = 120 if row["Age Max"] == "None" else int(row["Age Max"])
if age in range(low, high + 1):
day = row["DayOftheWeek"]
days[day] = days.get(day, 0) + 1
print(sum(days.values()), days)
1. Join the tables
A session row only gives a Location ID. The child builds a small dictionary from Locations, ID to District, then looks each session up in it. That is a join, the same idea a database uses, written in four lines.
2. Filter by age
Each row has Age Min and Age Max. A blank maximum means no upper limit, so the script treats it as 120. A session fits a 9-year-old when 9 sits inside the range, which Python checks with range.
3. Count by day
Every fitting row adds one to its weekday. For age 9 we got Saturday 191, Thursday 174, Friday 154, Sunday 150, Wednesday 144, Monday 137 and Tuesday 120: 1,070 in all, swim and skate making up most of them.
The trap in the data dictionary
The City’s field note for Age Min says “minimum allowable age in months”. The values tell a different story: ranges such as 0 to 5, 6 to 12 and 13 to 18, and a youth council open from 13 to 24. Those only make sense as years, so we read them as years and say so. Spotting that a label and its data disagree is a real skill, and children enjoy catching a grown-up file being wrong.
What the counts do not say matters as much. 273 of the sessions open to a 9-year-old name a caregiver or family in the title, so an adult has to come too. A count of sessions is not a count of places on the ice, and the file is a snapshot: change the download date and the numbers move. A good next step for the class is the after-school question: of the 1,070, how many start at 3 pm or later on a weekday? Our answer was 315. Data used under the Open Government Licence - Toronto. Contains information licensed under the Open Government Licence - Toronto (licence, dataset page). The City does not endorse this page or our classes.
