Statistics Canada Retail Food Prices
Statistics Canada Retail Food Prices
Statistics Canada table 18-10-0245-01 provides monthly average retail prices for 110 food products in a bulk CSV ZIP, with reference month, geography, product and package size, Canadian-dollar value, status and vector fields. The averages come from retailer transaction data and download without a key.
Required Attribution:
Source: Statistics Canada, Monthly average retail prices for selected products: Food, reference date. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
Coverage
The bulk series runs monthly from January 2017 through August 2026 and covers Canada, ten provinces, Whitehorse and Yellowknife. The page was modified and the checked ZIP was generated October 7, 2026; availability for the two northern geographies is incomplete for confidentiality reasons.
Verdict
This is a regional food-cost signal across meat, dairy, produce, pantry and prepared-food categories. It is not a pure price index: changing products, package mixes and purchasing patterns can change the average from month to month. Statistics Canada says the data are subject to revision, and the January 2024 retailer expansion creates a comparison break. Yukon and Northwest Territories coverage starts with the September 2025 release and omits some prices.
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Use in your agent
Load Canadian retail food prices into pandas and Parquet. Checked against the provider's documentation on Nov 1, 2026.
Access
- No account or key. The official bulk ZIP contains the full CSV and a metadata CSV.
Request
curl -O 'https://www150.statcan.gc.ca/n1/en/tbl/csv/18100245-eng.zip'Format
ZIP containing a CSV with reference month, geography, product, unit, scalar, vector, value and status fields, plus a metadata CSV.
Load into pandas and Parquet
Needs Python 3 with requests, pandas and pyarrow.
"""Statistics Canada monthly retail-price table 18-10-0245-01 -> pandas -> Parquet."""
import io
import zipfile
import requests
import pandas as pd
URL = "https://www150.statcan.gc.ca/n1/en/tbl/csv/18100245-eng.zip"
r = requests.get(URL, timeout=60)
r.raise_for_status()
with zipfile.ZipFile(io.BytesIO(r.content)) as z:
df = pd.read_csv(z.open("18100245.csv"), low_memory=False)
df["REF_DATE"] = pd.to_datetime(df["REF_DATE"], format="%Y-%m")
df.to_parquet("statcan_monthly_retail_food_prices.parquet", index=False)
print(len(df), "rows", df["REF_DATE"].min().date(), "to", df["REF_DATE"].max().date(),
df["GEO"].nunique(), "geographies", df["Products"].nunique(), "products")Run by us on 2026-11-01 (python 3.13.5 | pandas 3.1.0 | pyarrow 26.0.0 | requests 2.34.2). Result: 141432 rows 2017-01-01 to 2026-08-01 13 geographies 110 products
Limits
- Rate limit: Not stated.
- The table is monthly; the tested bulk file contains 141,432 rows.
- Not all 110 prices are available for Yukon and the Northwest Territories because of confidentiality.
Quirks
- These are category averages, not constant-quality indexes; composition and package mix can change over time.
- The retailer sample expanded for January 2024, affecting month-over-month and 12-month comparisons around that date.
- Product labels embed a specific or standardized package size and should not be stripped during grouping.
Terms and attribution
- The Statistics Canada Open Licence permits reuse and value-added products under its conditions.
- The specified Statistics Canada source notice must be maintained.
Sources
- https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810024502: “Prices are based on transaction data from Canadian retailers, and are presented in Canadian current dollars.”
- https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1810024502: “Data are subject to revision.”
- https://www.statcan.gc.ca/en/terms-conditions/open-licence: “Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.”
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