01 / WeatherLoading
A change in the air.
Checking forecast availability.
Agoravista / A personal projectWhat’s shaping
What’s shaping
UK retail?
A small working edition of my retail-intelligence project. Public information, brought together to explore what might matter for FMCG.
02 / CalendarLoading
Dates that matter.
The next bank holidays in the selected place’s nation.
Checking calendar availability.
From information to a questionWhat could this mean
What could this mean
for the basket?
Possible category effects, with the reasoning in view.
Interpretations will appear where supporting data is available.
03 / Published monthly contextLoading
The cost of the grocery basket.
UK food and non-alcoholic beverage inflation. Annual percentage change, published monthly by ONS.
How this working edition fits into Agoravista
The wider personal project collects public retail, weather, calendar and economic information into PostgreSQL, with a Python dashboard for exploring the relationships. This edition uses a small cloud-hosted collector and saved feed results, so it does not depend on my home server.
Weather is a point forecast for the selected city. Bank holidays follow the relevant nation’s calendar. ONS inflation is a UK monthly observation; changing the forecast period does not turn it into daily or regional data.
The category notes are transparent, illustrative rules, not fitted sales forecasts. Warm-weather notes use a sampled forecast high of at least 18°C; cool-weather notes use a high of 10°C or less. Rain-related notes are triggered by rain or shower forecast symbols. Calendar notes consider bank holidays in the next seven days.
There is no combined demand score or retailer sales prediction in this edition. Missing sources remain unavailable; an unsuccessful refresh retains the last saved result and marks it as older data.
Weather: MET Norway, CC BY 4.0. Calendar: GOV.UK. Inflation: ONS series D7G8. GOV.UK and ONS information is used under the Open Government Licence v3.0.
Why I’m building itResourcefulness,
Resourcefulness,
with a retail purpose.
Working with retail data makes you curious about what sits around the numbers: the weather, the calendar, household costs and the stories shaping the week.
Agoravista is my personal space to explore those connections. It brings together the data engineering I enjoy, the retail context I work in, and hands-on experimentation with local and cloud AI.
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