Twelve Datasets at Christmas

This Month’s Podcast. Also Available on Spreaker

This month’s post is something special to celebrate the holidays. We’re looking at twelve datasets, some Christmas related, some not, from across Canada. We’re going to cover every province and territory, so let’s get going! These are presented in the order of how we went through them on the podcast which you can listen to using the player above.

  1. Prince Edward Island
  2. Quebec
  3. Alberta
  4. Manitoba
  5. Newfoundland & Labrador
  6. Nunavut
  7. British Columbia
  8. New Brunswick
  9. Ontario
  10. Saskatchewan
  11. Nova Scotia
  12. The North

Prince Edward Island

Analyst: Katie “Green Gables” Renaud

For a small province of less than 200,000 people, P.E.I. has a great open data portal! Something we don’t have in every province are conservation plates, which as the name suggests, are license plates you can buy where the proceeds are donated to support conservation efforts. In P.E.I., those funds go directly to the PEI Wildlife Conservation Fund. Now here’s the fun part – in P.E.I, you can choose from five different icons for your conservation plate: blue jay, brook trout, Canada goose, lady slipper, and red fox. Funny enough, there’s a clear trend in favourite conservation plates. Red fox is by far the most popular icon since the plates began to be offered in 2013, consistently followed by blue jay. Canada goose beat out brook trout in the first year, but was overtaken by brook trout from 2014 to 2019. Similarly, lady slipper managed a slight lead over Canada goose in 2014 to take 4th place, but sunk to least favourite from 2015 to 2019. The islanders clearly play favourites when it comes to their conservation plates, but the competition for plates has paid off, with a few hundred thousand dollars raised since 2013 for the PEI Wildlife Conservation Fund. A few other provinces have these as well, with Nova Scotia’s funds also going to wildlife conservation and BC’s funds to parks conservation. It would be awesome to see all provinces and territories follow suit!

Source: https://data.princeedwardisland.ca/d/9pz4-ydgt

Quebec

Analyst: Frazier “Montreal Smoked” Fathers

I’ll be honest, Quebec has some great open data sources. The Province of Quebec’s open data portal not only holds provincial data but also “rolls up” many municipal data portals as well. The problem that I didn’t consider when I indifferently selected my provinces, was that almost all of them are exclusively in French. Although I have some decent french skills, but not fluent, the issue with the data is that many column headers are abbreviated in French. So it isn’t even the full French word that I could go and translate to confirm, rather the first few letters, code word or initials as column header. This did create some problems. 

As a result, trying to find a holiday theme, traveling is always a part of the holidays (most years not 2020). So the road conditions are important if you are packing up the family into a car and driving to see grandma. The Province of Quebec has a significant open data tracking of road conditions and visibility status for a number of the major provincial highways. With over 190,000 observations the spreadsheets and shapefiles. The summary of these observations look like this: 

While a quick mapping of a day in early 2020 looks like this. 

Quebec Road Condition Mapping Example for a Representative Day in Early 20202 (Click for Full Size Image)

Alberta

Analyst: Doug “Alberta Advantage” Sartori

For Alberta, we built a map using data from a variety of source: Banff’s open data portal, the Province of Alberta’s park GIS data and road network data, the federal government’s national railway network data and a crowdsourced dataset of ghost towns sourced from Wikipedia.

Here are Alberta ghost towns mapped with major highways:

Alberta Ghost Towns Mapped with Major Highways

This map shows ghost towns in Alberta relative to the railway network.

The Ghost Towns with the Rail Network

That red segment of railway is an abandoned line. Here’s a closer look at the ghost towns that were created by the closure of the railway:

Ghost Towns Where Rail Closures Contributed to Town Collapse

There are four ghost towns near the Banff tourist town and national park. These are mapped with roads and trails associated with the town.

Ghosts Towns Near Banff

Manitoba

Analyst: John “Weakerthan” Haldeman

We’ve gushed over Winnipeg’s open data portal in the past, so it was an easy choice to pick a data set concerning the province’s largest city and capital. One of the best data sets on the portal is the city’s tree inventory. Below is a visualization of that inventory. Taller hexagons represent more trees and, since this is a holiday show, the color of the hexagon represents the proportion of trees in that area that are traditionally related to Christmas trees (fir, pine, and spruce).

Visualization of Winnipeg’s Tree Inventory Showing Christmas Tree (Interactive Version)

Newfoundland & Labrador

Analyst: Katie “Screeched In” Renaud

Newfoundland seems to be, by far, the most neglected data portal on the east coast. With a dismal selection of very standard data sets and most not being updated in years, we’re looking at the top three boy and girl baby names of 2013-2017. If you’re a young boy in Newfoundland, there’s a good chance someone you know is named is Jackson, which was the top baby name from 2013-2017, only overtaken by Benjamin in 2017, which was a newcomer to the top three baby names in 2016. Otherwise, if you don’t know a Jackson, you probably know a Jack, and maybe a Liam.

Newfoundland Top Boys Names

There’s a bit more variation amongst girls in Newfoundland, but there’s a good chance you’ll know someone named Emma if you were born between 2013 and 2016, with that being the top girl baby name for those years. The other top favourite over the time period is Ava, appearing in the top three each year except 2014. Charlotte, Olivia, Sophia, and Lily make appearances in the top three throughout 2013-2017 as well.

Newfoundland Top Girls Names

Nunavut

Analyst: John “Sparsely Populated” Haldeman

The federal government, and the government Nunavut have been working with local hunters and trappers to collect data and samples from harvested ringed seals. The majority of seals are measured in the field by Inuit hunters who record date of kill, sex and blubber depth. The data from the harvested animals are used to evaluate stressors and overall seal health, in the Canadian Arctic. Here is a visualization of the collected data showing average length, weight, and number of seals sampled. You can scroll through the years and interact with the map in other ways.

The Number, Average Weight, and Average Length of Seals Harvested in 2008

British Columbia

Analyst: Doug “Sea-to-Sky” Sartori

BC lists more than 1500 data sets from many different providers on its open data portal. I wanted to focus on climate data, so I initially looked at the data from historical and present climate stations. Unfortunately, this data set was too complex for the time available this month. Hopefully we’ll pick this project up for a future podcast because there is a rich vein of information to mine from historical climate observations.

For this month, I looked at the BC Greenhouse Gas Emissions Archive, which provides a nice summary of estimated emissions by source since 1990. After a little bit of monkeying with the data to make it more graphable I used a couple of John’s favourite tools to put together a few graphs. You’ll find all the graphs, code and data here.

I started with a graph of the overall picture. Here, “Other Land Use” and Energy really dominated all other GHG emissions sources.

Here’s what the graph looks like without “Other Land Use”

Energy is the biggest emitter, so I graphed some different levels of subcategory.

Transport accounts for half of BC emissions from energy, and as such is the biggest single contributor to GHG emissions in BC, so it’s worth breaking down that subcategory a bit further.

New Brunswick

Analyst: Katie “Most Bilingual in the Podcast” Renaud

With another great east coast open data portal, we get to explore sales of alcoholic beverages in New Brunswick. This data set pits spirits, wine, beer, and ciders/coolers/and other refreshments against each other. Beer, by far, brought in the most alcohol sales consistently from 2004 to 2018, hitting its peak in 2009, selling $228,620 worth. Something to do with recession blues perhaps? Interestingly, spirits, wine, and ciders and coolers have seen a consistent, steady increase from 2004 to 2018 as well, with wine making the biggest jump from sales of $43,304 in 2004 to $99,047 in 2018, more than doubling its growth, and sitting just behind spirits in 2018, which garnered $100,755 in sales. The question is, will we continue to see wine outpace the growth of spirits and, rather stagnant, beer sales? Will it catch up to beer sales in the next decade? Only time will tell.

Alcohol Sales in New Brunswick

Ontario

Analyst: Frazier “Cottage Country” Fathers

For Ontario I pulled the official list of Christmas Tree farms list from the Ontario Government and just mapped their addresses in an easy to access google map. So if you need to get a last minute replacement trees you can easily find a source. I would point out that my family always got a tree from some lot in the county growing up, this list is by no means the most local nor exhaustive.

Ontario’s “Official” Christmas Tree Merchants

Saskatchewan

Analyst: “Prairie Doug” Sartori

Besides the public data available for Saskatchewan, Andrew Dyck maintains the Open Data SK website which lists some “liberated data” for the province, including a project to clean up a decade of Regina crime statistics and make them more usable. Combining this data set with the City of Regina’s Neighbourhood Service Area data was a bit trickier than it looked initially – Regina’s neighbourhoods as understand by the police don’t quite line up with the neighbourhood definitions the city uses. Andrew was kind enough to help provide some assistance in making the association between these two different levels of geographic aggregation. The result might not be perfect as there is surely some overlap between neighbourhoods but it provides a bit more detail than the Police-provided map. Adding in Regina road centerline data from the City’s open data portal results in this map:

Crime Map of Regina, Saskatchewan

Nova Scotia

Analyst: Katie “Blueberry” Renaud

Nova Scotia’s data portal had some interesting open data, including farm registration by commodity. 23% of farms, 557 farms in total, are registered as beef farms, which is really very few compared to a province like Alberta, with over 18,000 cattle farms. However, the 13% of farms registered as blueberry farms, 330 farms in total, are much more competitive. Apparently, blueberries are Canada’s most exported fruit, and while Quebec and New Brunswick produce more wild blueberries than Nova Scotia, third place isn’t too bad, and Oxford, NS is recognized as the blueberry capital of Canada!

Nova Scotia – Beef and Blueberries

The North

Analyst: John “Dead Last in Knuckle Hop” Haldeman

We wanted a “twelve data sets of Christmas” show, but there are thirteen provinces and territories. As such we have to fudge a little and combine the Territories. Think of the Nunavut section earlier as a bonus.

The Arctic Winter Games is a circumpolar sport competition for Northern communities in Canada and other polar countries like Russia, the USA, and the Scandinavian countries. We went to the Arctic Winter Games website and pulled the medal rankings for each year available. Here’s a graph of the rankings per year and region:

Medal Rankings for the Last Six Arctic Winter Games

That’s it! Wasn’t that enough? From all of us at Mean, Median, and Moose to you and yours, happy holidays!

One thought on “Twelve Datasets at Christmas

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s