#canssi — Public Fediverse posts

I gave a brief talk at #CANSSI Ontario yesterday on what I've been learning from #RStats and #RSpatial folks about interactive map-making w large vector data (e.g. 200k+ features)

Slides: https://silviacanelon.com/talk/2022-thinking-big/

I added a bonus slide after the talk to include excellent feedback from attendees 🙌

Thanks @rohanalexander for the nudge to submit & @michaeldorman84, Sharla, Ana, @milesmcbain and @vb_jens for offering suggestions featured in the slides :blobcatbaguettehero:

@rstats

I gave a brief talk at #CANSSI Ontario yesterday on what I've been learning from #RStats and #RSpatial folks about interactive map-making w large vector data (e.g. 200k+ features)

Slides: https://silviacanelon.com/talk/2022-thinking-big/

I added a bonus slide after the talk to include excellent feedback from attendees 🙌

Thanks @rohanalexander for the nudge to submit & @michaeldorman84, Sharla, Ana, @milesmcbain and @vb_jens for offering suggestions featured in the slides :blobcatbaguettehero:

@rstats

I gave a brief talk at #CANSSI Ontario yesterday on what I've been learning from #RStats and #RSpatial folks about interactive map-making w large vector data (e.g. 200k+ features)

Slides: https://silviacanelon.com/talk/2022-thinking-big/

I added a bonus slide after the talk to include excellent feedback from attendees 🙌

Thanks @rohanalexander for the nudge to submit & @michaeldorman84, Sharla, Ana, @milesmcbain and @vb_jens for offering suggestions featured in the slides :blobcatbaguettehero:

@rstats

I gave a brief talk at #CANSSI Ontario yesterday on what I've been learning from #RStats and #RSpatial folks about interactive map-making w large vector data (e.g. 200k+ features)

Slides: https://silviacanelon.com/talk/2022-thinking-big/

I added a bonus slide after the talk to include excellent feedback from attendees 🙌

Thanks @rohanalexander for the nudge to submit & @michaeldorman84, Sharla, Ana, @milesmcbain and @vb_jens for offering suggestions featured in the slides :blobcatbaguettehero:

@rstats

I gave a brief talk at #CANSSI Ontario yesterday on what I've been learning from #RStats and #RSpatial folks about interactive map-making w large vector data (e.g. 200k+ features)

Slides: https://silviacanelon.com/talk/2022-thinking-big/

I added a bonus slide after the talk to include excellent feedback from attendees 🙌

Thanks @rohanalexander for the nudge to submit & @michaeldorman84, Sharla, Ana, @milesmcbain and @vb_jens for offering suggestions featured in the slides :blobcatbaguettehero:

@rstats

@vb_jens gave a very meaningful presentation at #CANSSI on the #officialstatistics data ecosystem in Canada, specifically for the georeferenced data, and how the different APIs can talk to one another and be piped https://mountainmath.ca/canssi/

The part that is generalizable to other applications is `library(tongfen)` to get the least common denominator to the geographies like census tracts from different vintages (or I would guess census tracts to postal codes).

#rstats #ggplot #datascience #gis

@vb_jens gave a very meaningful presentation at #CANSSI on the #officialstatistics data ecosystem in Canada, specifically for the georeferenced data, and how the different APIs can talk to one another and be piped https://mountainmath.ca/canssi/

The part that is generalizable to other applications is `library(tongfen)` to get the least common denominator to the geographies like census tracts from different vintages (or I would guess census tracts to postal codes).

#rstats #ggplot #datascience #gis

@vb_jens gave a very meaningful presentation at #CANSSI on the #officialstatistics data ecosystem in Canada, specifically for the georeferenced data, and how the different APIs can talk to one another and be piped https://mountainmath.ca/canssi/

The part that is generalizable to other applications is `library(tongfen)` to get the least common denominator to the geographies like census tracts from different vintages (or I would guess census tracts to postal codes).

#rstats #ggplot #datascience #gis

@vb_jens gave a very meaningful presentation at #CANSSI on the #officialstatistics data ecosystem in Canada, specifically for the georeferenced data, and how the different APIs can talk to one another and be piped https://mountainmath.ca/canssi/

The part that is generalizable to other applications is `library(tongfen)` to get the least common denominator to the geographies like census tracts from different vintages (or I would guess census tracts to postal codes).

#rstats #ggplot #datascience #gis

@apreshill such a terrific presentation at #CANSSI -- see https://www.apreshill.com/talk/2022-canssi-happiest-nb/ #datascience #rstats #rmarkdown #quarto #jupyter

Alison talked about what *is* a notebook; the features of good notebooks -- good and bad smells around organizing notebooks; the features that add to usability and readability and overall utility of notebooks. I can steal every slide and explain how it applies to my work :heart:. Immersion in #DisneyWorld constructed reality is a bonus.

@apreshill such a terrific presentation at #CANSSI -- see https://www.apreshill.com/talk/2022-canssi-happiest-nb/ #datascience #rstats #rmarkdown #quarto #jupyter

Alison talked about what *is* a notebook; the features of good notebooks -- good and bad smells around organizing notebooks; the features that add to usability and readability and overall utility of notebooks. I can steal every slide and explain how it applies to my work :heart:. Immersion in #DisneyWorld constructed reality is a bonus.

@apreshill such a terrific presentation at #CANSSI -- see https://www.apreshill.com/talk/2022-canssi-happiest-nb/ #datascience #rstats #rmarkdown #quarto #jupyter

Alison talked about what *is* a notebook; the features of good notebooks -- good and bad smells around organizing notebooks; the features that add to usability and readability and overall utility of notebooks. I can steal every slide and explain how it applies to my work :heart:. Immersion in #DisneyWorld constructed reality is a bonus.

@apreshill such a terrific presentation at #CANSSI -- see https://www.apreshill.com/talk/2022-canssi-happiest-nb/ #datascience #rstats #rmarkdown #quarto #jupyter

Alison talked about what *is* a notebook; the features of good notebooks -- good and bad smells around organizing notebooks; the features that add to usability and readability and overall utility of notebooks. I can steal every slide and explain how it applies to my work :heart:. Immersion in #DisneyWorld constructed reality is a bonus.