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1000 results for “smach”
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New to me: There's a Shiny Assistant within GitHub Copilot in VSCode to help you with Shiny code. Start asking it questions with @shiny.
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New to me: There's a Shiny Assistant within GitHub Copilot in VSCode to help you with Shiny code. Start asking it questions with @shiny.
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New to me: There's a Shiny Assistant within GitHub Copilot in VSCode to help you with Shiny code. Start asking it questions with @shiny.
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New to me: There's a Shiny Assistant within GitHub Copilot in VSCode to help you with Shiny code. Start asking it questions with @shiny.
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New to me: There's a Shiny Assistant within GitHub Copilot in VSCode to help you with Shiny code. Start asking it questions with @shiny.
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Fun R Shiny app that lets you analyze your Goodreads reading data. By Gigi Kenneth.
App: https://gkenneth.shinyapps.io/goodreads2/
Code: https://github.com/gigikenneth/goodreads2
#RStats #RShiny #ShinyConf2025 #ShinyConf -
Fun R Shiny app that lets you analyze your Goodreads reading data. By Gigi Kenneth.
App: https://gkenneth.shinyapps.io/goodreads2/
Code: https://github.com/gigikenneth/goodreads2
#RStats #RShiny #ShinyConf2025 #ShinyConf -
Fun R Shiny app that lets you analyze your Goodreads reading data. By Gigi Kenneth.
App: https://gkenneth.shinyapps.io/goodreads2/
Code: https://github.com/gigikenneth/goodreads2
#RStats #RShiny #ShinyConf2025 #ShinyConf -
Fun R Shiny app that lets you analyze your Goodreads reading data. By Gigi Kenneth.
App: https://gkenneth.shinyapps.io/goodreads2/
Code: https://github.com/gigikenneth/goodreads2
#RStats #RShiny #ShinyConf2025 #ShinyConf -
Fun R Shiny app that lets you analyze your Goodreads reading data. By Gigi Kenneth.
App: https://gkenneth.shinyapps.io/goodreads2/
Code: https://github.com/gigikenneth/goodreads2
#RStats #RShiny #ShinyConf2025 #ShinyConf -
Extremely robust and well designed Shiny app from Curbcut, making massive amounts of local city data accessible via maps. They dealt with performance issues partly by pre-computing data for every city block 🤯 and storing those in qs files, as well as rendering pre-generated Mapbox vector tiles.
Worth watching the talk by Maxime Bélanger de Blois if/when it's online.
App: https://montreal.curbcut.ca/
GitHub: https://github.com/Curbcut/curbcut-montreal
#RShiny #RStats #ShinyConf2025 #ShinyConf #dataviz -
Extremely robust and well designed Shiny app from Curbcut, making massive amounts of local city data accessible via maps. They dealt with performance issues partly by pre-computing data for every city block 🤯 and storing those in qs files, as well as rendering pre-generated Mapbox vector tiles.
Worth watching the talk by Maxime Bélanger de Blois if/when it's online.
App: https://montreal.curbcut.ca/
GitHub: https://github.com/Curbcut/curbcut-montreal
#RShiny #RStats #ShinyConf2025 #ShinyConf #dataviz -
Extremely robust and well designed Shiny app from Curbcut, making massive amounts of local city data accessible via maps. They dealt with performance issues partly by pre-computing data for every city block 🤯 and storing those in qs files, as well as rendering pre-generated Mapbox vector tiles.
Worth watching the talk by Maxime Bélanger de Blois if/when it's online.
App: https://montreal.curbcut.ca/
GitHub: https://github.com/Curbcut/curbcut-montreal
#RShiny #RStats #ShinyConf2025 #ShinyConf #dataviz -
Extremely robust and well designed Shiny app from Curbcut, making massive amounts of local city data accessible via maps. They dealt with performance issues partly by pre-computing data for every city block 🤯 and storing those in qs files, as well as rendering pre-generated Mapbox vector tiles.
Worth watching the talk by Maxime Bélanger de Blois if/when it's online.
App: https://montreal.curbcut.ca/
GitHub: https://github.com/Curbcut/curbcut-montreal
#RShiny #RStats #ShinyConf2025 #ShinyConf #dataviz -
Extremely robust and well designed Shiny app from Curbcut, making massive amounts of local city data accessible via maps. They dealt with performance issues partly by pre-computing data for every city block 🤯 and storing those in qs files, as well as rendering pre-generated Mapbox vector tiles.
Worth watching the talk by Maxime Bélanger de Blois if/when it's online.
App: https://montreal.curbcut.ca/
GitHub: https://github.com/Curbcut/curbcut-montreal
#RShiny #RStats #ShinyConf2025 #ShinyConf #dataviz -
Interactive Web app creates alternative text from a plot. By @ivelasq3 built with the R Shiny framework and {ellmer}, {shinychat}, {magick} & other #RStats 📦s
App: https://posit-ai-altr.share.connect.posit.cloud/
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Interactive Web app creates alternative text from a plot. By @ivelasq3 built with the R Shiny framework and {ellmer}, {shinychat}, {magick} & other #RStats 📦s
App: https://posit-ai-altr.share.connect.posit.cloud/
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Interactive Web app creates alternative text from a plot. By @ivelasq3 built with the R Shiny framework and {ellmer}, {shinychat}, {magick} & other #RStats 📦s
App: https://posit-ai-altr.share.connect.posit.cloud/
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Interactive Web app creates alternative text from a plot. By @ivelasq3 built with the R Shiny framework and {ellmer}, {shinychat}, {magick} & other #RStats 📦s
App: https://posit-ai-altr.share.connect.posit.cloud/
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Interactive Web app creates alternative text from a plot. By @ivelasq3 built with the R Shiny framework and {ellmer}, {shinychat}, {magick} & other #RStats 📦s
App: https://posit-ai-altr.share.connect.posit.cloud/
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What ID can you use to get data for a specific topic in the US Census 1-year American Community Survey? I made an experimental Custom GPT where you ask a natural language question and get a response. Free ChatGPT account needed.
https://chatgpt.com/g/g-67c7c1012ea081918c52c6f25480af2b-find-american-community-survey-1-year-variable-ids
#USCensus #Census #GenAI #DDJ -
4 tools for chatting with your data: NotebookLM, ChatGPT Projects, Claude Projects, and Perplexity Spaces
https://www.computerworld.com/article/3846926/chat-with-your-data-queries-genai-tools-compared.htmlMy latest for #Computerworld
#GenAI -
"Working with Decennial Census Data in R" - video from last week's workshop with Kyle Walker now up on YouTube
https://www.youtube.com/watch?v=8NKj8yF2gfo
Final workshop in the 3-part series is *tomorrow*, Wednesday Feb 26 noon to 3 pm: Mapping and Spatial Analysis with US Census Data in R. Info: https://ssdan.net/events/the-2025-ssdan-webinar-series-2023-acs-data-with-r-mapping-tools-and-the-2020-census/
#RStats #RSpatial #GIS #USCensus -
I LOVE the family-friendly New Year's Eve fun planned for a local rail trail today! Fire pits, games, treats, music - all free.
FYI 4:30 to 7:30 pm Cochituate Rail Trail if you're in the area.#Natick: https://www.friendsofnaticktrails.org/crtnye
#Framingham: https://mailchi.mp/0c6e4a846f0d/welcome-to-friends-of-framingham-trails-12726582
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2/2 Also from Kyle Walker: "Copy-paste in this example to try it out, which fits in a post":
library(tidycensus)
library(mapview)get_acs(
geography = "tract",
variables = "B19013_001",
state = "TX",
county = "Tarrant",
year = 2023,
geometry = TRUE
) |>
mapview(zcol = "estimate",
layer.name = "Median HH income<br>2019-2023 ACS")tidycensus: https://walker-data.com/tidycensus/
Kyle's book on analyzing Census data: https://walker-data.com/census-r/ -
From Kyle Walker: "It's release day for the 2019-2023 American Community Survey 5-year data!
"The ACS is a phenomenal PUBLIC and FREE resource for granular demographic information about the US.
"Use the new data *right now* with the
#rstats tidycensus package. Just swap in `year = 2023` in your call to `get_acs()`!"With just a few lines of R code, you can map and explore thousands of variables at the neighborhood level anywhere in the US." 1/2
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👀Fred Moser has an early version of a "lightweight Tabulator.js integration for R/Shiny" -- an HTMLWidget for Tabulator.js to create interactive, editable HTML tables.
{amtabulator} #rstats 📦info: https://fxi.io/amtabulator/
More on the underlying Tabulator.js library: https://tabulator.info/
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New open-source speech-to-text model Moonshine “returns results faster and more efficiently than the current state of the art, OpenAI’s Whisper, while matching or exceeding its accuracy” one of its creators says. “Key improvements are an architecture that offers an overall 1.7x speed boost compared to Whisper, and a flexibly-sized input window.”
Blog post by Pete Warden: https://petewarden.com/2024/10/21/introducing-moonshine-the-new-state-of-the-art-for-speech-to-text/
GitHub: https://github.com/usefulsensors/moonshine
Paper: https://arxiv.org/abs/2410.15608 -
New open-source speech-to-text model Moonshine “returns results faster and more efficiently than the current state of the art, OpenAI’s Whisper, while matching or exceeding its accuracy” one of its creators says. “Key improvements are an architecture that offers an overall 1.7x speed boost compared to Whisper, and a flexibly-sized input window.”
Blog post by Pete Warden: https://petewarden.com/2024/10/21/introducing-moonshine-the-new-state-of-the-art-for-speech-to-text/
GitHub: https://github.com/usefulsensors/moonshine
Paper: https://arxiv.org/abs/2410.15608 -
New open-source speech-to-text model Moonshine “returns results faster and more efficiently than the current state of the art, OpenAI’s Whisper, while matching or exceeding its accuracy” one of its creators says. “Key improvements are an architecture that offers an overall 1.7x speed boost compared to Whisper, and a flexibly-sized input window.”
Blog post by Pete Warden: https://petewarden.com/2024/10/21/introducing-moonshine-the-new-state-of-the-art-for-speech-to-text/
GitHub: https://github.com/usefulsensors/moonshine
Paper: https://arxiv.org/abs/2410.15608