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[[Data Science Communities of Practice]] - UseR!
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<small>[[Data Science Communities of Practice]] - UseR!</small>
  
''This page provides summaries of discussions and tutorials organized by '''User R!''' GC Community of Practice''
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====== This page provides the list of discussions organized by the GCcollab's  '''[[gccollab:groups/about/7391537|R4GC (Use R!) community]].''' Please consider contributing to those discussions by joining this community and participating in community's weekly [[gccollab:groups/about/7855030|'''"Lunch and Learn Data Science with R" meetups.''']] ======
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* General topics:
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** Why R?
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** Best way to start (and keep learning) R
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**[[gccollab:discussion/view/7391599/enevents-and-forums-for-learning-and-talking-about-rfr|Events and Forums for R users]]
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**[[gccollab:discussion/view/7789646/enexcel-rfr|From Excel to R]]
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**[[gccollab:discussion/view/7404883/enwhy-r-r-or-python-no-r-and-pythonfr|R with Python (and other languages/tools)]]
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** Efficient programming in R (coding style, memory-efficient coding, collaboration-ready codes, source control)
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**'''data.table''' for efficient data processing
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**[[gccollab:discussion/view/7909837/enreading-all-sorts-of-data-in-r-efficientlyfr|Reading various kinds of data in R]]
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** Open R codes for GC: on GCcode and GitHub
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** RStudio news and tricks
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* Specialized topics:
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**[[gccollab:discussion/view/7391596/endata-visualization-with-ggplot2-and-its-extensionsfr|'''ggplot2'''  and its extensions for data visualization]]
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**[[gccollab:discussion/view/7391594/enshiny-for-interactive-data-visualization-analysis-and-web-app-developmentfr|'''Shiny''' for Interactive Data Visualization, Analysis and Web App development]]
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**'''R Markdown''' for automated and reproducible data science
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**''Record Linking'' and other Data Engineering tasks in R
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**[[gccollab:discussion/view/7391598/engeospatial-coding-and-visualization-in-rfr|''Geo/Spatial'' coding and visualization in R]]
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**''Text Analysis'' in R
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**''Machine Learning and Modeling'' in R
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**Using R with GC data infustructure (gcdocs, AWS, etc)
  
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* R4GC community "Lunch and Learn Data Science with R" weekly meetups : (NB: you need to join the  [[gccollab:groups/about/7855030|"Lunch and Learn Data Science with R" meetups]] group to access recordings of these sessions)
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** 12 Nov - 19 Nov 2021: Text Analysis with R follow-up  / Converting codes to Shiny App
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** 8 Oct 2021: Text Analysis with R. Part 1: identifying near-duplicate documents
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** 1 Oct 2021: Shiny App to summarize very large, high-dimensional tables (code & app provided)
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** 30 Jul  - 17 Sep 2021: Geo/Spatial coding and visualization with R. (code provided)
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** 16 Jul 2021: Dual Coding - Python and R unite ! (code provided)
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** 9 Jul 2021: Exploring ggplots (recording, code provided)
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** 2 Jul 2021: Parsing GC Tables (code provided)
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** 25 Jun 2021: Using the Open Government Portal API within R ([[gccollab:file/view/8864413/envideo-notes-meetup-2021-07-25-using-the-api-for-open-data-portal-within-rfr|recording]], [https://github.com/open-canada/lunch_and_learn_opengov code on github.com/open-canada])
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** 21 Apr 2021: Analyzing PSES results using R and Shiny
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** 16 Apr - 15 May 2021: Building R packages  (recording, codes provided)
  
 
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* Webinars at RStudio - https://www.rstudio.com/resources/webinars/ (codes at https://github.com/rstudio/webinars)
Discussions at '''[[gccollab:groups/about/7391537|Use R! gccollab group]] :'''
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** The new insights from these webinars and other R-related blogs and events are discussed at R4GC community meetups
 
 
* Best way to start and keep learning R
 
* R with Python
 
* From Excel to R
 
* Reading various kinds of data in R
 
* Open R codes for GC: on GCcode and GitHub
 
* RStudio news and tricks
 
* Events and Forums for R users
 
* '''data.table''' for efficient data processing
 
* '''ggplot2'''  and its extensions for data visualization
 
* '''Shiny''' for Web App development, Interactive Data Visualization and Analysis
 
* '''R Markdown''' for reproducible research and development
 
* Record Linking and other Data Engineering tasks in R
 
* Geo/Spatial coding and visualization in R
 
* Text Analysis in R
 
* Machine Learning and Modeling in R
 
 
 
 
 
Webinars at [[gccollab:groups/about/7855030|Friday's "Lunch and Learn Data Science with R" meetups]]:
 
 
 
* 30 Jul 2021: Geospatial data tools in R (code)
 
* 16 Jul 2021: Dual Coding - Python and R unite!
 
* 9 Jul 2021: Exploring ggplots (recording, code)
 
* 2 Jul 2021: Parsing GC Tables (code)
 
* 25 Jun 2021: Using the API for open data portal within R (recording, code)
 
* Analyzing PSES results using R and Shiny: 21 Apr 2021
 
* Building R packages: 16 Apr 2021 - 21 Apr 2021 (recording, code)
 
 
 
 
 
See also webinars at RStudio: https://www.rstudio.com/resources/webinars/ (codes at https://github.com/rstudio/webinars)
 

Latest revision as of 08:19, 27 October 2021

Data Science Communities of Practice - UseR!

This page provides the list of discussions organized by the GCcollab's R4GC (Use R!) community. Please consider contributing to those discussions by joining this community and participating in community's weekly "Lunch and Learn Data Science with R" meetups.
  • R4GC community "Lunch and Learn Data Science with R" weekly meetups : (NB: you need to join the "Lunch and Learn Data Science with R" meetups group to access recordings of these sessions)
    • 12 Nov - 19 Nov 2021: Text Analysis with R follow-up / Converting codes to Shiny App
    • 8 Oct 2021: Text Analysis with R. Part 1: identifying near-duplicate documents
    • 1 Oct 2021: Shiny App to summarize very large, high-dimensional tables (code & app provided)
    • 30 Jul - 17 Sep 2021: Geo/Spatial coding and visualization with R. (code provided)
    • 16 Jul 2021: Dual Coding - Python and R unite ! (code provided)
    • 9 Jul 2021: Exploring ggplots (recording, code provided)
    • 2 Jul 2021: Parsing GC Tables (code provided)
    • 25 Jun 2021: Using the Open Government Portal API within R (recording, code on github.com/open-canada)
    • 21 Apr 2021: Analyzing PSES results using R and Shiny
    • 16 Apr - 15 May 2021: Building R packages (recording, codes provided)