Learning and using R - together in National Capital Region

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R101 - Learning R together (Lunch and Learn)

Home Resources CommunityLunches with Data Challenges R101

This page provides information related Lunch and Learn “R Ottawa” meet-up sessions organized by Dmitry Gorodnichy with his colleagues in Gov’t of Canada. In interactive hands-on way Dmitry shows how to build from scratch Data Science Apps, such as iTrack Covid (https://itrack.shinyapps.io/covid), using open source data in R.

These 40-min sessions are done via Zoom each Wednesday and Friday, are open to public and are recorded. If you missed a session, you can watch it on YouTube: “Learning R: Computer Science Way” (Building a COVID App from scratch) to catch up.

Commonly, each session touches on three topics:

No programming experience or data science background required. No installation of software is needed either. All coding is done in https://rstudio.cloud. It’s free, no subscription required, and is greatly supported by community.

For all questions please contact: Dmitry.Gorodnichy@cbsa-asfc.gc.ca (or Dmitry.Gorodnichy@gmail.com)

Homework for the week:

Session 8, Fri: 2020/05/29 -

Note: There will be a break in Lunch and Learn R sessions, after this session.

Session 7: Wed: 2020/05/27 - video

Session 6: 2020/05/22 - video

Our first fully-automated Report: printing graphs for all states in a for loop

New Files:

Session 5: 2020/05/20 - video

We’ll continue where we left: merging it all, running it all, and plotting, and then kniting our first Automated Report in RMarkdown.

Topics :

New Files:

Session 4: 2020/05/15 - Special Edition to catch up for those who missed first two sessions video

Topics :

Session 3: 2020/05/13 - video

Third session talks about the difference Computing Science (aka Computer Science) vs. Data Science, and what we are learning here: We learn how to program in R the way Computer Scietists program, and how to building tools (or algorithms) that find answers to our Data-related questions (such as “Where Covid is the worst tomorrow?” - which is Computer Science, as opposed to Data Science, where Data is visualized or processed, but no tools are developed and it is still a human who needs to find the answer.

A better name for this course should be CMPUT 101 - Introduction to Computing, which is the name of the course that Dmitry taught at the University of Alberta (back in 1999 it was Matlab that we used,rather than R), instead of R101 (which may lead to think we are learning something else).

Topics covered:

1- Refresher on how to start: from knowing nothing (see also first session)
2- Analysing situation in Quebec (recap of last session findings), and in US /New York (this session focus)
3- More about data.table
4- Functions
5- Simple but complete Covid App tool example (01-report.Rmd) - no-interactivity

R: (01-read.R)

R Markdown: (01-report.Rmd)

Session 2: 2020/05/06 - video

In our second session, we continue from where we left: we will open the .csv file from JHU and analyze it in a number of ways. The R script that we have started creating last time in rstudio.cloud is copied to /r101 folder: 01-read.R

Topics covered:

Session 1: 2020/04/29 - video / transcript

This is our first Live recorded session…

Topics covered:

  1. your first steps to start learning R: go to www.rstudio.com, and follow to Resources- Education-For Learners-Tutorials- ending up in https://rstudio.cloud and finding tutorials there: Learn - Primers - The Basics - Visualization Basics
  2. your first steps to start programming in R: New Project, New File - R Script, first executed one line (to read .csv file using fread() ), first error (could not find function), first installed package (library(data.table))
  3. your first R-powered document and App: New File - R Markdown
  4. your first tricks and take-aways