Event 38: R/Python (Ian) talk, add timestamps

misc/38_ian_r.md

@@ -2,16 +2,64 @@ Here is an example of the description included with the YouTube video.
 video:  https://youtu.be/5c4cb6kvJGE
 
 ```text
-Event: R, an Ecosystem Where Pythonistas Can Thrive
-
 ## Upcoming Events
 Join our Meetup group for more events!
 https://www.meetup.com/data-umbrella
 
+[38] R, an Ecosystem Where Pythonistas Can Thrive (Ian Flores)
+
+## Key Links
+- Transcript: https://github.com/data-umbrella/event-transcripts/blob/main/2021/38-ian-r.md
+- Meetup Event: https://www.meetup.com/data-umbrella/events/281938125/
+- Video: https://youtu.be/5c4cb6kvJGE 
+- Slides: https://ian-flores.github.io/r-ecosystem-4-python-slides/slides.html#1
+- GH repo: https://github.com/ian-flores/r-ecosystem-4-python
+
+## Outline of Talk
+- Introduction
+- Sharing data with computers
+- Sharing data with humans
+- R tools Pythonistas should know
+- Case Study: Bilingual Data Pipeline
+
 ## Agenda
-00:00:00 to 00:05:50 Introduction to Data Umbrella 
-00:05:50 Ian Introduction
+00:00:00 Introduction to Data Umbrella 
+00:06:58 Ian begins
+00:08:03 Talk Outline
+00:09:35 3 Types of sharing data with computers (web APIs, cloud storage, database)
+00:10:27 Web APIs: Overview
+00:13:00 Accessing data from APIs using Python (urlib3, requests)
+00:14:38 Serving data with APIs using Python (flask, FastAPI)
+00:16:22 Accessing data from APIs using Rstats (httr2, curl)
+00:18:20 Serving data with APIs using R (plumber)
+00:19:51 Web APIs: {plumber}
+00:20:50 Cloud storage - overview
+00:25:04 Cloud storage - formats (JSON, YAML, CSV, TSV) 
+00:26:02 Binary formats of data; Don't use: pickles, RDS; Do use: parquet, feather, avro
+00:27:49 Data storage - databases (SQL) (Database Drivers packages: odbc, DBI, dplyr)
+00:30:52 Sharing ~data~/insights with humans
+00:31:44 RMarkdown *down-verse ({pkgdown}, {bookdown}, {blogdown}); Extensibility through YAML header ({glosario}, {lambdr}, {xaringan})
+00:35:43 Quarto (Jupyter notebooks, Knitr, ObservableJS)
+00:36:44 Shiny (Example website: https://voronoys.shinyapps.io/voronoys/)
+00:37:40 Shiny and other Python frameworks (Streamlit, Dash, Voila)
+00:39:45 R Tools Pythonistas should know
+00:40:14 {reticulate} package (call Python from within R)
+00:42:03 Workflows in R: {targets} (make-like pipeline toolkit for statistics and data science in R)
+00:43:25 {tidyverse} R packages for data science (read, clean, manipulate, visualize, etc. for data); compare to SciPy stack
+00:44:47 Similarities across R and Python; virtual environments: {renv}, virtualenv
+00:46:28 Similarities: Class Systems
+00:47:30 Limitations of R
+00:50:22 Packages in R to work with the cloud
+00:51:03 Case study: Data Pipeline (https://github.com/ian-flores/r-ecosystem-4-python)
 00:56:30 Q&A begins
+00:58:10 Q: Is it advisable to work with R and Python together?
+00:58:50 Q: working with different versions of R and Python
+00:59:30 Q: How efficient is it to use packages such as reticulate to work with both R and Python in the same document?
+01:00:22 Q: Can you use FastAPI within R?
+01:01:05 Q: What are commonly accessed Python libraries within R's reticulate package?
+01:02:22 Q: What does python's scikit-learn have that is not available in R?
+01:04:45 Q: Is R a good option for large datasets and production?
+01:06:28 Q: Can you talk about RStudio, the company? 
 01:08:30 Demo of RStudio IDE
 
 ## Event
@@ -20,10 +68,10 @@ This talk will introduce Python users to the R ecosystem. Attendees should expec
 ## Speaker
 Ian is a data person with a background in Data Science and DevOps. He has experience consulting within the pharmaceutical industry, government sector, NGOs and educational institutions in multiple countries. As part of his academic background he holds a Master’s degree in Data Science from the University of British Columbia. Outside of work, he is a certified freediver, loves to surf in the Northeast coast of Puerto Rico and cooks spicy food.
 
-## Slides:  
-https://ian-flores.github.io/r-ecosystem-4-python-slides/slides.html#1
+- LinkedIn: https://linkedin.com/in/ian-flores-siaca
+- Twitter:https://twitter.com/iflores_siaca
+- GitHub: https://github.com/ian-flores
 
-## Resources
-https://github.com/ian-flores/r-ecosystem-4-python
+#python #rstats #datascience #rvspython
 
 ```