Links to resources
Packages
Python
R
R for Data Science is the best help to get you into the tidyverse
- ggplot2
- dplyr
- readr
- stringr
- tidyr
- purrr
- arrow
- sfarrow
- waffle
- ggfittext
- sf
- USAboundaries
- leaflet
- geofacet
- DBI
- tidymodels
Links about data, programming, and visualization
- Salvaging the pie
- Too many bars
- How spatial polygons shape our world (Amelia McNamara)
- How Humans See Data (John Rauser)
- Investigating Anomalies (John Rauser)
- Grammar of Graphics DataCamp
- Effectively Communicating Numbers
- Data Visualization (Chapter 1 - Look at data)
Being readings
Structured thinking
- Questions and data science
- Computational Thinking and Optional Reading for new programmers
- How to Become a Data Scientist, The Self-Starter Way and What’s The Best Path To Becoming A Data Scientist?
- What do people do with new data
- The art of structured thinking and analyzing and Tools for improving structured thinking (for analysts)
Data and data thinking
- Hadley on Tidy Data (skim read)
- Quartz Reference for How to deal with data issues (optional)
- Statistical Concepts in Presenting Data
- What charts say and What charts do
- Chapter 4: The Truthful Art: Data, Charts, and Maps for Communication
- Issues with Spatial Aggregation
- Gelman on p hacking
- Of beauty, sex, and power: Statistical challenges in estimating small effects
- NoSQL vs. SQL: The Future of Data
Ethics and data science
- Ethics of a Data Scientist
- An ethical code can’t be about ethics and Ethical codes vs. ethical code
- What insurance allready does
- Big Data and Civil Rights
- The ethics of web scraping
- Big data and the Underground Railroad and Machine Learning, Physiognomy, and Hidden Bias
- Ethics in Data Science (4 episodes)
- How big data is unfair
- Who decides the ethics
- What If Data Scientists Had Licenses Like Lawyers?
- What is an “algorithm”? It depends whom you ask