class notes

week 1
• data science & AI
• text: chapter 2
• topic: install, c(), install.packages(), library(), ?, tidyverse, pipe, ggplot()
• notes: introduction · 2.1 - 2.2 · section 3.1 · some basic statistics
• assignment: submission guidelines · [a1 - due 8/29] [a2 - due 9/2] · [a3 - due 9/4]
week 2
• text: chapters 1.4-1.6 and chapter 3
• topic: bar & box plots, histograms, angled axis text, clean_names, scale_x_continuous, seq(), select,rename,
• data: atus
• notes: filtering, boxplots, histograms · choosing visualizations · viz w/ATUS data ·
• assignments: see notes: due 9/4 & 9/9
week 3
• text: chapter 3
• topic: row-ops (filter,arrange,distinct), col-ops (mutate,select,rename,relocate), cut(), write_rds, read_rds, group_by, slice
• notes load/save atus · row & col ops · group_by & cut · table ops · mini project: social science data
• assignments assignment 5: due 9/16 · mini project: due 9/23
• video: (I will start recording my screen during class. This is only a partial recording of Thursday lecture)
week 4
• topic: pivot_longer, lm, ggstats, stat_prop, scale_color_manual
• notes pivoting · titanic-stats · tattoos ·
• video: tuesday · thursday
week 5
• topic: mini-project prez
• notes ggstats · debugging · ai in r ·
• video: thursday
• assignments a6
week 6
• topic: animations & maps
• notes animations · maps ·
• video: video
week 7
• topic: ggplot exensions
• notes list mini-project 2
• video: video
• more notes: zillow 1 · zillow 2 · importing data ·
• video: thursday
week 8
• topic: zillow, scales
• notes: divergent bar ·
• video: thursday