rudeboybert

library(fivethirtyeight)
library(tidyverse)

# I still can't use forcats package from scratch
levels <- c("nowomen-disagree", "notalk-disagree", "men-disagree",
            "dubious-disagree", "ok-disagree")

bechdel %>% 
  filter(str_detect(test, "disagree")) %>% 
  select(test, binary) %>% 

rudeboybert

# This is the source code of Albert Y. Kim (rudeboybert)'s "Introduction to 
# Splines" video. 

# Lines 4-86 were run before the video and hidden from the viewer in order to
# simplify the content of the video.
library(tidyverse)
library(broom)

# Set options, random number generator seed value, & ggplot geom() + theme()
# arguments

rudeboybert

library(lubridate)
library(dplyr)
library(mosaic)
set.seed(41)

students <- c(
  "Annie", "Caroline", "David", "Ian", "Jack", "Jared", "Joccelyn", "Joe", 
  "Julia", "Luisangel", "Madeline", "Rebecca", "Samuel", "Sarah", "Sierra", 
  "Sophia", "Stefan", "Steven", "Theodore", "Tina", "Wengel", "William", "Zach"
)

rudeboybert

library(USAboundaries)
library(rgeos)
library(maptools)
library(RColorBrewer)

# Get polygon data
counties_shp <- us_counties()
counties_polygon <- tidy(counties_shp, region="geoid")
counties_data <- counties_shp@data
counties <- left_join(counties_polygon, counties_data, by=c("id"="geoid"))

rudeboybert

# Same plot as https://rudeboybert.github.io/MATH116/assets/figure/blue_vs_red.jpg
# But with y-axis starting at 0
library(dplyr)
library(ggplot2)

voter_turnout <- data_frame(
  # Make year a categorical variable:
  Year = as.factor(c(2008, 2008, 2012, 2012, 2016, 2016)),
  Party = c("Democrat", "Republican", "Democrat", "Republican", "Democrat", "Republican"),
  Votes = c(69.5, 60, 66, 61, 59, 59)

rudeboybert

# Probability Clinton Wins -- bookie odds 11.07.16
# Code by Jay Emerson for scraping data off web page, and displaying

z <- scan('https://electionbettingodds.com', what="", sep="\n")
z <- z[grep("in last day", z)]
z <- gsub("<[^<>]*>", ",", z)
z <- gsub("^.*',(.*):.*,Clinton ([0-9.]*)%.*$", "\\1,\\2", z)[-1]
writeLines(z, "betfair.csv")
z <- read.csv("betfair.csv", as.is=TRUE, header=FALSE)
names(z) <- c("state", "pclinton")

rudeboybert

library(dplyr)
library(ggplot2)
library(rgdal)
library(leaflet)

# Set your working directory to where the folder that contains your shapefiles is at:
VT <- rgdal::readOGR("VT_shapefiles/tl_2015_50_tract.shp", layer = "tl_2015_50_tract")

# The variable in ALAND exists here, i.e. you don't need to join anything
VT@data

rudeboybert

# Load packages, including mosaic package
library(dplyr)
library(ggplot2)
library(mosaic)

# Flip a coin once. Try this multiple times:
rflip()

# Flip a coin 10 times. Try this multiple times:
rflip(10)

rudeboybert

# Which states changed colors here:
# http://fivethirtyeight.com/features/election-update-women-are-defeating-donald-trump/

library(ggplot2)
library(maps)
library(mapproj)
library(dplyr)

# Load map of us data
all_states <- map_data("state")