rudeboybert

#------------------------------------------------------------------------------
# Lec08: 2019/02/25
#------------------------------------------------------------------------------
library(tidyverse)
library(broom)
library(stringr)


#------------------------------------------------------------------------------
# Data for today

rudeboybert

#------------------------------------------------------------------------------
# Lec02: 2019/01/30
#------------------------------------------------------------------------------
library(tidyverse)
library(moderndive)

# 1. Load in training and test data
train <- read_csv("https://rudeboybert.github.io/SDS293/static/train.csv")
test <- read_csv("https://rudeboybert.github.io/SDS293/static/test.csv")

rudeboybert

Keybase proof

I hereby claim:

• I am rudeboybert on github.
• I am rudeboybert (https://keybase.io/rudeboybert) on keybase.
• I have a public key whose fingerprint is 9BC5 364D 4EF2 6E73 F2BF 09A8 00F8 04CC B263 7D03

To claim this, I am signing this object:

rudeboybert

library(tidyverse)
library(infer)

africa_results <-
  "https://rudeboybert.github.io/SDS220/static/PS/africa_results.csv" %>%
  read_csv() %>%
  select(priming_number, how_many_countries)
View(africa_results)

# What actually happened! Observed difference

rudeboybert

#-------------------------------------------------------------------------------
# Setup
#-------------------------------------------------------------------------------
library(tidyverse)

# Population of heights
population_heights <- read_csv("https://goo.gl/3gsSwx")
View(population_heights)

# The population mean mu. What we will pretend we don't know. Equals 164.3cm.

rudeboybert

# Lec 27: Friday 2018/11/9
library(tidyverse)
library(USAboundaries)
library(leaflet)
library(maps)
library(fivethirtyeight)
library(sf)

# Forget Lec26! sf package for maps is better!
USA_sf <- maps::map("state", plot = FALSE, fill = TRUE) %>%

rudeboybert

library(tidyverse)
library(fivethirtyeight)
library(maps)

# View Clinton vs Trump 2016 campaign stops data. Based on
# https://fivethirtyeight.com/features/the-last-10-weeks-of-2016-campaign-stops-in-one-handy-gif/
View(pres_2016_trail)

# Load US state data. See ?map_data() for other options
us_state_map <- map_data("state") %>%

rudeboybert

# R source code for all slides/videos in Albert Y. Kim's "Modeling with Data in
# the Tidyverse" DataCamp course:
# https://www.datacamp.com/courses/modeling-with-data-in-the-tidyverse
# This code is available at http://bit.ly/modeling_tidyverse

# Load all necessary packages -----
library(ggplot2)
library(dplyr)
library(moderndive)

rudeboybert

library(tidyverse)
library(plotly)
library(moderndive)


# Preprocess data ---------------------------------------------------------
set.seed(76)
data(house_prices)

# Re-scale price and size (square footage) by log10 and take a subsample of points

rudeboybert

library(ggplot2)
library(dplyr)
library(gapminder)

# Only for 2007 data
gapminder2007 <- gapminder %>% 
  filter(year == 2007)


# Simple plot -------------------------------------------------------------