rer145

library(dplyr)
library(stringr)

deaths<-read.csv("z_KoreanConflict.csv", header=TRUE, stringsAsFactors=FALSE)

rer145

library(dplyr)
library(ggplot2)
library(stringr)
library(lubridate)

# First grab the data and filter out the bad data in INCIDENT_DATE (see https://gist.github.com/rer145/68b75131d7e2d89adc53b1f8d75ab294)
deaths<-read.csv("KoreanConflict.csv", header=TRUE, stringsAsFactors=FALSE)

regEx = "^\\d{8}$"

rer145

library(dplyr)
library(stringr)

deaths<-read.csv("z_KoreanConflict.csv", header=TRUE, stringsAsFactors=FALSE)

# We want to make sure all data in INCIDENT_DATE is correct
# A quick investigation shows the data in a YYYYMMDD format, but some fields are empty
# A simple regular expression can just check for 8 digits
regEx = "^\\d{8}$"

rer145

library(Lahman)
library(dplyr)
library(ggplot2)
library(ggiraph)

# Get all teams from 1980 and the number of home runs hit
df<-Teams %>%
  filter(yearID == 1980) %>%
  select(name, HR) %>%
  arrange(HR)

rer145

library(dplyr)
library(Lahman)
library(ggplot2)

# Get all the teams from 1980 and how many home runs they hit
df<-Teams %>%
  filter(yearID==1980) %>%
  select(name, HR) %>%
  arrange(HR)

rer145

library(dplyr)
library(tidytext)
library(janeaustenr)

# Using dplyr and janeaustenr, get the contents of 'Sense & Sensibility'
sns<-austen_books()
sns<-sns%>%
  filter(book=='Sense & Sensibility')

head(sns)

rer145

library(dplyr)
library(tidytext)
library(janeaustenr)

# Using dplyr and janeaustenr, get the contents of 'Sense & Sensibility'
sns<-austen_books()
sns<-sns%>%
  filter(book=='Sense & Sensibility')

head(sns)

rer145

library(gutenbergr)
library(stringr)

# search for the EXACT name of the novel title
gutenberg_works(title=='Dracula')

# search for the EXACT author's name (Last Name, First Name)
gutenberg_works(author=='Stoker, Bram')

# search for the word 'Frankenstein' in the title column