.Rhistory

bookdown:::serve_book()
bookdown:::serve_book()
library(knitr)
library(tidyverse)
library(fivethirtyeight)
library(rmarkdown)
library(knitr)
library(tidyverse)
library(fivethirtyeight)
library(rmarkdown)
knitr::include_graphics("images/03-01-newproject.png")
knitr::include_graphics("images/03-02-newproject.png")
bookdown:::serve_book()
if <- 3+2
install.packages("bookdown"
)
bookdown:::serve_book()
install.packages(
"fivethirtyeight"
)
bookdown:::serve_book()
fivethirtyeight::tv_hurricanes_by_network
data(tv_hurricanes_by_network)
data("tv_hurricanes_by_network")
View(tv_hurricanes_by_network)
View(tv_hurricanes)
tripdata_201906 <- read_csv(unzip("https://s3.amazonaws.com/niceride-data/201906-niceride-tripdata.csv.zip"))
tripdata_201906 <- unzip("https://s3.amazonaws.com/niceride-data/201906-niceride-tripdata.csv.zip")
download.file("https://s3.amazonaws.com/niceride-data/201906-niceride-tripdata.csv.zip",temp, mode="wb")
temp <- tempfile()
download.file("https://s3.amazonaws.com/niceride-data/201906-niceride-tripdata.csv.zip",temp, mode="wb")
unzip(temp, "tripdata_201906.csv")
unzip(temp, "201906-niceride-tripdata.csv.zip")
unzip(temp, "201906-niceride-tripdata.csv")
unzip(temp, "2001906-niceride-tripdata.csv")
dd <- read_csv("2001906-niceride-tripdata.csv")
View(dd)
temp <- tempfile()
download.file("https://s3.amazonaws.com/niceride-data/Nice_ride_data_2017_season.zip",temp, mode="wb")
unzip(temp, "Nice_ride_trip_history_2017_season.csv")
Nice_ride_trip_history_2017_season <- read_csv("Nice_ride_trip_history_2017_season.csv")
download.file("https://s3.amazonaws.com/niceride-data/Nice_ride_data_2017_season.zip",temp, mode="wb")
unzip(temp, "Nice_ride_trip_history_2017_season.csv")
temp
unzip(temp, "Nice_ride_data_2017_season.csv")
unzip(temp, "Nice_ride_data_2017_season.zip")
temp <- tempfile()
temp <- tempfile()
download.file("https://s3.amazonaws.com/niceride-data/Nice_ride_data_2017_season.zip",temp, mode="wb")
temp
unzip(temp, "Nice_ride_trip_history_2017_season.csv")
niceride_2017 <- read_csv("data_large/Nice_ride_trip_history_2017_season.csv")
View(niceride_2017)
bookdown:::serve_book()
library(metcouncilR)
data("nice_ride_2018") # niceride dataset
table(nice_ride_2018$usertype)
View(nice_ride_2018)
help("nice_ride_2018")
hist(nice_ride_2018$tripduration)
barplot(table(nice_ride_2018$usertype))
barplot(table(nice_ride_2018$usertype), main = "User Type")
barplot(table(nice_ride_2018$bike_type), main = "Bike Type")
ggplot(nice_ride_2018) # set up our plotting area and axes
ggplot(nice_ride_2018, aes(x = usertype)) # set up our plotting area
ggplot(nice_ride_2018, aes(x = usertype)) +
geom_bar() # add the geoms
ggplot(nice_ride_2018, aes(x = usertype)) +
geom_bar() +
labs(title = "User Types") # add a title
knitr::include_graphics("images/rstudiocloud.png")
bookdown::render_book("index.Rmd", "bookdown::pdf_book")
bookdown::render_book("index.Rmd", "bookdown::epub_book")
bookdown::render_book("index.Rmd", "bookdown::pdf_book")
library(tinytex)
bookdown::render_book("index.Rmd", "bookdown::pdf_book")
tinytex::install_tinytex()
bookdown::render_book("index.Rmd", "bookdown::pdf_book")
bookdown::render_book("index.Rmd", "bookdown::pdf_book")
bookdown::render_book("index.Rmd", "bookdown::pdf_book")
bookdown:::serve_book()
ggplot(nice_ride_2018) # set up our plotting area
ggplot(nice_ride_2018, aes(x = tripduration)) # set up our axes
ggplot(nice_ride_2018, aes(x = tripduration)) +
geom_histogram() # add the geoms
60 * 5
ggplot(nice_ride_2018, aes(x = tripduration)) +
geom_histogram(binwidth = 300) # add the geoms
summary(nice_ride_2018$tripduration)
summary(nice_ride_2018$tripduration)
11136253/60
185604.2 / 60
3093.403 /24
11720 /60
13435/60
70247 /60
1170.783 /60
5 * 24
5 * 24 * 60 * 60
67785 / 60
67785 / 60 / 60
5 * 60 * 60
nice_ride_2018 <- filter(nice_ride_2018, tripduration <= 18000)
data("nice_ride_2018")
nice_ride_2018_2 <- filter(nice_ride_2018, tripduration <= 18000)
ggplot(nice_ride_2018_2, aes(x = tripduration)) +
geom_histogram() # add the geoms
ggplot(nice_ride_2018, aes(x = usertype)) +
geom_bar() +
labs(title = "User Types", x = "User Type", y = "Trips") # add a title
ggplot(nice_ride_2018_2, aes(x = tripduration)) +
geom_histogram() + # add the geoms
labs(title = "Durations of trips under 5 hours (in seconds)", x = "Duration (seconds)", y = "Trips")
data("nice_ride_2018")
View(nice_ride_2018)
library(metcouncilR)
data("nice_ride_2018") # niceride dataset
help("nice_ride_2018")
hist(nice_ride_2018$start_month)
ggplot(nice_ride_2018, aes(x = start_month)) # set up our axes
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram() # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bindwith = 1) # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bindwith = 2) # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram() # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bins = 24) # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bins = 20) # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bins = 12) # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bins = 0) # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bins = 5) # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bins = 7) # add the geoms
ggplot(nice_ride_2018, aes(x = start_month)) +
geom_histogram(bins = 8) # add the geoms
hist(nice_ride_2018$start_hour)
hist(nice_ride_2018$tripduration)
data("nice_ride_2018") # niceride dataset
help("nice_ride_2018")
library(metcouncilR)
data("nice_ride_2018") # niceride dataset
help("nice_ride_2018")
install_github("katiejolly/metcouncilR")
install_github("katiejolly/metcouncilR", force = TRUE)
library(metcouncilR)
data("nice_ride_2018") # niceride dataset
hist(nice_ride_2018$tripduration)
ggplot(nice_ride_2018, aes(x = tripduration)) # set up our axes
ggplot(nice_ride_2018, aes(x = tripduration)) +
geom_histogram() # add the geoms and the total number of geoms that you want
ggplot(nice_ride_2018, aes(x = tripduration)) +
geom_histogram() + # add the geoms
labs(title = "Durations of trips under 5 hours (in seconds)", x = "Duration (seconds)", y = "Trips")
ggplot(nice_ride_2018, aes(x = birth_year)) +
geom_bar() +
labs(title = "Reported birth year of riders", x = "Year", y = "Trips") # add a title
sum(nice_ride_2018$birth_year == 60)
sum(nice_ride_2018$birth_year == 1970)
sum(nice_ride_2018$birth_year == 1971)
sum(nice_ride_2018$birth_year == 1972)
sum(nice_ride_2018$birth_year == 1970)
sum(nice_ride_2018$birth_year == 1969)
sum(nice_ride_2018$birth_year == 1968)
sum(nice_ride_2018$birth_year == 1969)
ggplot(nice_ride_2018, aes(x = start_day)) + geom_bar(fill = "cyan4")
ggplot(nice_ride_2018, aes(x = start_day)) +
geom_bar(fill = "cyan4") +
theme_minimal() +
labs("What days did people use niceride in 2018?", x = "Day of the week", y = "Trips", caption = "Source: Niceride MN")
ggplot(nice_ride_2018, aes(x = start_day)) +
geom_bar(fill = "cyan4") +
theme_minimal() +
labs("What days did people use niceride in 2018?", x = "Day of the week", y = "Trips", caption = "Source: Niceride MN")
ggplot(nice_ride_2018, aes(x = start_day)) +
geom_bar(fill = "cyan4") +
theme_minimal() +
labs(title = "What days did people use niceride in 2018?", x = "Day of the week", y = "Trips", caption = "Source: Niceride MN")
ggplot(nice_ride_2018, aes(x = start_day)) +
geom_bar(fill = "cyan4") +
theme_minimal() +
labs(title = "What days did people use niceride in 2018? Weekends are a favorite.", x = "Day of the week", y = "Trips", caption = "Source: Niceride MN")
bookdown:::serve_book()
saturday_trips <- filter(nice_ride_2018, start_day == "Sat")
dim(saturday_trips) # check that you have these dimensions
after_12 <- filter(nice_ride_2018, end_hour > 12)
dim(after_12)
saturday_after_12 <- filter(nice_ride_2018, end_hour > 12 & start_day == "Sat")
weekend_trips <- filter(nice_ride_2018, start_day == "Sat" | start_day == "Sun")
weekendFri_trips <- filter(nice_ride_2018, start_day %in% c("Sat", "Sun", "Fri"))
weekendFri_trips <- filter(nice_ride_2018, start_day == "Sat" | start_day == "Sun" | start_day == "Fri")
weekendFri_trips <- filter(nice_ride_2018, start_day == "Sat" | start_day == "Sun" | start_day == "Fri")
dim(weekendFri_trips)
weekendFri_trips <- filter(nice_ride_2018, start_day %in% c("Sat", "Sun", "Fri"))
dim(weekendFri_trips)
print(vec)
vec <- c("Katie", "Dunn", "Jolly") # a vector of the 3 parts of my name
print(vec)
vec + 1
vec <- c(1, 4, 9, 25) # a vector of squares
vec + 1
sqrt(vec)
vec <- c(1, 4, 9, 16) # a vector of squares
vec + 1
sqrt(vec)
library(tidyverse)
library(sf)
library(leaflet)
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun")) %>%
group_by(start_station_name) %>%
count() %>%
top_n(n, 10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col()
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun")) %>%
group_by(start_station_name) %>%
count() %>%
top_n(10, n) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col()
top_n
?top_n
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun")) %>%
group_by(start_station_name) %>%
count()
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun")) %>%
group_by(start_station_name) %>%
count() %>%
top_n(10, n)
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun")) %>%
group_by(start_station_name) %>%
count() %>%
top_n(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col()
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun")) %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col()
filter(nice_ride_2018, start_station_name == "NULL")
nulls <- filter(nice_ride_2018, start_station_name == "NULL")
View(nulls)
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun") & biketbike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col()
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col()
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col() +
theme(axis.text = element_text(angle = 80))
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col() +
theme(axis.text = element_text(angle = 60, vjust = 1))
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col() +
theme(axis.text = element_text(angle = 60, hjust = 1))
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_histogram()
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_histogram(binwidth = 1)
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_histogram(binwidth = 1) +
facet_wrap(~start_day)
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_histogram(binwidth = 1, color = "white") +
facet_wrap(~start_day)
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_histogram(binwidth = 1, color = "white") +
facet_wrap(~start_day) + # lay out the plots by the weekday
theme_minimal()
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_density(binwidth = 1, color = "white") +
facet_wrap(~start_day) + # lay out the plots by the weekday
theme_minimal()
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_density() +
facet_wrap(~start_day) + # lay out the plots by the weekday
theme_minimal()
?geom_density
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_density(adjust = 2) +
facet_wrap(~start_day) + # lay out the plots by the weekday
theme_minimal()
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_density(adjust = 1.5) +
facet_wrap(~start_day) + # lay out the plots by the weekday
theme_minimal()
ggplot(nice_ride_2018, aes(x = start_hour)) +
geom_density(adjust = 1.5) + # the adjust argument just makes the plots a little smoother
facet_wrap(~start_day) + # lay out the plots by the weekday
theme_minimal()
bookdown:::serve_book()
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col() +
theme(axis.text = element_text(angle = 60, hjust = 1)) +
theme_minimal()
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
theme_minimal()
nice_ride_2018 %>%
filter(start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col() +
theme_minimal() +
theme(axis.text = element_text(angle = 60, hjust = 1))
nice_ride_2018 %>%
filter(!start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(start_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col() +
theme_minimal() +
theme(axis.text = element_text(angle = 60, hjust = 1))
nice_ride_2018 %>%
filter(!start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(end_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = start_station_name, y = n)) +
geom_col() +
theme_minimal() +
theme(axis.text = element_text(angle = 60, hjust = 1))
nice_ride_2018 %>%
filter(!start_day %in% c("Sat", "Sun") & bike_type == "Classic") %>%
group_by(end_station_name) %>%
count() %>%
arrange(desc(n)) %>%
head(10) %>%
ggplot(aes(x = end_station_name, y = n)) +
geom_col() +
theme_minimal() +
theme(axis.text = element_text(angle = 60, hjust = 1))