50 个州随时间变化的箱线图
Boxplot for 50 States over time
根据答案编辑
我有 50 个州随时间变化的结婚率数据。我正在尝试为每个州制作单独的箱形图，并且还能够将这些图放在 R 中的州地图上。如果这不可能，由于拥堵，我很想知道如何只放置最小值或地图上每个州的最大值。
Link to Data if interested
我在 R 中以两种方式列出了我的数据，我认为第一种方式在图形方面会更好。
marriage<-read.csv(file="~/Desktop/masters.csv", header=T, sep=",",check.names=FALSE)
marriagefine <-
marriage %>%
pivot_longer(
cols = `2017`:`1990`,
names_to = 'year',
values_to = 'rate'
) %>%
mutate(
year = as.numeric(year)
)
这让 R 阅读我的 table 这样的东西；
> marriagefine
# A tibble: 1,071 x 3
State year rate
<fct> <dbl> <dbl>
1 Alabama 2017 7
2 Alabama 2016 7.1
3 Alabama 2015 7.4
4 Alabama 2014 7.8
5 Alabama 2013 7.8
6 Alabama 2012 8.2
7 Alabama 2011 8.4
8 Alabama 2010 8.2
9 Alabama 2009 8.3
10 Alabama 2008 8.6
# … with 1,061 more rows
另一种阅读方式
State 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1995 1990
1 Alabama 7.0 7.1 7.4 7.8 7.8 8.2 8.4 8.2 8.3 8.6 8.9 9.2 9.2 9.4 9.6 9.9 9.4 10.1 10.8 9.8 10.6
2 Alaska 6.9 7.1 7.4 7.5 7.3 7.2 7.8 8.0 7.8 8.4 8.5 8.2 8.2 8.5 8.1 8.3 8.1 8.9 8.6 9.0 10.2
3 Arizona 5.8 5.9 5.9 5.8 5.4 5.6 5.7 5.9 5.6 6.0 6.4 6.5 6.6 6.7 6.5 6.7 7.6 7.5 8.2 8.8 10.0
4 Arkansas 9.5 9.9 10.0 10.1 9.8 10.9 10.4 10.8 10.7 10.6 12.0 12.4 12.9 13.4 13.4 14.3 14.3 15.4 14.8 14.4 15.3
5 California 6.3 6.5 6.2 6.4 6.5 6.0 5.8 5.8 5.8 6.7 6.2 6.3 6.4 6.4 6.1 6.2 6.5 5.8 6.4 6.3 7.9
6 Colorado 7.3 7.4 6.8 7.1 6.5 6.8 7.0 6.9 6.9 7.4 7.1 7.2 7.6 7.4 7.8 8 8.2 8.3 8.2 9.0 9.8
7 Connecticut 5.6 5.6 5.3 5.4 5 5.2 5.5 5.6 5.9 5.4 5.5 5.5 5.8 5.8 5.5 5.7 5.4 5.7 5.8 6.6 7.9
8 Delaware 5.5 5.6 5.7 6 6.6 5.8 5.2 5.2 5.4 5.5 5.7 5.9 5.9 6.1 6 6.4 6.5 6.5 6.7 7.3 8.4
9 District of Columbia 8.2 8.1 8.2 11.8 10.8 8.4 8.7 7.6 4.7 4.1 4.2 4 4.1 5.2 5.1 5.1 6.2 4.9 6.6 6.1 8.2
10 Florida 7.8 8.1 8.2 7.3 7 7.2 7.4 7.3 7.5 8.0 8.5 8.6 8.9 9.0 9 9.4 9.3 8.9 8.7 9.9 10.9
11 Georgia 6.9 6.8 6.2 --- --- 6.5 6.6 7.3 6.6 6.0 6.8 7.3 7.0 7.9 7 6.5 6.1 6.8 7.8 8.4 10.3
12 Hawaii 15.3 15.6 15.9 17.7 16.3 17.5 17.6 17.6 17.2 19.1 20.8 21.9 22.6 22.6 22 20.8 19.6 20.6 18.9 15.7 16.4
13 Idaho 7.8 8.1 8.2 8.4 8.2 8.2 8.6 8.8 8.9 9.5 10.0 10.1 10.5 10.8 10.9 11 11.2 10.8 12.1 13.1 13.9
我的箱形图命令基于下面列出的答案
boxplot(rate ~ State, data = marriagefine,
main="Box Plot for Marriage Rates by State",
xlab="States", ylab="Rates",
col=rainbow(length(unique(marriagefine$State))))
我如何将每个箱形图和/或每个图的 minimum/maximum 值叠加到美国地图上？我知道这是基本的大纲。
library(usmap)
plot_usmap(regions = c("states", "state", "counties", "county"),
include = c(), exclude = c(), data = data.frame(),
values = "values", labels = FALSE,
label_color = "black")
错误应该很简单，因为您的全局环境中没有这样的对象。具体来说，没有分配 State 作为一个独立的对象，其中包含一个名为 rate 的元素，以便能够调用 State$rate。相反，您在名为 State 和 rate 的数据框中有两个字段，您可以分别调用：marriagefine$State 和 marriagefine$rate.
但是，boxplot 支持根据 data 参数中传递的项目数据框运行的公式样式。 （以下仅使用 post 正文中的 posted 数据）
# BY YEAR
boxplot(rate ~ year, data = marriagefine,
main="Stats for Marriage Rates, 1990-2017",
xlab="States", ylab="Rates",
col=rainbow(length(2017:1990)))
# BY STATE
boxplot(rate ~ State, data = marriagefine,
main="Stats for Marriage Rates, 1990-2017",
xlab="States", ylab="Rates",
col=rainbow(length(unique(marriagefine$State))))
这需要一个闪亮的解决方案：
lapply(c("shiny", "data.table", "ggplot2", "RColorBrewer", "ggrepel"),
require, character.only = TRUE)
# mangle data
marriage <- fread("masters.csv", header = TRUE)
marriage <- melt(marriage, id.vars = "State")
marriage$variable <- as.numeric(as.character(marriage$variable ))
setnames(marriage, c("State", "year", "rate"))
marriage$State <- tolower(marriage$State)
states_map <- map_data("state")
marriage <- merge(data.table(data.frame(state.center),
state.abb, State=tolower(state.name)), marriage, by="State")
# pick fixed color palette
myPalette <- colorRampPalette(rev(brewer.pal(11, "Spectral")))
sc <- scale_fill_gradientn(colours = myPalette(100),
limits = range(marriage$rate))
# Define UI
ui <- fluidPage(
titlePanel("Marriage"),
sidebarLayout(
sidebarPanel(
sliderInput("year", "Year", min(marriage$year),
max(marriage$year), value=min(marriage$year), step = 1)
),
mainPanel(
plotOutput(outputId = "box", height = "800px")
)
)
)
# Define server function
server <- function(input, output) {
output$box <- renderPlot({
req(input$year)
DT <- marriage[year==input$year]
ggplot(DT, aes(map_id = State)) +
geom_map(aes(fill = rate), map = states_map) +
expand_limits(x = states_map$long, y = states_map$lat) +
sc +
geom_text_repel(data=DT, aes(x=x, y=y, label = rate), size=10)
})
}
# Create Shiny object
shinyApp(ui = ui, server = server)
回复请求：静态版本有两个图，每个状态的最大值和最小值彼此相邻：
# Load packages
lapply(c("data.table", "ggplot2", "RColorBrewer", "ggrepel", "cowplot"),
require, character.only = TRUE)
# mangle data
marriage <- fread("masters.csv", header = TRUE)
marriage <- melt(marriage, id.vars = "State")
marriage$variable <- as.numeric(as.character(marriage$variable ))
setnames(marriage, c("State", "year", "rate"))
marriage$State <- tolower(marriage$State)
states_map <- map_data("state")
marriage <- merge(data.table(data.frame(state.center),
state.abb, State=tolower(state.name)), marriage, by = "State")
# pick fixed color palette
myPalette <- colorRampPalette(rev(brewer.pal(11, "Spectral")))
sc <- scale_fill_gradientn(colours = myPalette(100),
limits = range(marriage$rate))
# sort by State and rate
setkeyv(marriage, c("State", "rate"))
# pick year with largest and smallest rate (could be one of several)
DT.max <- marriage[, tail(.SD, 1), by = State]
DT.min <- marriage[, head(.SD, 1), by = State]
theme_set(theme_void())
# generate plot of maximum and minimum rates by State
p1 <- ggplot(DT.max, aes(map_id = State)) +
geom_map(aes(fill = rate), map = states_map) +
expand_limits(x = states_map$long, y = states_map$lat) +
sc +
geom_text_repel(data=DT.max, aes(x=x, y=y,
label = paste0(rate, "\n(",year,")")), size=3.5) +
ggtitle("Maximum marriage rate 1990-2017 \nby State (year measured)") +
theme(plot.title = element_text(hjust = 0.5))
p2 <- ggplot(DT.min, aes(map_id = State)) +
geom_map(aes(fill = rate), map = states_map) +
expand_limits(x = states_map$long, y = states_map$lat) +
sc +
geom_text_repel(data=DT.min, aes(x=x, y=y,
label = paste0(rate, "\n(",year,")")), size=3.5) +
ggtitle("Minimum marriage rate 1990-2017 \nby State (year measured)") +
theme(plot.title = element_text(hjust = 0.5))
# plot plots next to each other
cowplot::plot_grid(p1, p2, ncol=2)
根据答案编辑
我有 50 个州随时间变化的结婚率数据。我正在尝试为每个州制作单独的箱形图，并且还能够将这些图放在 R 中的州地图上。如果这不可能，由于拥堵，我很想知道如何只放置最小值或地图上每个州的最大值。 Link to Data if interested
我在 R 中以两种方式列出了我的数据，我认为第一种方式在图形方面会更好。
marriage<-read.csv(file="~/Desktop/masters.csv", header=T, sep=",",check.names=FALSE)
marriagefine <-
marriage %>%
pivot_longer(
cols = `2017`:`1990`,
names_to = 'year',
values_to = 'rate'
) %>%
mutate(
year = as.numeric(year)
)
这让 R 阅读我的 table 这样的东西；
> marriagefine
# A tibble: 1,071 x 3
State year rate
<fct> <dbl> <dbl>
1 Alabama 2017 7
2 Alabama 2016 7.1
3 Alabama 2015 7.4
4 Alabama 2014 7.8
5 Alabama 2013 7.8
6 Alabama 2012 8.2
7 Alabama 2011 8.4
8 Alabama 2010 8.2
9 Alabama 2009 8.3
10 Alabama 2008 8.6
# … with 1,061 more rows
另一种阅读方式
State 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1995 1990
1 Alabama 7.0 7.1 7.4 7.8 7.8 8.2 8.4 8.2 8.3 8.6 8.9 9.2 9.2 9.4 9.6 9.9 9.4 10.1 10.8 9.8 10.6
2 Alaska 6.9 7.1 7.4 7.5 7.3 7.2 7.8 8.0 7.8 8.4 8.5 8.2 8.2 8.5 8.1 8.3 8.1 8.9 8.6 9.0 10.2
3 Arizona 5.8 5.9 5.9 5.8 5.4 5.6 5.7 5.9 5.6 6.0 6.4 6.5 6.6 6.7 6.5 6.7 7.6 7.5 8.2 8.8 10.0
4 Arkansas 9.5 9.9 10.0 10.1 9.8 10.9 10.4 10.8 10.7 10.6 12.0 12.4 12.9 13.4 13.4 14.3 14.3 15.4 14.8 14.4 15.3
5 California 6.3 6.5 6.2 6.4 6.5 6.0 5.8 5.8 5.8 6.7 6.2 6.3 6.4 6.4 6.1 6.2 6.5 5.8 6.4 6.3 7.9
6 Colorado 7.3 7.4 6.8 7.1 6.5 6.8 7.0 6.9 6.9 7.4 7.1 7.2 7.6 7.4 7.8 8 8.2 8.3 8.2 9.0 9.8
7 Connecticut 5.6 5.6 5.3 5.4 5 5.2 5.5 5.6 5.9 5.4 5.5 5.5 5.8 5.8 5.5 5.7 5.4 5.7 5.8 6.6 7.9
8 Delaware 5.5 5.6 5.7 6 6.6 5.8 5.2 5.2 5.4 5.5 5.7 5.9 5.9 6.1 6 6.4 6.5 6.5 6.7 7.3 8.4
9 District of Columbia 8.2 8.1 8.2 11.8 10.8 8.4 8.7 7.6 4.7 4.1 4.2 4 4.1 5.2 5.1 5.1 6.2 4.9 6.6 6.1 8.2
10 Florida 7.8 8.1 8.2 7.3 7 7.2 7.4 7.3 7.5 8.0 8.5 8.6 8.9 9.0 9 9.4 9.3 8.9 8.7 9.9 10.9
11 Georgia 6.9 6.8 6.2 --- --- 6.5 6.6 7.3 6.6 6.0 6.8 7.3 7.0 7.9 7 6.5 6.1 6.8 7.8 8.4 10.3
12 Hawaii 15.3 15.6 15.9 17.7 16.3 17.5 17.6 17.6 17.2 19.1 20.8 21.9 22.6 22.6 22 20.8 19.6 20.6 18.9 15.7 16.4
13 Idaho 7.8 8.1 8.2 8.4 8.2 8.2 8.6 8.8 8.9 9.5 10.0 10.1 10.5 10.8 10.9 11 11.2 10.8 12.1 13.1 13.9
我的箱形图命令基于下面列出的答案
boxplot(rate ~ State, data = marriagefine,
main="Box Plot for Marriage Rates by State",
xlab="States", ylab="Rates",
col=rainbow(length(unique(marriagefine$State))))
我如何将每个箱形图和/或每个图的 minimum/maximum 值叠加到美国地图上？我知道这是基本的大纲。
library(usmap)
plot_usmap(regions = c("states", "state", "counties", "county"),
include = c(), exclude = c(), data = data.frame(),
values = "values", labels = FALSE,
label_color = "black")
错误应该很简单，因为您的全局环境中没有这样的对象。具体来说，没有分配 State 作为一个独立的对象，其中包含一个名为 rate 的元素，以便能够调用 State$rate。相反，您在名为 State 和 rate 的数据框中有两个字段，您可以分别调用：marriagefine$State 和 marriagefine$rate.
但是，boxplot 支持根据 data 参数中传递的项目数据框运行的公式样式。 （以下仅使用 post 正文中的 posted 数据）
# BY YEAR
boxplot(rate ~ year, data = marriagefine,
main="Stats for Marriage Rates, 1990-2017",
xlab="States", ylab="Rates",
col=rainbow(length(2017:1990)))
# BY STATE
boxplot(rate ~ State, data = marriagefine,
main="Stats for Marriage Rates, 1990-2017",
xlab="States", ylab="Rates",
col=rainbow(length(unique(marriagefine$State))))
这需要一个闪亮的解决方案：
lapply(c("shiny", "data.table", "ggplot2", "RColorBrewer", "ggrepel"),
require, character.only = TRUE)
# mangle data
marriage <- fread("masters.csv", header = TRUE)
marriage <- melt(marriage, id.vars = "State")
marriage$variable <- as.numeric(as.character(marriage$variable ))
setnames(marriage, c("State", "year", "rate"))
marriage$State <- tolower(marriage$State)
states_map <- map_data("state")
marriage <- merge(data.table(data.frame(state.center),
state.abb, State=tolower(state.name)), marriage, by="State")
# pick fixed color palette
myPalette <- colorRampPalette(rev(brewer.pal(11, "Spectral")))
sc <- scale_fill_gradientn(colours = myPalette(100),
limits = range(marriage$rate))
# Define UI
ui <- fluidPage(
titlePanel("Marriage"),
sidebarLayout(
sidebarPanel(
sliderInput("year", "Year", min(marriage$year),
max(marriage$year), value=min(marriage$year), step = 1)
),
mainPanel(
plotOutput(outputId = "box", height = "800px")
)
)
)
# Define server function
server <- function(input, output) {
output$box <- renderPlot({
req(input$year)
DT <- marriage[year==input$year]
ggplot(DT, aes(map_id = State)) +
geom_map(aes(fill = rate), map = states_map) +
expand_limits(x = states_map$long, y = states_map$lat) +
sc +
geom_text_repel(data=DT, aes(x=x, y=y, label = rate), size=10)
})
}
# Create Shiny object
shinyApp(ui = ui, server = server)
回复请求：静态版本有两个图，每个状态的最大值和最小值彼此相邻：
# Load packages
lapply(c("data.table", "ggplot2", "RColorBrewer", "ggrepel", "cowplot"),
require, character.only = TRUE)
# mangle data
marriage <- fread("masters.csv", header = TRUE)
marriage <- melt(marriage, id.vars = "State")
marriage$variable <- as.numeric(as.character(marriage$variable ))
setnames(marriage, c("State", "year", "rate"))
marriage$State <- tolower(marriage$State)
states_map <- map_data("state")
marriage <- merge(data.table(data.frame(state.center),
state.abb, State=tolower(state.name)), marriage, by = "State")
# pick fixed color palette
myPalette <- colorRampPalette(rev(brewer.pal(11, "Spectral")))
sc <- scale_fill_gradientn(colours = myPalette(100),
limits = range(marriage$rate))
# sort by State and rate
setkeyv(marriage, c("State", "rate"))
# pick year with largest and smallest rate (could be one of several)
DT.max <- marriage[, tail(.SD, 1), by = State]
DT.min <- marriage[, head(.SD, 1), by = State]
theme_set(theme_void())
# generate plot of maximum and minimum rates by State
p1 <- ggplot(DT.max, aes(map_id = State)) +
geom_map(aes(fill = rate), map = states_map) +
expand_limits(x = states_map$long, y = states_map$lat) +
sc +
geom_text_repel(data=DT.max, aes(x=x, y=y,
label = paste0(rate, "\n(",year,")")), size=3.5) +
ggtitle("Maximum marriage rate 1990-2017 \nby State (year measured)") +
theme(plot.title = element_text(hjust = 0.5))
p2 <- ggplot(DT.min, aes(map_id = State)) +
geom_map(aes(fill = rate), map = states_map) +
expand_limits(x = states_map$long, y = states_map$lat) +
sc +
geom_text_repel(data=DT.min, aes(x=x, y=y,
label = paste0(rate, "\n(",year,")")), size=3.5) +
ggtitle("Minimum marriage rate 1990-2017 \nby State (year measured)") +
theme(plot.title = element_text(hjust = 0.5))
# plot plots next to each other
cowplot::plot_grid(p1, p2, ncol=2)