This code produces a single boxplot:
df <- data.frame(value = rnorm(62), my.date = seq(as.Date("2013-12-01"), as.Date("2014-01-31"), by="1 day"))
library(ggplot2)
ggplot(df, aes(as.Date(my.date), value)) + geom_boxplot() + scale_x_date(minor_breaks = "1 week", labels = date_format("%W\n%b"))
How can I produce a plot that has single boxplots for each week between 1 December and 31 January? So within the single plot, there should be about 8 boxplots. Would prefer solution that uses either ggplot() or scale_x_date().
One option is to transform your date before using ggplot
library(ggplot2)
df <- data.frame(value = rnorm(62),
my.date = seq(as.Date("2013-12-01"), as.Date("2014-01-31"), by="1 day"))
weeks <- format(df$my.date, "%Y/%W")
weeks <- factor(weeks, levels = unique(weeks))
ggplot(df, aes(weeks, value)) +
geom_boxplot()
library(ggplot2)
ggplot(df, aes(format(as.Date(my.date), "%W\n%b"), value)) + geom_boxplot()
Edit:
To order the dates:
ggplot(df, aes(reorder(format(as.Date(my.date), "%W\n%b"),
as.Date(my.date)),
value)) +
geom_boxplot()
This fulfils #luciano's request to retain functionality of scale_x_date
library('scales')
library(ggplot2)
df <- data.frame(value = rnorm(62), my.date = seq(as.Date("2013-12-01"), as.Date("2014-01-31"), by="1 day"))
ggplot(df, aes(x=as.Date(my.date), y=value, group=format(as.Date(my.date),"%W-%b"))) + geom_boxplot() + scale_x_date(date_breaks = "1 week", date_labels="%Y-%b-%d")
Alternatively, if you don't want the data grouped by week# - which gives you the split around most new years - you can group by week ending Sundays as below. Adjusting from the Sunday weekending, to say Friday, can be achieved with some such code
ceiling_date(x, "week") + ifelse(weekdays(x) %in% c("Saturday", "Sunday"), 5, -2)
ggplot(df, aes(x=as.Date(my.date), y=value, group=ceiling_date(my.date, "week"))) + geom_boxplot() + scale_x_date(date_breaks = "1 week", date_labels="%Y-%b-%d")
Related
Below I create a reproducible example chart ranging for 10000 days. As you can see this chart is highly informative and value adding, but it will do for the example.
Instead of one x label every 10 years, I would like to force a label every year. How can this be achieved?
library(ggplot2)
library(tidyr)
exdays <- 1:10000
exdata <- sin(exdays)
exdate <- as_date("2022-01-01")+days(exdays)
exdat <- tibble(exdate, exdata)
p1 <- ggplot(exdat, aes(x=exdate, y=exdata)) +
geom_line(color="darkred", size=0.7) +
ggtitle("example")
p1
You maybe want this using scale_x_date with date_breaks of 1 year where you specify the date_labels:
library(ggplot2)
library(tidyr)
exdays <- 1:10000
exdata <- sin(exdays)
exdate <- as_date("2022-01-01")+days(exdays)
exdat <- tibble(exdate, exdata)
p1 <- ggplot(exdat, aes(x=exdate, y=exdata)) +
geom_line(color="darkred", size=0.7) +
scale_x_date(date_breaks = "1 year", date_labels = "%Y") +
ggtitle("example")
p1
Output:
This works
p1 <- ggplot(exdat, aes(x=exdate, y=exdata)) +
geom_line(color="darkred", size=0.7) +
ggtitle("example") + scale_x_date(date_breaks = "1 year")
How do I plot each year as a separate line in ggplot2 I tried the below code but it seems to plot continuous as a single plot.
library(ggplot2)
# Dummy data
data <- data.frame(
Date = c(as.Date("2017-01-14") - 0:13,as.Date("2016-01-14") - 0:13),
value = runif(28)
)
#data$Date <- strptime(data$Date, "%Y-%m-%d" )
data$Year <- as.character(year(data$Date))
data$Year <- factor(data$Year)
ggplot(data) + geom_line(aes(x = Date, y = value, group=Year, color=Year)) +
scale_x_date(date_breaks = "1 day", date_labels = "%d-%m-%y") +
theme(axis.text.x = element_text(angle = 90))
But I want each year to be a separate graph in the same plot.
something like below
Try this approach formating day and month in your date. You got a mess in your plot because of the different year in your date variable. Setting format can help you. Here the code:
library(ggplot2)
library(lubridate)
# Dummy data
data <- data.frame(
Date = c(as.Date("2017-01-14") - 0:13,as.Date("2016-01-14") - 0:13),
value = runif(28)
)
data$Year <- as.character(year(data$Date))
data$Year <- factor(data$Year)
#Format month
data$MonthDay <- format(data$Date,'%b-%d')
#Plot
ggplot(data) + geom_line(aes(x = MonthDay, y = value, group=Year, color=Year)) +
theme_bw()+
theme(axis.text.x = element_text(angle = 90))
Output:
Currently using ggplot2 and scales doing this but would be ideal to show a date range +/- 1 Year (for example). I shouldn't really be hardcoding these dates as it's not very efficient.
library(scales) #date time scales
library(ggplot2) # Visualization
ggplot(dataset,aes(x=datetime_start, y=dataset$Product, color=Stage, order = - as.numeric(Stage))) +
geom_segment(aes(x=From,xend=To,yend=dataset$Product), size=10) +
scale_x_datetime(
breaks = date_breaks("1 month"),
labels=date_format("%b%y"),
limits = c(
as.POSIXct("2016-03-01"),
as.POSIXct("2018-02-01")
)
) +
Expand the scale:
library(ggplot2)
df <- data.frame(x = seq(Sys.Date()-lubridate::years(2), Sys.Date(), by="3 month"))
df$y <- 1:nrow(df)
p <- ggplot(df, aes(x, y)) + geom_line()
p + scale_x_date(expand = c(0, 365))
This code produces a single boxplot:
df <- data.frame(value = rnorm(62), my.date = seq(as.Date("2013-12-01"), as.Date("2014-01-31"), by="1 day"))
library(ggplot2)
ggplot(df, aes(as.Date(my.date), value)) + geom_boxplot() + scale_x_date(minor_breaks = "1 week", labels = date_format("%W\n%b"))
How can I produce a plot that has single boxplots for each week between 1 December and 31 January? So within the single plot, there should be about 8 boxplots. Would prefer solution that uses either ggplot() or scale_x_date().
One option is to transform your date before using ggplot
library(ggplot2)
df <- data.frame(value = rnorm(62),
my.date = seq(as.Date("2013-12-01"), as.Date("2014-01-31"), by="1 day"))
weeks <- format(df$my.date, "%Y/%W")
weeks <- factor(weeks, levels = unique(weeks))
ggplot(df, aes(weeks, value)) +
geom_boxplot()
library(ggplot2)
ggplot(df, aes(format(as.Date(my.date), "%W\n%b"), value)) + geom_boxplot()
Edit:
To order the dates:
ggplot(df, aes(reorder(format(as.Date(my.date), "%W\n%b"),
as.Date(my.date)),
value)) +
geom_boxplot()
This fulfils #luciano's request to retain functionality of scale_x_date
library('scales')
library(ggplot2)
df <- data.frame(value = rnorm(62), my.date = seq(as.Date("2013-12-01"), as.Date("2014-01-31"), by="1 day"))
ggplot(df, aes(x=as.Date(my.date), y=value, group=format(as.Date(my.date),"%W-%b"))) + geom_boxplot() + scale_x_date(date_breaks = "1 week", date_labels="%Y-%b-%d")
Alternatively, if you don't want the data grouped by week# - which gives you the split around most new years - you can group by week ending Sundays as below. Adjusting from the Sunday weekending, to say Friday, can be achieved with some such code
ceiling_date(x, "week") + ifelse(weekdays(x) %in% c("Saturday", "Sunday"), 5, -2)
ggplot(df, aes(x=as.Date(my.date), y=value, group=ceiling_date(my.date, "week"))) + geom_boxplot() + scale_x_date(date_breaks = "1 week", date_labels="%Y-%b-%d")
Suppose I have a plot like this:
DF <- data.frame(date=Sys.Date() - (-100):100, y=rnorm(201))
library("ggplot2")
library(scales)
ggplot(DF, aes(x=date, y=y)) +
geom_point() +
scale_x_date(breaks = "1 month", minor_breaks = "1 week", labels=date_format("%b"))
Here I want to include major lines and labels at every month and minor lines at every week. This works well, but now I would like to include the year behind the abbreviated month, but only for the first month of that year in the plot. Thus, the labels should read sep 2014. okt, nov, dec, jan 2015, feb, mrt....
Is this possible?
You can do it with a custom date formatter to remove duplicated years:
my_date_format <- function()
{
function(x)
{
m <- format(x,"%b")
y <- format(x,"%Y")
ifelse(duplicated(y),m,paste(m,y))
}
}
ggplot(DF, aes(x=date, y=y)) +
geom_point() +
scale_x_date(breaks = "1 month", minor_breaks = "1 week", labels=my_date_format())