Let's consider data:
x <- c(
"1900-01-01", "1900-04-01", "1900-07-01", "1900-10-01", "1901-02-01",
"1901-05-01", "1901-08-01",
"1901-11-01", "1902-02-01", "1902-05-01", "1902-08-01", "1902-11-01", "1903-02-01"
)
x <- as.Date(x)
y <- 1:length(x)
df <- data.frame("Date" = x, "Preds" = y)
I want to make a plot using ggplot but with every date marked (in format %M-%Y):
My work so far:
ggplot(df, aes(x = Date, y = Preds)) +
geom_line() +
scale_x_date(date_breaks = "3 month", date_labels = "%b-%Y")
However this code brings one problem: starting day is in February, whereas our dates starts in Jan.
Do you know how can I back my time by one month ? And Do I have to specify exactly that I want to make a breaks by three months ? Or is there any generic solution that would allow me to just have ticks for every date without this specification ?
We just need to include breaks = x:
ggplot(df, aes(x = Date, y = Preds)) +
geom_line() +
scale_x_date(breaks = x, date_labels = "%b-%Y")
Related
I need to visualize and compare the difference in two equally long sales periods. 2018/2019 and 2019/2020. Both periods begin at week 44 and end at week 36 of the following year. If I create a graph, both periods are continuous and line up. If I use only the week number, the values are sorted as continuum and the graph does not make sense. Can you think of a solution?
Thank You
Data:
set.seed(1)
df1 <- data.frame(sells = runif(44),
week = c(44:52,1:35),
YW = yearweek(seq(as.Date("2018-11-01"), as.Date("2019-08-31"), by = "1 week")),
period = "18/19")
df2 <- data.frame(sells = runif(44),
week = c(44:52,1:35),
YW = yearweek(seq(as.Date("2019-11-01"), as.Date("2020-08-31"), by = "1 week")),
period = "19/20")
# Yearweek on x axis, when both period are separated
ggplot(df1, aes(YW, sells)) +
geom_line(aes(color="Period 18/19")) +
geom_line(data=df2, aes(color="Period 19/20")) +
labs(color="Legend text")
# week on x axis when weeks are like continuum and not splited by year
ggplot(df1, aes(week, sells)) +
geom_line(aes(color="Period 18/19")) +
geom_line(data=df2, aes(color="Period 19/20")) +
labs(color="Legend text")
Another alternative is to facet it. This'll require combining the two sets into one, preserving the data source. (This is commonly a better way of dealing with it in general, anyway.)
(I don't have tstibble, so my YW just has seq(...), no yearweek. It should translate.)
ggplot(dplyr::bind_rows(tibble::lst(df1, df2), .id = "id"), aes(YW, sells)) +
geom_line(aes(color = id)) +
facet_wrap(id ~ ., scales = "free_x", ncol = 1)
In place of dplyr::bind_rows, one might also use data.table::rbindlist(..., idcol="id"), or do.call(rbind, ...), though with the latter you will need to assign id externally.
One more note: the default formatting of the x-axis is obscuring the "year" of the data. If this is relevant/important (and not apparent elsewhere), then use ggplot2's normal mechanism for forcing labels, e.g.,
... +
scale_x_date(labels = function(z) format(z, "%Y-%m"))
While unlikely that you can do this without having tibble::lst available, you can replace that with list(df1=df1, df2=df2) or similar.
If you want to keep the x axis as a numeric scale, you can do:
ggplot(df1, aes((week + 9) %% 52, sells)) +
geom_line(aes(color="Period 18/19")) +
geom_line(data=df2, aes(color="Period 19/20")) +
scale_x_continuous(breaks = 1:52,
labels = function(x) ifelse(x == 9, 52, (x - 9) %% 52),
name = "week") +
labs(color="Legend text")
Try this. You can format your week variable as a factor and keep the desired order. Here the code:
library(ggplot2)
library(tsibble)
#Data
df1$week <- factor(df1$week,levels = unique(df1$week),ordered = T)
df2$week <- factor(df2$week,levels = unique(df2$week),ordered = T)
#Plot
ggplot(df1, aes(week, sells)) +
geom_line(aes(color="Period 18/19",group=1)) +
geom_line(data=df2, aes(color="Period 19/20",group=1)) +
labs(color="Legend text")
Output:
I have measurement data from the past months:
Variables
x <- df$DatoTid
y <- df$Partikler
color <- df$Opgave
I'm trying to plot my data based on the timestamp, so that I have the hours of the day in the x-axis, instead of the specific POSIXct datetime.
I would like the labels and ticks of the x-axis to be fx "00:00", "01:00",..."24:00".
So that noon is in the middle of the x-axis.
So far I tried to convert the datetime values into characters.
Doesn't look good yet (as you can see the axis ticks and labels are gone. Possibly other things are wrong as well).
Can someone help me?
And please let me know how to upload the data for you. I don't know how to add a huge .csv-file....
# Rounding up to nearest 10 min:
head(df)
df$Tid2 <- format(strptime("1970-01-01", "%Y-%m-%d", tz="CET") +
round(as.numeric(df$DatoTid)/300)*300 + 3600, "%Y-%m-%d %H:%M:%S")
head(df)
df$Tid2 <- as.character(df$Tid2)
str(df)
x <- df$Tid2
y <- df$Partikler
color <- df$Opgave
plot2 <- ggplot(data = df, aes(x = x, y = y, color = color)) +
geom_point(shape=16, alpha=0.6, size=1.8) +
scale_y_continuous(labels=function(x) format(x, big.mark = ".", decimal.mark = ",", scientific = FALSE)) +
scale_x_discrete(breaks=c("00:00:00", "06:00:00", "09:00:00", "12:00:00", "18:00:00", "21:00:00")) +
scale_color_discrete(name = "Case") +
xlab(" ") +
ylab(expression(paste("Partikelkoncentration [pt/cc]"))) +
myTheme +
theme(legend.text=element_text(size=8), legend.title=element_text(size=8))
plot2
I would approach this by making a new time stamp that uses a single day, but the hours/minutes/seconds of your existing time stamp.
First, here's a made-up version of your data, here using a linear trend in Partikler:
library(tidyverse); library(lubridate)
df <- data_frame(Tid2 = seq.POSIXt(from = ymd_h(2019010100),
to = ymd_h(2019011500), by = 60*60),
Partikler = seq(from = 0, to = 2.5E5, along.with = Tid2),
Opgave = as.factor(floor_date(Tid2, "3 days")))
# Here's a plot that's structurally similar to yours:
ggplot(df, aes(Tid2, Partikler, col = Opgave)) +
geom_point() +
scale_color_discrete(name = "Case")
Now, if we change the timestamps to be in the same day, we can control them like usual in ggplot, but with them collapsed into a single day of timing. We can also change the x axis so it doesn't mention the date component of the time stamp:
df2 <- df %>%
mutate(Tid2_sameday = ymd_hms(paste(Sys.Date(),
hour(Tid2), minute(Tid2), second(Tid2))))
ggplot(df2, aes(Tid2_sameday, Partikler, col = Opgave)) +
geom_point() +
scale_color_discrete(name = "Case") +
scale_x_datetime(date_labels = "%H:%M")
I want to display difftime data with ggplot2 and I want the tick format to be hh:mm.
library(ggplot2)
a= as.difftime(c("0:01", "4:00"), "%H:%M", unit="mins")
b= as.difftime(c('0:01', "2:47"), "%H:%M", unit="mins")
ggplot(data=NULL, aes(x=b, y=a)) + geom_point(shape=1) +
scale_x_time(labels = date_format("%H:%M"),
breaks = "1 hour")
But I get the following warning:
Don't know how to automatically pick scale for object of type difftime. Defaulting to continuous.
Warning message:
In structure(as.numeric(x), names = names(x)) : NAs introduced by coercion
and this as a graph:
Update:
my example was too minimal, I also need to be able to display negative differences, so this would be better data:
a= as.difftime(c(-60, -4*60), unit="mins")
b= as.difftime(c(-60, 2*60+47), unit="mins")
ggplot(data=NULL, aes(x=b, y=a)) + geom_point(shape=1)
The answer has two parts.
Plotting difftime objects
According to help("scale_x_time"), ggplot2 supports three date/time classes: scale_*_date for dates (class Date), scale_*_datetime for datetimes (class POSIXct), and scale_*_time for times (class hms). The last one is what we need here.
Class hms is a custom class for difftime vectors. as.hms() has a method for difftime. So. difftime objects can be plotted with ggplot2 by coercing to class hms:
a <- as.difftime(c(-60, -4 * 60), unit = "mins")
b <- as.difftime(c(-60, 2 * 60 + 47), unit = "mins")
library(ggplot2)
ggplot(data = NULL, aes(x = hms::as.hms(b), y = hms::as.hms(a))) +
geom_point(shape = 1)
Please, note that negative time differences are shown as well.
Formatting the tick labels
The OP has requested that tick marks should be labeled in hh:mm format. Apparently, the default formatting is hh:mm:ss. This can be modified by specifying a function that takes the breaks as input and returns labels as output to the labels parameter of the scale_x_time() and scale_y_time() functions:
format_hm <- function(sec) stringr::str_sub(format(sec), end = -4L)
ggplot(data = NULL, aes(x = hms::as.hms(b), y = hms::as.hms(a))) +
geom_point(shape = 1) +
scale_x_time(name = "b", labels = format_hm) +
scale_y_time(name = "a", labels = format_hm)
The format_hm() function truncates the :ss part from the default format. In addition, the axis are labeled nicely.
Depending on your constraints, you might consider translating the difftimes to distinct datetimes, which ggplot can handle just fine:
library(lubridate)
a_date_times <- floor_date(Sys.time(), "1 day") + a
b_date_times <- floor_date(Sys.time(), "1 day") + b
ggplot(data=NULL, aes(x=a_date_times, y=b_date_times)) +
geom_point(shape=1)
My best approach so far is:
library(ggplot2)
library(lubridate)
a= as.difftime(c(-60, -4*60), unit="mins")
b= as.difftime(c(-60, 2*60+47), unit="mins")
xbreaks = seq(ceiling(min(b)/60), floor(max(b)/60)) * 60
ybreaks = seq(ceiling(min(a)/60), floor(max(a)/60)) * 60
ggplot(data=NULL, aes(x=b, y=a)) + geom_point(shape=1) +
scale_x_continuous(labels = f, breaks = xbreaks) +
scale_y_continuous(labels = f, breaks = ybreaks)
f <- function(x){
t = seconds_to_period(abs(x)*60)
r = sprintf("% 2i:%02i", sign(x)*hour(t), minute(t))
return(r)
}
I want the x-axis in the following graph to start at 06:00 and end at 22:00, with breaks at every 4 hours. I can't figure out the following, however.
a) How to make the x-axis start at 06:00 without any empty space before 06:00.
b) How to make the x-axis end at 22:00 without any empty space after 22:00. Right now it doesn't even show 22:00
c) How to have breaks at every 4 hours.
d) How to assign a label to the y-axis (currently it's simply X4, the column name).
I've tried several things, but without success. Some example data:
range <- seq(as.POSIXct("2015/4/18 06:00"),as.POSIXct("2015/4/18 22:00"),"mins")
df <- data.frame(matrix(nrow=length(range),ncol=4))
df[,1] <- c(1:length(range))
df[,2] <- 2*c(1:length(range))
df[,3] <- 3*c(1:length(range))
df[,4] <- range
Reshape:
library(reshape2)
df2 <- melt(df,id="X4")
Graph:
library(ggplot2)
ggplot(data=df2,aes(x=X4,y=value,color=variable)) + geom_line()+
scale_y_continuous(expand=c(0,0)) +
coord_cartesian(xlim=c(as.POSIXct("2015/4/18 06:00:00"),as.POSIXct("2015/4/18 22:00:00")))
Which makes the graph look like this:
Any ideas?
Here is some code that should help you. This can easily be done using scale_x_datetime.
## desired start and end points
st <- as.POSIXct("2015/4/18 06:00:00")
nd <- as.POSIXct("2015/4/18 22:00:00")
## display data for given time range
ggplot(data = df2, aes(x = X4, y = value, color = variable)) +
geom_line() +
scale_y_continuous("Some name", expand = c(0, 0)) +
scale_x_datetime("Some name", expand = c(0, 0), limits = c(st, nd),
breaks = seq(st, nd, "4 hours"),
labels = strftime(seq(st, nd, "4 hours"), "%H:%S"))
I want to set bounds for the x-axis for a plot of time-series data which features only time (no dates). My limits are:
lims <- strptime(c("03:00","16:00"), format = "%H:%M")
And my ggplot prints fine, but when I add this to scale_x_datetime
scale_x_datetime(limits = lims)
I get Error: Invalid input: time_trans works with objects of class POSIXct only
Fully reproducible example courtesy of How to create a time scatterplot with R?
dates <- as.POSIXct(as.Date("2011/01/01") + sample(0:365, 100, replace=TRUE))
times <- as.POSIXct(runif(100, 0, 24*60*60), origin="2011/01/01")
df <- data.frame(
dates = dates,
times = times
)
lims <- strptime(c("04:00","16:00"), format = "%H:%M")
library(scales)
library(ggplot2)
ggplot(df, aes(x=dates, y=times)) +
geom_point() +
scale_y_datetime(limits = lims, breaks=date_breaks("4 hour"), labels=date_format("%H:%M")) +
theme(axis.text.x=element_text(angle=90))
the error message says that you should use as.POSIXct on lims.
You also need to add the date (year, month and day) in lims, because by default it will be `2015, which is off limits.
lims <- as.POSIXct(strptime(c("2011-01-01 03:00","2011-01-01 16:00"), format = "%Y-%m-%d %H:%M"))
ggplot(df, aes(x=dates, y=times)) +
geom_point() +
scale_y_datetime(limits =lims, breaks=date_breaks("4 hour"), labels=date_format("%H:%M"))+
theme(axis.text.x=element_text(angle=90))