Plot Dates on the X Axis and Time on the Y Axis with Ggplot2

Plot dates on the x axis and time on the y axis with ggplot2

There are two steps required:

• Extract the time element from the POSIXct object. You can do that with some lubridate extractor functions and a bit of arithmetic, or by subtracting as.Date(dttm) from dttm. I show both ways.
• Add a date-time y-axis and specify a suitable formatter

Two alternative ways to extract the time from a POSIXct object:

dropDate <- function(x){
  3600*hour(x)+60*minute(x)+second(x)
}

dropDate2 <- function(x){
  as.numeric(x - as.Date(x))
}  

You may also wish to specify explicit labels for the axes:

qplot(day(dttm), dropDate(dttm)) + 
    scale_y_datetime(format="%H:%M:%S") + 
    xlab("Day") + ylab("Hour")

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There are more examples of this type of scale in ?scale_datetime, which will point you to ?strptime for an explanation of the date and time formatting codes.

How can I plot date on x-axis and price list on y-axis and attribute by using ggplot?

here are the details to zx8754's answer.
First, note that I put an X infront of the date columns: this is because column-names in R should not start with a number.

df <- data.frame( dress_id = c(1,2,3,4,5),
                  "X29/8/2013" = c(2000,150,6,1000,900),
                  "X31/8/2013" = c(2000,200,7,1100,1000),
                  "X2/9/2013" = c(2400,600,7,1350,1300),
                  "X4/9/2013" = c(2600,600,7,1500,1400),
                  style = c("Sexy", "Casual","vintage","Brief","cute"))

Next, I load the tidyverse package, which contains functions to work with data.frames and also includes ggplot2

library(tidyverse)

Finally, I transform your data from wide to long: this is done with the gather functions. As a result, there is now a date column in your data.frame which contains all the present dates and a value column which contains the sales prices.

df %>%
  gather(date, value, -dress_id, -style) %>%
  mutate(date = as.Date(date, format = c("X%d.%m.%Y"))) %>%
  ggplot(aes(x = date, y = value, colour = style)) + 
  geom_line()

Create a plot with time on the x- and y-axis (in R)

ggplot understands time/date data. Use the Date class, as you've done in the question:

D <- data.frame( time1 = as.Date(c("2007-06-22","2007-05-22","2007-05-23")),
                time2 = as.Date(c("2007-06-22","2007-05-24","2007-06-05")) )

Now you can pass it to ggplot, using scale_x_date and scale_y_date to achieve flexibility in specifying breaks/labels/etc.:

library( ggplot2 )
ggplot( D, aes(x=time1, y=time2) ) + geom_point() +
    scale_x_date( date_labels = "%b %d", date_breaks = "1 week") +
    scale_y_date( date_labels = "%b %d", date_breaks = "1 day" )

See ?scale_x_date for more information.

Customize x-axis labels on ggplot: Only display dates that are on Mondays

You may try

ggplot(df, aes(x=Date, y=Count)) + 
    geom_bar(stat="identity", fill="steelblue") + 
    scale_x_date(date_breaks = "week", date_labels = "%b %d")

Add point to line graph in ggplot when x axis is in Date format

When you have "2012-01-1", R considers this character data. You need to make it a date.

geom_point(aes(x = as.Date("2012-01-01"), y=3000), size = 1, colour = "Red")

Using ggplot scale_x_datetime() to set first date on x axis

library(ggplot2)
dat <- data.frame(date = seq(as.Date("2020-03-05 17:00:00", 
                                     format = "%Y-%m-%d %H:%M:%S"), 
                             as.Date("2022-03-05 17:00:00", 
                                     format = "%Y-%m-%d %H:%M:%S"), 
                             length=18000))
dat$x <- rnorm(18000)
dat$date <- as.POSIXct(dat$date)                  

ggplot(dat, aes(x=date, y=x)) + 
  geom_line() + 
  theme_classic() + 
  scale_x_datetime(breaks= seq(min(dat$date), max(dat$date), length=6), 
                   date_labels="%b-%y")

^{Created on 2022-05-03 by the reprex package (v2.0.1)}

How to make dates in x-axis equidistant in ggplot2 (geom_area) and format date as %d %b %Y

This seems tricky. geom_area does not plot when x is a factor.
However, given you want equidistant dates, we can use rank.

sex <- c('F','F','F',
         'M','M','M')

date <- c("26/11/2018","08/02/2020","08/09/2020", 
          "26/11/2018","08/02/2020","08/09/2020")

percentage <- c(40, 30, 20, 60, 70, 80)          

df <- data.frame(sex, 
             as.Date(date, format = "%d/%m/%Y"),
             percentage)

area1 <- ggplot(df, aes(rank(date), percentage,fill=sex)) + 
  geom_area()+
  scale_y_continuous(breaks = seq(0,100,10))+
  scale_x_continuous(breaks = rank(df$date),
                     labels = format(df$date, "%d/%m/%Y")) +
  scale_fill_brewer(labels=c("Female","Male"),palette ="Paired")

plot(area1)

Only show maximum and minimum dates/values for x and y axis label in ggplot2 plot

You could achieve your desired result by setting the breaks of the scales equal to the range of the variables mapped on x and y:

Notes:

1. If you want to start the y-scale at zero you could do breaks = c(0, max(df$value)).

2. Instead of removing the axis titles via theme you could simply do it via labs.

library(ggplot2)
ggplot(df, aes(
  x = date, y = value, group = type,
  color = type, fill = type
)) +
  geom_area(alpha = 0.4) +
  scale_y_continuous(breaks = range(df$value)) +
  scale_x_date(breaks = range(df$date)) +
  scale_color_manual(
    values = c("1" = "gray", "2" = "red", "3" = "blue"),
    aesthetics = c("color", "fill"), name = "type"
  ) +
  labs(x = NULL, y = NULL)

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