ggplot2 to plot time series by date using seperate date and variable dateframes r

Question

I'm trying to plot a time series. In one dataframe(y), I have 56 items in a column vector and I have a second dataframe (dates) with corresponding dates. I am trying to graph the time series as the values of y on the y-axis and the dates on the x axis. I have tried a number of things using ggplt2 geom_freqpoly but I can't figure it out. I'm open to other methods besides ggplot and i can cbind date and y into one dateframe as well if it will make things easier.

Any advice?

library(ggplot2)

set.seed(123)

N<- 500
M<-56

x<- matrix( rnorm(N*M,mean=23,sd=3), N, M)
y <- colMeans(x,dim=1)

y <-as.data.frame(y)

Date <- seq(as.Date("2018-01-01"), as.Date("2018-02-25"), by="days")
Date <- as.POSIXct(Date, format = "%Y-%m-%d %H:%M")

a <- ggplot(date, aes(y))
a + geom_freqpoly()

www www · Accepted Answer · 2018-02-25T05:31:59

Here are methods from several different packages.

ggplot2

The ggplot2 package works the best on a data frame, so I would suggest you to create a data frame with your data. In addition, not sure why do you want to use geom_freqpoly. I think geom_line will work for time-series data.

library(ggplot2)

set.seed(123)

N<- 500
M<-56

x<- matrix( rnorm(N*M,mean=23,sd=3), N, M)
y <- colMeans(x,dim=1)

Date <- seq(as.Date("2018-01-01"), as.Date("2018-02-25"), by="days")
Date <- as.POSIXct(Date, format = "%Y-%m-%d %H:%M")

dat <- data.frame(Date = Date, y = y)

ggplot(dat, aes(x = Date, y = y)) +
  geom_line() +
  theme_classic()

ggpubr

ggpubr is an extension of the ggplot2 package. We can use ggline package to plot the data.

library(ggpubr)    
ggline(data = dat, x = "Date", y = "y")

lattice

We can also use the xyplot function from the lattice package.

library(lattice)

xyplot(y ~ Date, data = dat, type = "l")

ggvis

The ggvis package, similar to ggplot, uses grammar of graphics to create plots.

library(ggvis)

ggvis(dat, ~Date, ~y) %>% layer_lines()

Base R

We can also use the base R.

plot(dat$Date, dat$y, xaxt = "n", type = "l", xlab = "Date", ylab = "y")
axis.POSIXct(1, at = seq(min(dat$Date), max(dat$Date), by = "week"), format="%b %d")

xts

We can also convert the data frame to an xts object and then plot it.

library(xts)

dat.ts <- xts(dat$y, order.by = dat$Date)
plot(dat.ts)

PerformanceAnalytics

We can also use the chart.TimeSeries from the performanceanalytics package to plot the xts package.

chart.TimeSeries(dat.ts)

dygraphs

The dygraphs package can create interactive time-series plot.

library(dygraphs)

dygraph(dat.ts)

plotly

We can also use plotly to create interactive plot.

library(plotly)

plot_ly(x = ~dat$Date, y = ~dat$y, mode = 'lines')

We can also use highcharter package to create interactive plot.

library(highcharter)

hchart(dat.ts)

ggplot2 to plot time series by date using seperate date and variable dateframes r

1 Answers