How to plot a line chart in ggplot with a date and time axis?

Question

I have a simple dataset that contains three columns of hourly observations over the course of a few days.

The data looks something like...

Time                    Fast    Standard   Slow
Aug 02 2020 18:00:00    100     200        300
Aug 02 2020 19:00:00    50      100        150
Aug 02 2020 18:00:00    100     200        300
Aug 03 2020 12:00:00    50      100        150
Aug 03 2020 11:00:00    40      50         70

I start by loading up the CSV:

library(tidyverse)

# Link source
if (!exists("gasprices")) { # Check if the object is not already loaded
  if (file.exists("./datafiles/gasprices.rdata")) {
    load("./datafiles/gasprices.rdata") 
  } else {
    gasprices <- read.csv("./datafiles/gasprices.csv")
  }

But when I go to plot one of the lines, I get a blank plot. I think R is showing every row, when what I really need is three overall change-over-time lines for the three variables (fast, standard, slow). My ideal outcome would show three lines of different colors changing over time in the x axis.

# Plot
g <- ggplot(gasprices, aes(x=Time, y=Fast)) +
  geom_line(color = "#00AFBB", size = 2)
  xlab("") +
  theme_light()
g

Any help would be greatly appreciated. Thank you,

Answer 1

It's likely to do with the column data-types. Try running the below for your dataframe, what do you get?

lapply(gasprices, class)

Try setting the datatype to a datetime before plotting:

gasprices$Time<- as.POSIXct(gasprices$Time, format = "%b %e %Y %H:%M:%S")

Have a look at this page for details about the providing the format to be used to parse the datetime.

Let me know how it goes!

Answer 2

What you should do is use the tidyverse package to unpivot your data.

  require(ggplot2)
  require(tidyr)
  require(dplyr)  

Lets create a dataframe with the same structure:

Data <- data.frame ( time = c(1,2,3), fast = c(100, 105, 110), slow = c(50, 70, 90), standart = c(94, 95, 96))

  time fast slow standart
1    1  100   50       94
2    2  105   70       95
3    3  110   90       96

Now we unpivot the data.

Data %>%
  tidyr::gather(key = 'Speed Type', value = 'Speed Value', -time)

 time Speed Type Speed Value
    1       fast         100
    2       fast         105
    3       fast         110
    1       slow          50
    2       slow          70
    3       slow          90
    1   standart          94
    2   standart          95
    3   standart          96

ggplot2::ggplot(data = UnpivotData, mapping = ggplot2::aes(x = time, y = `Speed Value`, color = `Speed Type`)) + 
    ggplot2::geom_line()

Answer 3

You must convert your dates to numeric values before you can plot lines with ggplot() . Perhaps this thread will help you. After doing this, you must provide new axis tick labels to your plot, for example:

plot + scale_x_discrete(labels= df$Time)

Here is a full example with date-to-numeric along with assigning axis tick labels:

library(reshape2)

# Make data frame
Lines <-"Time                    Fast    Standard   Slow
Aug 02 2020 18:00:00    100     200        300
Aug 02 2020 19:00:00    50      100        150
Aug 02 2020 20:00:00    100     200        300
Aug 03 2020 12:00:00    50      100        150
Aug 03 2020 11:00:00    40      50         70"

df <- read.csv(text = gsub("  +", ",", readLines(textConnection(Lines))),
                check.names = FALSE)

# Convert date string to proper format
df$Time <- as.POSIXct(df$Time, format = "%b %d %Y %H:%M:%S")

# Reshape data for easier plotting. This function is from Reshape2.
df <- melt(df, id = "Time")

# Plot
ggplot(data = df, aes(x = as.numeric(Time), y = value, color = variable)) +
  geom_line() +
  scale_x_continuous(breaks = as.numeric(df$Time), labels = as.character(df$Time)) +
  theme(axis.text.x = element_text(angle = 90, vjust = 1, hjust=1))

exampleplot