时间戳正在破坏我在 ggplot2 中的图形，我该如何解决这个问题？

Question

I have a data set called X1234 and I have three columns (num, timestamp, Levels of concentration), here is a sample of what my data looks like:

num | timestamp      | Levels of Concentration
1   | 4/2/2019 10:45 | 60.80
2   | 4/2/2019 11:00 | 60.08
3   | 4/2/2019 11:15 | 60.08
4   | 4/2/2019 11:30 | 60.26
5   | 4/2/2019 11:45 | 60.26
6   | 4/2/2019 12:00 | 60.44
7   | 4/2/2019 12:15 | 60.44
8   | 4/2/2019 12:30 | 60.44
9   | 4/2/2019 12:45 | 60:62
10  | 4/2/2019 13:00 | 60.62

When I use ggplot to plot a graph of the area (the x-axis = num , y-axis = Levels of Concentration ) I get a good graph, however, I want to do this with a timestamp . Here is the picture of what I would like my graph to look like and the code I used for it was :

ggplot(X1234, aes(x = X1234$num, y=X1234$`Levels of Concentration`)) + geom_area()

Ideal Graph

However I need to use the timestamp as the x-axis, but when I do so my graph changes completely and I don't understand why. Here is the code I used for the second graph (x = timestamp , y = Levels of Concentration )

X1234$timestamp_local <- as.Date (X1234$timestamp_local, '%m/%d ')
ggplot(data = X1234, aes (x= X1234$timestamp_local, y = X1234$`Levels of Concentration`)) +  geom_area()

My actual graph using the timestamp

Answer 1

The problem is that num is a number which is plotted an a continuous scale, while timestamp is of type character which results in a discrete scale.

For plotting timestamp on a continuous scale it needs to be coerced to the datetime class POSIXct properly, eg, by using lubridate::mdy_hm() :

library(ggplot2)
library(lubridate)
ggplot(X1234) +
  aes(x = mdy_hm(timestamp), y = `Levels of Concentration`) +
  geom_area()

Data

X1234 <- readr::read_delim("
num | timestamp      | Levels of Concentration
1   | 4/2/2019 10:45 | 60.80
2   | 4/2/2019 11:00 | 60.08
3   | 4/2/2019 11:15 | 60.08
4   | 4/2/2019 11:30 | 60.26
5   | 4/2/2019 11:45 | 60.26
6   | 4/2/2019 12:00 | 60.44
7   | 4/2/2019 12:15 | 60.44
8   | 4/2/2019 12:30 | 60.44
9   | 4/2/2019 12:45 | 60.62
10  | 4/2/2019 13:00 | 60.62", delim = "|", trim_ws = TRUE)