#dput
df <- structure(list(V1 = structure(c(2L, 2L, 1L, 3L, 1L, 4L, 5L, 4L), .Label = c("2013-01-02", "2013-01-03", "2013-01-04", "2013-01-05", "2013-01-11"), class = "factor"), V2 = structure(c(1L, 3L, 8L, 4L, 7L, 6L, 5L, 2L), .Label = c(" 04:04:23", " 06:28:43", " 10:02:04", " 11:35:16", " 14:29:18", " 17:31:30", " 23:31:56", " 23:45:16"), class = "factor")), .Names = c("V1", "V2"), class = "data.frame", row.names = c(NA, -8L))
Using ggplot
since it gives fine-grained control over your plot. Use different layers for the measurements and the density itself.
df$tcol<- as.POSIXct(paste(df$dte, df$timestmp), format= "%Y-%m-%d %H:%M:%S")
library(ggplot2)
measurements <- geom_point(aes(x=tcol, y=0), shape=15, color='blue', size=5)
kde <- geom_density(aes(x=tcol), bw="nrd0")
ggplot(df) + measurements + kde
Leads to
Now, if you want to further adjust the x-axis labels (since you want each separate day marked, you can use the scales
package.
We are going to use scale_x_date
but that only takes in 'Date'
library(scales)
df$tcol <- as.Date(df$tcol, format= "%Y-%m-%d %H:%M:%S")
xlabel <- scale_x_date(labels=date_format("%m-%d"), breaks="1 day")
ggplot(df) + xlabel + measurements + kde
This gives:
Please note that the hours seem to have gotten rounded.
Hopefully this helps you move forward.