R: plotting data.frame against time with "hardcoded" date column - r

Question

I have googled a lot and yet I still cant figure this one out. I am trying to plot one column in a dataframe against time, however my date column is "hardcoded" (for the lack of a better word) as index in the dataframe not a DATE column, as a variable, by itself.
> head(tmp)[1]
this is what I get, the 1st column is Returns:
RETURNS
2010-01-13 00:00:00 0.8291384
2010-01-14 00:00:00 0.2423567
2010-01-15 00:00:00 -1.0882186
2010-01-19 00:00:00 1.2422194
2010-01-20 00:00:00 -1.0654438
2010-01-21 00:00:00 -1.9126605
If I plot it like:
plot(tmp$RETURNS)
I get a plot of returns against index from 1 to 1500 (number of obs.) and not time. If I got a distinct time column I would plot it like this and it would be fine:
plot(tmp$DATE, tmp$RETURNS)
However, I dont know how to extract the date from that "hardcoded" date column, if that makes sense. I tried to convert it to other objects, timeSeries, zoo etc. Didnt help.I am sure there is some kind of simple function, I just cant find it. Thanks for any help guys.
EDIT:
Thanks guys, your help is very much appreciated. All answers are great, too bad that I cant accept them all ;) Of course it was rownames what I was looking for.

Answer 1

Reproducing your data (you should really have used dput to make life easier for us):
df <- as.data.frame(c(0.8291384, 0.2423567,-1.0882186, 1.2422194,-1.0654438,-1.9126605))
names(df) <- c("RETURNS")
rownames(df) <- c("2010-01-13 00:00:00", "2010-01-14 00:00:00", "2010-01-15 00:00:00", "2010-01-19 00:00:00","2010-01-20 00:00:00","2010-01-21 00:00:00")
df
RETURNS
2010-01-13 00:00:00 0.8291384
2010-01-14 00:00:00 0.2423567
2010-01-15 00:00:00 -1.0882186
2010-01-19 00:00:00 1.2422194
2010-01-20 00:00:00 -1.0654438
2010-01-21 00:00:00 -1.9126605
Cleaning up:
df$Date <- as.Date(rownames(df))
rownames(df) <- NULL
df
RETURNS Date
1 0.8291384 2010-01-13
2 0.2423567 2010-01-14
3 -1.0882186 2010-01-15
4 1.2422194 2010-01-19
5 -1.0654438 2010-01-20
6 -1.9126605 2010-01-21
Plotting:
plot(df$Date, df$RETURNS)
or
library(ggplot2)
ggplot(df, aes(x=Date, y=RETURNS)) + geom_point() + scale_x_date()

Answer 2

Assuming that the input is as in the Note below then using zoo we can plot using classic graphics, ggplot2 and lattice as follows. We also show a base R solution at the end and a variation. Note that since the time is always 0 we used "Date" class for the time index in all cases.
library(zoo)
z <- zoo(df$RETURNS, as.Date(rownames(df)))
plot(z)
library(ggplot2)
autoplot(z)
library(lattice)
xyplot(z)
# this one does not use any packages
df2 <- data.frame(time = as.Date(rownames(df)), RETURNS = df$RETURNS)
plot(RETURNS ~ time, df2)
# this also works using df2 just calculated
plot(df2)
Note: We assume the input is:
df <- data.frame(
RETURNS = c(0.8291384, 0.2423567,-1.0882186, 1.2422194,-1.0654438,-1.9126605),
row.names = c("2010-01-13 00:00:00", "2010-01-14 00:00:00", "2010-01-15 00:00:00",
"2010-01-19 00:00:00","2010-01-20 00:00:00","2010-01-21 00:00:00"))