Extract numbers from string as numeric or dates in R - r

Question

I am working with some hdf5 data sets. However, the dates are stored in the file and no hint of these dates from the file name. The attribute file consists of day of the year, month of the year, day of the month and year columns.
I would like to pull out data to create time series identity for each of the files i.e.year month date format that can be used for time series.
A sample of the data can be downloaded here:
[ ftp://l5eil01.larc.nasa.gov/tesl1l2l3/TES/TL3COD.003/2007.08.31/TES-Aura_L3-CO_r0000006311_F01_09.he5 ]
There is an attribute group file and a data group file.
I use the R library "rhdf5" to explore the hdf5 files. E.g
CO1<-h5ls ("TES-Aura_L3-CO_r0000006311_F01_09.he5")
Attr<-h5read("TES-Aura_L3-CO_r0000006311_F01_09.he5","HDFEOS INFORMATION/coremetadata")
Data<-h5read("TES-Aura_L3-CO_r0000006311_F01_09.he5", "HDFEOS\SWATHS\ColumnAmountNO2\Data Fields\ColumnAmountNO2Trop")
The Attr when read consist of a long string with the only required information being "2007-08-31" which is the date of acquisition. I have been able to extract this using the Stringr library:
regexp <- "([[:digit:]]{4})([-])([[:digit:]]{2})([-])([[:digit:]]{2})"
Date<-str_extract(Attr,pattern=regexp)
which returns the Date as:
"2007-08-31"
The only problem left now is that the Date isnt recognised as numeric or date. How do I change this as I need to bind the Date with the data for all days to create a time series (more like an identifier as the data sets are irregular), please? a sample of how it looks after extracting the dates from string and binding with the CO values for each date is below
Dates CO3b
[1,] "2011-03-01" 1.625811e+18
[2,] "2011-03-04" 1.655504e+18
[3,] "2011-03-11" 1.690428e+18
[4,] "2011-03-15" 1.679871e+18
[5,] "2011-03-17" 1.705987e+18
[6,] "2011-03-17" 1.661198e+18
[7,] "2011-03-17" 1.662694e+18
[8,] "2011-03-20" 1.520328e+18
[9,] "2011-03-21" 1.510642e+18
[10,] "2011-03-21" 1.556637e+18
However, R recognises these dates as character and not as date. I need to convert them to a time series I can work with.

Answer 1

Seems like you've already done all the hard work! Based off your comment, here's how you could take it across the finish line.
From your comment, seems like you have the strings in a good format. Given that your variable is named date, simply go
dateObjects<-as.Date(Date) #where Date is your variable
and either the single value or vector of character strings (as the format you gave in the comment) will now be date objects, which you could use with a library like zoo to create time series.
If your strings are not necessarily in the format you've described, then refer to the following link to see how to format other string forms as dates.
http://www.statmethods.net/input/dates.html
Given your example data frame you can create a time series in the following way, using the package zoo.
library(zoo)
datavect<-as.zoo(df$CO3b)
index(datavect)<-as.Date(df$Date)
here we take your CO data, covert it to a zoo object, then assign the appropriate date to each entry, converting it from a character to a date object. Now if you print datavect, you'll see each data entry attached to a date. This allows you to take advantage of zoo methods, such as merge and window.

Answer 2

Here is one approach not using string extraction. If you know how long your time series should be, which you should based on the length of your dataset and knowledge of its periodicity, you could just create a regular date series and then add that into a data.frame with other variables of interest. Assuming you have daily data the below would work. Obviously your length.out would be different.
d1 <- ISOdate(year=2007,month=8,day=31)
d2 <- as.Date(format(seq(from=d1,by="day",length.out=10),"%Y-%m-%d"))
[1] "2007-08-31" "2007-09-01" "2007-09-02" "2007-09-03" "2007-09-04" "2007-09-05" "2007-09-06" "2007-09-07" "2007-09-08" "2007-09-09"
class(d2)
[1] "Date"
Edit of Original:
Oh I see. Well after reading in your new data example the below worked for me. It was a pretty straight forward transform. cheers
library(magrittr) # Needed for the pipe operator %>% it makes it really easy to string steps together.
dateData
Dates CO3b
1 2011-03-01 1.63e+18
2 2011-03-04 1.66e+18
3 2011-03-11 1.69e+18
4 2011-03-15 1.68e+18
5 2011-03-17 1.71e+18
6 2011-03-17 1.66e+18
7 2011-03-17 1.66e+18
8 2011-03-20 1.52e+18
9 2011-03-21 1.51e+18
10 2011-03-21 1.56e+18
dateData %>% sapply(class) # classes before transforming (character,numeric)
dateData[,1] <- as.Date(dateData[,1]) # Transform to date
dateData %>% sapply(class) # classes after transforming (Date,numeric)
str(dateData) # one more check
'data.frame': 10 obs. of 2 variables:
$ Dates: Date, format: "2011-03-01" "2011-03-04" "2011-03-11" "2011-03-15" ...
$ CO3b : num 1.63e+18 1.66e+18 1.69e+18 1.68e+18 1.71e+18 ...