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Hi All, Newbie question for you all but i have been looking at the archieves and the help dtuff to get a rough idea of what i want to do I would like to merge two dataframes together based on a keyed variable in one dataframe linking to the other dataframe. Only some of the cases will match but i would like to keep the others as well. My dataframes have 67 and 28 cases respectively and i would

Hi I have recently been analyzing birthweight data from a clinic. The data has obvious defects in that there is digit preference on certain weights making them overrepresented. This shows as spikes in the histogram on certain well rounded weights like 2, 2.5, 3, etc. I would like to show this to government officials but can't figure out how I should present the finding in an easy to

I want to take the first row of each unique ID value from a data frame. For instance > ddTable <- data.frame(Id=c(1,1,2,2),name=c("Paul","Joe","Bob","Larry")) I want a dataset that is Id Name 1 Paul 2 Bob > unique(ddTable) Will give me all 4 rows, and > unique(ddTable$Id) Will give me c(1,2), but not accompanied by the name column.

Greetings to all. I need to concatenate data frames that do not have all the same variable names, there is only a partial overlap in the variables. So, for example, if i have two data frames, a and b, that look like the following: > a a b 1 1 4 2 2 5 3 3 6 4 4 7 5 5 8 > b c a 1 1 10 2 2 11 3 3 12 4 4 13 5 5 14 i want to concatenate them by row, without any matching, so that the

This is an OpenPGP/MIME signed message (RFC 2440 and 3156) --------------enig5A700CC15DEABD01445A1B70 Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable Hi, I have modified the code originally posted to include capability for arbitrary weightings for the rows and columns (which apply in the nominal-ordinal and the ordinal-ordinal cases). The code is pasted

Hi everyone! I have a question about data processing efficiency. My data are as follows: I have a data set on quarterly institutional ownership of equities; some of them have had recent IPOs, some have not (I have a binary flag set). The total dataset size is 700k+ rows. My goal is this: For every quarter since issue for each IPO, I need to find a "matched" firm in the same