Merge has an option 'all', when set to 'TRUE' merge will return a
data.frame of every row in both data.frames. You can also specify all.x,
and all.y.
I do not suggest taking this path. Rather, standardize time columns for
all 15 data.frames with as.POSIXct()/as.POSIXlt() depending on the input
time format.
-Kevin
On 10/18/13 04:37 , "sandeep.samp...@ril.com" <sandeep.samp...@ril.com>
wrote:
Hi,
I'm trying to combine 15 different data frames but all have time field as
common. But the thing is time intervals are different (like min's and
sec's).
So I have to check the common time from all the 15 data frames and merge it
to a single data frame and then export it to excel or csv.
I tried with below query but it's not giving exact output. It's almost 5
year of data, but its giving output for 3months only.
Please help with your query to get my output.
a <- merge(MA2DHPA,MA2DHPB,by="IP_Trend_Time")
b <- merge(MA2UCPA,MA2UCPB,by="IP_Trend_Time")
c <- merge(MA2DCPA,MA2DCPB,by="IP_Trend_Time")
d <- merge(MA2DHTA,MA2DHTB,by="IP_Trend_Time")
e <- merge(MA2UCTA,MA2UCTB,by="IP_Trend_Time")
f <- merge(MA2DCTA,MA2DCTB,by="IP_Trend_Time")
g <- merge(MA2CP,MA2CPS,by="IP_Trend_Time")
h <- MA2AP
x <- merge(a,b,by="IP_Trend_Time")
y <- merge(c,d,by="IP_Trend_Time")
z <- merge(e,f,by="IP_Trend_Time")
w <- merge(g,h,by="IP_Trend_Time")
x1 <- merge(x,y,by="IP_Trend_Time")
y1 <- merge(z,w,by="IP_Trend_Time")
MA2 <- merge(x1,y1,by="IP_Trend_Time")
Regards,
Sandeep S|IT&C,
Reliance Industries Limited (E&P) | Onshore Terminal | Gadimoga
* +91 884 2977066 / 9908130749
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