[R] remove rows with infinite/nan values from a zoo dataset

[arun]

Hi,

No problem.

In my previous post, I showed how to dput() your example dataset.  Please use dput() in the future.
vec1<- c(3.369247e-04,0.000000e+00,9.022183e-04,0.000000e+00,-1.105819e-04,-Inf,1.191271e-04,1.681718e-04,NaN,1.150126e-04,1.031037e-03,2.710993e-04)

indx<-seq(as.Date("2009-09-01"),as.Date("2009-09-17"),by=1)
indx1<-indx[-c(5:7,12:13)]
library(zoo)
z1<- zoo(vec1,order.by=indx1)
 sum(z1,na.rm=TRUE) #without removing the Inf. 
#[1] -Inf


sum(z1[is.finite(z1)],na.rm=TRUE)
#[1] 0.002833009


#or just
sum(z1[is.finite(z1)])
#[1] 0.002833009
A.K.





Thank you for your reply A.K. 

Sorry for my misleading -- the first question should be removing
 #N/A N/A values when reading a csv file. So the example provided in the
 original post was dragged from a csv spreadsheet directly. 
(which I used the code "prices=read.zoo("C:\\Users\\Desktop\\\\awc_au.csv",header=TRUE,sep=",",format="%Y-%m-%d" ") 

Then the following up question is removing from a zoo data set. 
After some calculation, the new zoo data set is as following: 
 2009-09-01         2009-09-02       2009-09-03     2009-09-04     2009-09-08    2009-09-09 
 3.369247e-04  0.000000e+00  9.022183e-04  0.000000e+00 -1.105819e-04          -Inf 
   2009-09-10       2009-09-11      2009-09-14    2009-09-15      2009-09-16     2009-09-17 
 1.191271e-04  1.681718e-04        NaN             1.150126e-04  1.031037e-03  2.710993e-04 

I need to sum them up so I used "sum(Z, na.rm=TRUE)" to remove the NaN values but not for the Inf/-Inf. 

Hope it is clear to you. 

Cheers, 
R.L 
----- Original Message -----
From: arun <smartpink111 at yahoo.com>
To: R help <r-help at r-project.org>
Cc: 
Sent: Tuesday, September 3, 2013 2:47 AM
Subject: Re: remove rows with infinite/nan values from a zoo dataset

Hi,
Please dput() the example dataset.  When I read from the one shown below, it looks a bit altered.

library(zoo)
dat1<- read.zoo(text="2009-07-15,#N/A N/A,#N/A N/A,18.96858
2009-07-16,20.30685,20.40664,#N/A N/A
2009-07-17,20.78813,20.03991,20.40664
2009-07-20,21.41278,21.41278,20.03991
2009-07-21,22.9963,22.98397,21.41278
2009-07-22,23.06443,23.01112,22.98397
2009-07-23,23.45905,24.72232,23.01112
2009-07-24,24.89291,25.56603,24.72232
2009-07-27,25.38929,24.80535,25.56603
2009-07-28,25.26712,25.65566,24.80535
2009-07-29,25.83884,24.98163,25.65566
2009-07-30,#N/A N/A,#N/A N/A,24.98163
2009-08-03,25.25553,25.93297,#N/A N/A
2009-08-04,26.02464,25.49159,25.93297
",sep=",",header=FALSE,FUN=as.Date,format="%Y-%m-%d",fill=TRUE) 


dput(dat1)  ###
structure(c(NA, 20.30685, 20.78813, 21.41278, 22.9963, 23.06443, 
23.45905, 24.89291, 25.38929, 25.26712, 25.83884, NA, 25.25553, 
26.02464, NA, 20.40664, 20.03991, 21.41278, 22.98397, 23.01112, 
24.72232, 25.56603, 24.80535, 25.65566, 24.98163, NA, 25.93297, 
25.49159, NA, NA, 20.40664, 20.03991, 21.41278, 22.98397, 23.01112, 
24.72232, 25.56603, 24.80535, 25.65566, NA, NA, 25.93297), .Dim = c(14L, 
3L), .Dimnames = list(NULL, c("V2", "V3", "V4")), index = structure(c(14440, 
14441, 14442, 14445, 14446, 14447, 14448, 14449, 14452, 14453, 
14454, 14455, 14459, 14460), class = "Date"), class = "zoo")


dat2<- dat1[!rowSums(is.na(dat1)),]
dat2
#                 V2       V3       V4
#2009-07-17 20.78813 20.03991 20.40664
#2009-07-20 21.41278 21.41278 20.03991
#2009-07-21 22.99630 22.98397 21.41278
#2009-07-22 23.06443 23.01112 22.98397
#2009-07-23 23.45905 24.72232 23.01112
#2009-07-24 24.89291 25.56603 24.72232
#2009-07-27 25.38929 24.80535 25.56603
#2009-07-28 25.26712 25.65566 24.80535
#2009-07-29 25.83884 24.98163 25.65566
#2009-08-04 26.02464 25.49159 25.93297


dat2[1,2]<- Inf
 dat2[5,3]<- -Inf


dat2[rowSums(is.finite(dat2))==ncol(dat2),]
#                 V2       V3       V4
#2009-07-20 21.41278 21.41278 20.03991
#2009-07-21 22.99630 22.98397 21.41278
#2009-07-22 23.06443 23.01112 22.98397
#2009-07-24 24.89291 25.56603 24.72232
#2009-07-27 25.38929 24.80535 25.56603
#2009-07-28 25.26712 25.65566 24.80535
#2009-07-29 25.83884 24.98163 25.65566
#2009-08-04 26.02464 25.49159 25.93297


A.K.

Hi There, 

I have a dataset with many rows and few columns as following: 

2009-07-15    #N/A N/A    #N/A N/A    18.96858 
2009-07-16    20.30685    20.40664    #N/A N/A 
2009-07-17    20.78813    20.03991    20.40664 
2009-07-20    21.41278    21.41278    20.03991 
2009-07-21    22.9963    22.98397    21.41278 
2009-07-22    23.06443    23.01112    22.98397 
2009-07-23    23.45905    24.72232    23.01112 
2009-07-24    24.89291    25.56603    24.72232 
2009-07-27    25.38929    24.80535    25.56603 
2009-07-28    25.26712    25.65566    24.80535 
2009-07-29    25.83884    24.98163    25.65566 
2009-07-30    #N/A N/A    #N/A N/A    24.98163 
2009-08-03    25.25553    25.93297    #N/A N/A 
2009-08-04    26.02464    25.49159    25.93297 

The class of the dataset is "zoo". My question might be stupid 
but could anyone suggest a way to remove the rows with #N/A values? 
I tried "rapply" command but it didn't work due to the data class. 

btw, how about for the "Inf" values? 

Thank you in advance!