[R] NA value in list of data frame
Thevaraja, Mayooran
M@Thev@r@j@ @end|ng |rom m@@@ey@@c@nz
Fri Oct 18 03:58:05 CEST 2019
Hello
You can use the following function,
######################################################
replace_missings <- function(x, replacement) {
is_missings <- is.na(x)
x[is_missings] <- replacement
message(sum(is_missings), " missings replaced by the given value ", replacement)
x
}
A <- c(0,1,2,3,4,5,6,7,8,9,10)
B <- c(12,15,3,65,NA,12,NA,4,6,25,4)
df <- data.frame(A,B)
replace_missings(df, replacement = 0)
#################################################
Regards
Mayooran
-----Original Message-----
From: R-help <r-help-bounces using r-project.org> On Behalf Of ani jaya
Sent: Friday, 18 October 2019 2:43 PM
To: r-help <r-help using r-project.org>
Subject: [R] NA value in list of data frame
Dear R-Help,
I have a list of data frame that I import from excel file using read.xlsx command.
sheets <- openxlsx::getSheetNames("rainfall.xlsx")
test <- lapply(sheets,function(i) read.xlsx("rainfall.xlsx", sheet=i, startRow=8, cols=1:2))
names(test) <- sprintf("%i", 1986:2015)
And I got a data.frame with 365 rows and two columns contains date and rainfall data.
There is a value in rainfall data that i want to change as NA (8888). So my question is how to change those value in all the data frame?
test[1]$`1986`
Date RR
1 01-01-1986 0
2 02-01-1986 7
3 03-01-1986 72
4 04-01-1986 4
5 05-01-1986 19
6 06-01-1986 4
7 07-01-1986 16
8 08-01-1986 21
9 09-01-1986 34
10 10-01-1986 72
11 11-01-1986 93
12 12-01-1986 178
13 13-01-1986 86
14 14-01-1986 11
15 15-01-1986 0
16 16-01-1986 31
17 17-01-1986 22
18 18-01-1986 18
19 19-01-1986 3
20 20-01-1986 0
21 21-01-1986 31
22 22-01-1986 46
23 23-01-1986 4
24 24-01-1986 40
25 25-01-1986 63
26 26-01-1986 125
27 27-01-1986 33
28 28-01-1986 44
29 29-01-1986 6
30 30-01-1986 0
31 31-01-1986 0
32 01-02-1986 2
33 02-02-1986 71
34 03-02-1986 8888
35 04-02-1986 0
36 05-02-1986 0
37 06-02-1986 56
38 07-02-1986 19
39 08-02-1986 3
40 09-02-1986 7
41 10-02-1986 24
42 11-02-1986 55
43 12-02-1986 0
44 13-02-1986 0
.
.
.
Should I extract the data frame from the list one by one?
Thank you for your help!
Best,
Saat M.
(Sorry for the uncompleted email before).
[[alternative HTML version deleted]]
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