On 18/10/19 2:43 PM, ani jaya wrote:
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]$`1986`
Date RR
1 01-01-1986 0
2 02-01-1986 7
3 03-01-1986 72
4 04-01-1986 4
5 05-01-1986 19
6 06-01-1986 4
7 07-01-1986 16
8 08-01-1986 21
9 09-01-1986 34
10 10-01-1986 72
11 11-01-1986 93
12 12-01-1986 178
13 13-01-1986 86
14 14-01-1986 11
15 15-01-1986 0
16 16-01-1986 31
17 17-01-1986 22
18 18-01-1986 18
19 19-01-1986 3
20 20-01-1986 0
21 21-01-1986 31
22 22-01-1986 46
23 23-01-1986 4
24 24-01-1986 40
25 25-01-1986 63
26 26-01-1986 125
27 27-01-1986 33
28 28-01-1986 44
29 29-01-1986 6
30 30-01-1986 0
31 31-01-1986 0
32 01-02-1986 2
33 02-02-1986 71
34 03-02-1986 8888
35 04-02-1986 0
36 05-02-1986 0
37 06-02-1986 56
38 07-02-1986 19
39 08-02-1986 3
40 09-02-1986 7
41 10-02-1986 24
42 11-02-1986 55
43 12-02-1986 0
44 13-02-1986 0
.
.
.
Should I extract the data frame from the list one by one?
Try (something like):
revisedTest <- lapply(test,function(x){x$RR[x$RR==8888] <- NA; x})
Or, using Bert Gunter's slick is.na() trick:
revisedTest <- lapply(test,function(x){is.na(x$RR) <- x$RR==8888; x})
(Note: not tested.)
cheers,
Rolf Turner
--
Honorary Research Fellow
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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