Following my question here: *
I would like to change the NA values by 0 when year >= 1997 & <=2010.
Here is a subset of the dataset :
structure(list(gid = c(79600, 79600, 79600, 79600, 79600, 79600,
79600, 79600, 79600, 79600, 79600, 79600, 79600, 79600, 79600,
79600, 79600, 79600, 79600, 79600, 79600, 79600, 79600, 79600,
79600, 79600, 79600, 79600, 79600, 79600, 79601, 79601, 79601,
79601, 79601, 79601, 79601, 79601, 79601, 79601, 79601, 79601,
79601, 79601, 79601, 79601, 79601, 79601, 79601, 79601, 79601,
79601, 79601, 79601, 79601, 79601, 79601, 79601, 79601, 79601
), Year = c(1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989,
1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000,
2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 1981,
1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992,
1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
2004, 2005, 2006, 2007, 2008, 2009, 2010), TotalConflicts = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), IncidenceConflicts = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA,
-60L), class = c("tbl_df", "tbl", "data.frame"))
Please note that the column IncidenceConflict is a binary column. Sometimes I got 1, 0 or NA.
I tried this but it does not work:
test<- test %>%
mutate(across(3:4, ~replace(.x, .x == "NA" & Year >= 1997, 0)))
CodePudding user response：
Updated code after clarification:
ifelse will do that:
df %>%
mutate(across(3:4, ~ifelse((Year >= 1997 & Year <= 2010)
& is.na(.), 0, .)))
gid Year TotalConflicts IncidenceConflicts
<dbl> <dbl> <dbl> <dbl>
1 79600 1981 NA NA
2 79600 1982 NA NA
3 79600 1983 NA NA
4 79600 1984 NA NA
5 79600 1985 NA NA
6 79600 1986 NA NA
7 79600 1987 NA NA
8 79600 1988 NA NA
9 79600 1989 NA NA
10 79600 1990 NA NA
11 79600 1991 NA NA
12 79600 1992 NA NA
13 79600 1993 NA NA
14 79600 1994 NA NA
15 79600 1995 NA NA
16 79600 1996 NA NA
17 79600 1997 0 0
18 79600 1998 0 0
19 79600 1999 0 0
20 79600 2000 0 0
21 79600 2001 0 0
22 79600 2002 0 0
23 79600 2003 0 0
24 79600 2004 0 0
25 79600 2005 0 0
26 79600 2006 0 0
27 79600 2007 0 0
28 79600 2008 0 0
29 79600 2009 0 0
30 79600 2010 0 0
31 79601 1981 NA NA
32 79601 1982 NA NA
33 79601 1983 NA NA
34 79601 1984 NA NA
35 79601 1985 NA NA
36 79601 1986 NA NA
37 79601 1987 NA NA
38 79601 1988 NA NA
39 79601 1989 NA NA
40 79601 1990 NA NA
41 79601 1991 NA NA
42 79601 1992 NA NA
43 79601 1993 NA NA
44 79601 1994 NA NA
45 79601 1995 NA NA
46 79601 1996 NA NA
47 79601 1997 0 0
48 79601 1998 0 0
49 79601 1999 2 1
50 79601 2000 0 0
51 79601 2001 0 0
52 79601 2002 0 0
53 79601 2003 0 0
54 79601 2004 0 0
55 79601 2005 0 0
56 79601 2006 0 0
57 79601 2007 0 0
58 79601 2008 0 0
59 79601 2009 0 0
60 79601 2010 0 0
>
ggh4x.axis.nesttext.y = element_text(margin = margin(r = 6, l = 6)),
CodePudding user response：
df %>%
mutate(across(3:4, ~ case_when(
between(x = Year, 1997, 2010) & is.na(.x) ~ 0,
TRUE ~ .x
)))
A tibble: 19 × 4
gid Year TotalConflicts IncidenceConflicts
<dbl> <dbl> <dbl> <dbl>
1 79600 1992 NA NA
2 79600 1993 NA NA
3 79600 1994 NA NA
4 79600 1995 NA NA
5 79600 1996 NA NA
6 79600 1997 0 0
7 79600 1998 0 0
8 79600 1999 0 0
9 79600 2000 0 0
10 79600 2001 0 0
11 79600 2002 0 0
12 79600 2003 0 0
13 79600 2004 0 0
CodePudding user response：
library(data.table)
COLS <- c("TotalConflicts", "IncidenceConflicts")
setDT(dt)[between(Year, 1997, 2010),
(COLS) := lapply(.SD, function(x) fifelse(is.na(x), 0, x)), .SDcols = COLS][]