-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of PIKAL Petr
Sent: Thursday, April 28, 2016 9:42 AM
To: G.Maubach at weinwolf.de; r-help at r-project.org
Subject: Re: [R] Interdependencies of variable types, logical expressions and
NA
Hi
Your script is not reproducible.
Creating Check_U_0__Kd_1_2011 from Umsatz_2011 and Kunde01_2011
Error in ifelse(Kunden01[[Umsatz]] == 0 & Kunden01[[Kunde]] == 1, 1, 0) :
object 'Kunden01' not found
This is interesting
x <- c(NA, FALSE, TRUE)
names(x) <- as.character(x)
outer(x, x, "&") ## AND table
<NA> FALSE TRUE
<NA> NA FALSE NA
FALSE FALSE FALSE FALSE
TRUE NA FALSE TRUE
I am not sure, but the logic for AND is to return TRUE only when both
expressions are TRUE.
so
T&T = T
F&F = F
T&NA = NA (you cannot decide hence NA)
F&NA = F (you can decide that regardless of NA the result must be F)
outer(x, x, "|") ## OR table
<NA> FALSE TRUE
<NA> NA NA TRUE
FALSE NA FALSE TRUE
TRUE TRUE TRUE TRUE
OTOH the logic for OR table is that if one of the expressions is TRUE the result
must be TRUE
T | T = T
F | F = F
T&NA = T (you can decide that regardless value in NA the result must be T)
F&NA = NA (you cannot decide hence NA)
And I believe that all your results can be explained by this logic.
Cheers
Petr
-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of
G.Maubach at weinwolf.de
Sent: Thursday, April 28, 2016 9:08 AM
To: r-help at r-project.org
Subject: [R] Interdependencies of variable types, logical expressions and
Hi All,
my script tries to do the following on factors:
## Check for case 3: Umsatz = 0 & Kunde = 1
for (year in 2011:2015) {
+ Umsatz <- paste0("Umsatz_", year)
+ Kunde <- paste0("Kunde01_", year)
+ Check <- paste0("Check_U_0__Kd_1_", year)
+
+ cat('Creating', Check, 'from', Umsatz, "and", Kunde, '\n')
+
+ Kunden01[[ Check ]] <- ifelse(Kunden01[[ Umsatz ]] == 0 &
+ Kunden01[[ Kunde ]] == 1,
+ 1, 0
+ )
+ Kunden01[[ Check ]] <- factor(Kunden01[[ Check ]],
+ levels=c(1, 0),
+ labels= c("Check 0", "OK")
+ )
+
+ }
Creating Check_U_0__Kd_1_2011 from Umsatz_2011 and Kunde01_2011
Creating Check_U_0__Kd_1_2012 from Umsatz_2012 and Kunde01_2012
Creating Check_U_0__Kd_1_2013 from Umsatz_2013 and Kunde01_2013
Creating Check_U_0__Kd_1_2014 from Umsatz_2014 and Kunde01_2014
Creating Check_U_0__Kd_1_2015 from Umsatz_2015 and Kunde01_2015
table(Kunden01$Check_U_0__Kd_1_2011, useNA = "ifany")
table(Kunden01$Check_U_0__Kd_1_2012, useNA = "ifany")
table(Kunden01$Check_U_0__Kd_1_2013, useNA = "ifany")
table(Kunden01$Check_U_0__Kd_1_2014, useNA = "ifany")
table(Kunden01$Check_U_0__Kd_1_2015, useNA = "ifany")
Kunden01$Check_U_0__Kd_1_all <-
ifelse(Kunden01$Check_U_0__Kd_1_2011 ==
1 |
+ Kunden01$Check_U_0__Kd_1_2012 ==
1 |
+ Kunden01$Check_U_0__Kd_1_2013 ==
1 |
+ Kunden01$Check_U_0__Kd_1_2014 ==
1 |
+ Kunden01$Check_U_0__Kd_1_2015 ==
1,
+ 1, 0)
table(Kunden01$Check_U_0__Kd_1_all, useNA = "ifany")
0 <NA>
7 23
(Ann.: I made the values up. But the relations equal real world data.)
I had expected to get back a factor or at least a numeric variable
containing 0, 1 and NA, instead 1 is not included.
I searched the web for information on the treatment of logical expressions
when the data contains NA. I found:
1.
https://stat.ethz.ch/R-manual/R-devel/library/base/html/NA.html
Examples
# Some logical operations do not return NA
c(TRUE, FALSE) & NA
c(TRUE, FALSE) | NA
2.
https://stat.ethz.ch/R-manual/R-devel/library/base/html/Logic.html
NA is a valid logical object. Where a component of x or y is NA, the
result will be NA if the outcome is ambiguous. In other words NA & TRUE
evaluates to NA, but NA & FALSE evaluates to FALSE. See the examples
below.
## construct truth tables :
x <- c(NA, FALSE, TRUE)
names(x) <- as.character(x)
outer(x, x, "&") ## AND table
outer(x, x, "|") ## OR table
Ann. Not very useful. How should it be read?
3.
http://www.ats.ucla.edu/stat/r/faq/missing.htm
Good explanation for NA in general and in analysis, but no information
about NA in logical expressions.
Then I made some tests with different data types and variables with NA:
-- cut --
# 2016-04-27-001_truth_table_for_logicals_and_NA.R
# Test 1
var2 <- c(TRUE, FALSE)
var3 <- c(NA, NA)
var1 <- c(1, 1)
ds <- data.frame(var1, var2, var3)
ds
ds$value_and_logical <- ifelse(ds$var1 | ds$var2, TRUE, FALSE)
ds$logical_and_na <- ifelse(ds$var2 | ds$var3, TRUE, FALSE)
ds$value_and_na <- ifelse(ds$var1 | ds$var3, TRUE, FALSE)
print(ds)
# Output
# var1 var2 var3 value_and_logical logical_and_na value_and_na
# 1 1 TRUE NA TRUE TRUE TRUE
# 2 1 FALSE NA TRUE NA TRUE
# Test 2
ds$var1 <- factor(ds$var1, levels = c(0, 1), labels = c("NOT ok", "OK"))
ds$var2 <- factor(ds$var2, levels = c(0, 1), labels = c("NOT ok", "OK"))
ds$var3 <- factor(ds$var3, levels = c(0, 1), labels = c("NOT ok", "OK"))
ds$value_and_logical <- ifelse(ds$var1 | ds$var2, TRUE, FALSE)
ds$logical_and_na <- ifelse(ds$var2 | ds$var3, TRUE, FALSE)
ds$value_and_na <- ifelse(ds$var1 | ds$var3, TRUE, FALSE)
# Output (abbrev.)
# Warning message:
# In Ops.factor(ds$var1, ds$var3) : ?|? ist nicht sinnvoll f?r Faktoren
print(ds)
# Output
# var1 var2 var3 value_and_logical logical_and_na value_and_na
# 1 OK <NA> <NA> NA NA NA
# 2 OK <NA> <NA> NA NA NA
-- cut --
I had expected to get the same result in Test 2 as in Test 1.
Where can I find information and documentation about NA handling in
logical expressions on different variable types?
Kind regards
Georg