I need to have a new variable ethnicity.
The variables that I have now:
Dutch (if yes = 1, if no = 0)
Russian (if yes = 2, if no =0)
So it looks like that now:
Russian Dutch
2 0
0 1
0 1
2 0
How can I combine "Dutch"and "Russian"variables into new one Ethnicity"?
I want to have this result:
Ethnicity
2
1
1
2
I have tried to it with compute, but it was not successful.
The simple\basic\generic approach is:
if dutch=1 ethnicity=1.
if russian=2 ethnicity=2.
But if I understand the structure of your data right, this should also work:
compute ethnicity=sum(dutch, russian).
Related
I'm wondering if there's a way for me to perform an exact match compare in SPSS. Currently, using the following will return system missing (null) in cases where one variable is sysmis:
compute var1_comparison = * Some logic here.
compute var1_check = var1 = var1_comparison.
The results look like this (hypens representing null values):
ID var1 var1_comparison var1_check
1 3 3 1
2 4 3 0
3 - 2 -
4 1 1 1
5 - - -
What I want is this:
ID var1 var1_comparison var1_check
1 3 3 1
2 4 3 0
3 - 2 0
4 1 1 1
5 - - 1
Is this possible using just plain SPSS syntax? I'm also open to using the Python extension, though I'm not as familiar with it.
Here's a slightly different approach, using temporary scratch variables (prefixed by a hash (#)):
recode var1 var1_comparison (sysmis=-99) (else=copy) into #v1 #v2.
compute Check=(#v1 = #v2).
This is to recreate your example:
data list list/ID var1 var1_comparison.
begin data
1, 3, 3
2 , 4, 3
3, , 2
4, 1, 1
5, ,
end data.
Now you have to deal separately with the situation where both values are missing, and then complete the calculation in all other situations:
do if missing(var1) or missing(var1_comparison).
compute var1_check=(missing(var1) and missing(var1_comparison)).
else.
compute var1_check = (var1 = var1_comparison).
end if.
I have a dataset that has three variables which indicate a category of event at three time points (dispatch, beginning, end). I want to establish the number of cases where (a) the category is the same for all three time points (b) those which have changed at time point 2 (beginning) and (c) those which have changed at time point 3 (end).
Can anyone recommend some syntax or a starting point?
To measure a change (non-equivalent) against T0 (Time zero or in your case Dispatch), wouldn't you simply check for equivalence between respective variables?:
DATA LIST FREE /ID T0 T1 T2.
BEGIN DATA.
1 1 1 1.
2 1 1 0.
3 1 0 1.
4 0 1 1.
5 1 0 0.
6 0 1 0.
7 0 0 1.
8 0 0 0.
END DATA.
COMPUTE ChangeT1=T0<>T1.
COMPUTE ChangeT2=T0<>T2.
To check all the values are the same across all three variables would be just (given you have string variables else otherwise you could do this differently if working with numeric variables such as Standard deviation):
COMPUTE CheckNoChange=T0=T1 & T0=T2.
Is it Possible to replace 0 value and turn it into dash in fast report?
like:
No. turns to
1 1
2 2
0 -
3 3
0 -
0 -
Yes.
Use a built-in script engine.
Assuming you have a dataset DS and a field FIELD_NAME then instead of [DS."FIELD_NAME"] you should write [IIF(<DS."FIELD_NAME"> = 0, '-', <DS."FIELD_NAME">)] as your frxMemoView text.
I have the following SPSS syntax to count using a conditional
DATASET ACTIVATE Conjunto_de_datos1.
DO IF (((p7_1 = 1) | (p7_2 = 1)) & (periodo = 2)).
COUNT noque_o_noria=p7_2 p7_1(1).
END IF.
EXECUTE.
the data is the folowing
p7_1 p7_2 periodo
1 1 2
1 0 2
1 1 2
1 1 1
1 1 1
0 1 2
The problem I have is that in the new column each row that meet the rule is given automatically the value 2, and the ones that don't meet the rule are lost values (empty).
What should I add to the code above to retrieve me 1 when it meets the rule and 0 when not?
You don't need so much syntax to do that. Just
compute noque_o_noria=(p7_2 = 1 or p7_1 = 1) and periodo = 2.
will do.
There is no point for the COUNT command, so you can use a COMPUTE noque_o_noria = 1 instead and then specify an ELSE condition, e.g.
DO IF (((p7_1 = 1) | (p7_2 = 1)) & (periodo = 2)).
COMPUTE noque_o_noria = 1.
ELSE.
COMPUTE noque_o_noria = 0.
END IF.
I suspect that the periodo variable was previously defined, and the DO IF is leaving the old values unchanged.
If the variable is new, then cases bypassed by DO IF will have the sysmis value. For cases that are processed by COUNT, the variable is initialized to zero for each case.
I currently have a data file that is structured like this:
1
-
-
2
-
3
-
I would like it to look like this:
1
1
1
2
2
3
3
Unfortunately I do not how to achieve this in SPSS. Is there are a simple command that could recode the data this way?
I have found the answer, by using the LAG function. (I defined 9999 as a missing value).
IF (variable = 9999) variable=LAG(variable).
EXECUTE.