I have two table looks like and I want to add column score to tableA from tableB, then get tableC, how to do in SAS?
the only rule is to add a column in tableA name "score " and its value is same as column "score" in tableB (which are all the same in tableB)
+----+---+---+---+
| id | b | c | d |
+----+---+---+---+
| 1 | 5 | 7 | 2 |
| 2 | 6 | 8 | 3 |
| 3 | 7 | 8 | 1 |
| 4 | 5 | 7 | 2 |
| 5 | 6 | 8 | 3 |
| 6 | 7 | 8 | 1 |
+----+---+---+---+
tableA
+---+---+-------+
| e | f | score |
+---+---+-------+
| 3 | 7 | 11 |
| 4 | 6 | 11 |
| 5 | 5 | 11 |
+---+---+-------+
tableB
+----+---+---+---+-------+
| id | b | c | d | score |
+----+---+---+---+-------+
| 1 | 5 | 7 | 2 | 11 |
| 2 | 6 | 8 | 3 | 11 |
| 3 | 7 | 8 | 1 | 11 |
| 4 | 5 | 7 | 2 | 11 |
| 5 | 6 | 8 | 3 | 11 |
| 6 | 7 | 8 | 1 | 11 |
+----+---+---+---+-------+
tableC
If the "id" is present in both tables, you can use the following to create Table C:
PROC SQL;
CREATE TABLE tableC AS
SELECT a.*, b.score
FROM tableA a JOIN tableB b
ON a.id = b.id;
QUIT;
Please confirm that this is what you need?
Related
I have data looking like this:
| ID |OpID|
| -- | -- |
| 10 | 1 |
| 10 | 2 |
| 10 | 4 |
| 11 |null|
| 12 | 3 |
| 12 | 4 |
| 13 | 1 |
| 13 | 2 |
| 13 | 3 |
| 14 | 2 |
| 14 | 4 |
Here OpID 4 means 1 and 2.
I would like to count the different occurrences of 1, 2 and 3 in OpID of distinct ID.
If the counts of OpID having 1 would be 4, 2 would be 4, 3 would be 2.
If ID has OpID of 4 but already has data of 1, 2 it wouldn't be counted. But if 4 exists and only 1 (2) is there, count for 2 (1) would be incremented.
The expected output would be:
|OpID|Count|
| 1 | 4 |
| 2 | 4 |
| 3 | 2 |
(Going to be using the results in a column chart)
Hope this makes sense...
edit: there are other columns too and an ID and OpID can be duplicated hence need to do a groupby clause before.
I would like to know how could I get the Sum of all working days for specific month but in the table starting each month's Sum over again.
This is my DateTable Now with this query for Work Days Sum:
Work Days Sum =
CALCULATE (
SUM ( 'DateTable'[Is working Day] ),
ALL ( 'DateTable' ),
'DateTable'[Date] <= EARLIER ( 'DateTable'[Date] )
)
Date | Month Order | Is working day | Work Days Sum |
January - 21 331
2022/01/01 | 1 | 0 | |
2022/01/02 | 1 | 0 | |
2022/01/03 | 1 | 1 | 1 |
2022/01/04 | 1 | 1 | 2 |
2022/01/05 | 1 | 1 | 3 |
2022/01/06 | 1 | 1 | 4 |
.....
2022/01/27 | 1 | 1 | 19 |
2022/01/28 | 1 | 1 | 20 |
2022/01/29 | 1 | 0 | 20 |
2022/01/30 | 1 | 0 | 20 |
2022/01/31 | 1 | 1 | 21 |
February 20 890
2022/02/01 | 2 | 1 | 22 |
2022/02/02 | 2 | 1 | 23 |
2022/02/03 | 2 | 1 | 24 |
2022/02/04 | 2 | 1 | 25 |
|
|
V
Date | Month Order | Is working day | Work Days Sum |
January - 21 21
2022/01/01 | 1 | 0 | |
2022/01/02 | 1 | 0 | |
2022/01/03 | 1 | 1 | 1 |
2022/01/04 | 1 | 1 | 2 |
2022/01/05 | 1 | 1 | 3 |
2022/01/06 | 1 | 1 | 4 |
.....
2022/01/27 | 1 | 1 | 19 |
2022/01/28 | 1 | 1 | 20 |
2022/01/29 | 1 | 0 | 20 |
2022/01/30 | 1 | 0 | 20 |
2022/01/31 | 1 | 1 | 21 |
February 20 41
2022/02/01 | 2 | 1 | 1 |
2022/02/02 | 2 | 1 | 2 |
2022/02/03 | 2 | 1 | 3 |
2022/02/04 | 2 | 1 | 4 |
2022/02/05 | 2 | 0 | 4 |
.....
Any idea on how I can change my dax query to achieve output of second table below the down arrow would be much appreciated.
Good day! I have a sample employee table like the one below. I need a DAX formula in Power BI to create a measure to count the number of direct reports of each employee. For Example, the Direct Report count of GL0001 will be 2 (Because GL0001 is the line manager of GL0002 and GL0019 and they report to GL0001), the Direct Report count of EMP-02023 will be 3, Direct Report count of GL0002 will be 3. Please help me also to create measures regarding the count of only one direct reporting and less than three direct reporting
| Employee ID | Line Manager ID | Layer (of Employee) | Layer (of Line Manager) |
|--------------|-------------------|----------------------|--------------------------|
| EMP-01980 | GL0003 | 4 | 3 |
| EMP-02023 | EMP-02015 | 6 | 5 |
| EMP-01636 | EMP-02015 | 6 | 5 |
| EMP-02138 | EMP-02162 | 6 | 5 |
| EMP-02145 | EMP-01980 | 5 | 4 |
| GL0023 | GL0022 | 5 | 4 |
| GL0001 | | 1 | 0 |
| GL0002 | GL0001 | 2 | 1 |
| GL0003 | GL0002 | 3 | 2 |
| GL0019 | GL0001 | 2 | 1 |
| GL0020 | GL0002 | 3 | 2 |
| GL0024 | GL0002 | 3 | 2 |
| EMP-01918 | EMP-00791 | 9 | 8 |
| EMP-01941 | EMP-00791 | 9 | 8 |
| EMP-02019 | EMP-02156 | 8 | 7 |
| EMP-02024 | EMP-02023 | 7 | 6 |
| EMP-02025 | EMP-02023 | 7 | 6 |
| EMP-03001 | EMP-02023 | 7 | 6 |
Your data doesn't have all the Employee ID for each Line Manager ID. That means the PATH calculation would not work.
I've assumed your data looks like this
Employee ID
Line Manager ID
1000001
1000002
1000001
1000003
1000002
1000004
1000003
1000005
1000004
1000006
1000005
1000007
1000006
1000008
1000007
1000009
1000006
1000010
1000003
Creating Calculated columns you can calculate the PATH and the PATH SIZE
Path
Path = path('Table'[Employee ID],'Table'[Line Manager ID])
Path Size
Path Length = PATHLENGTH([Path])
Output
Edit
In that case, you can use the Line Manager ID column to count direct reports, measure below.
DAX: Calculated Column
CountDirectReport =
VAR EmpId = [Employee ID]
RETURN
CALCULATE (
COUNTROWS ( 'Table' ),
FILTER ( 'Table', [Line Manager ID] = EmpId )
)
Output
I have a below table
+------+------+------+------+------+-----+
| Yr | col1 | col2 | col3 | col4 | PQR |
+------+------+------+------+------+-----+
| 2012 | 1 | 0 | 1 | 1 | 2 |
| 2012 | 0 | 1 | 0 | 0 | 4 |
| 2013 | 1 | 1 | 1 | 1 | 6 |
| 2014 | 0 | 0 | 0 | 0 | 8 |
| 2012 | 1 | 0 | 1 | 1 | 7 |
| 2013 | 0 | 1 | 0 | 0 | 3 |
| 2014 | 1 | 0 | 1 | 1 | 2 |
| 2012 | 0 | 1 | 0 | 0 | 10 |
| 2014 | 0 | 0 | 1 | 0 | 12 |
| 2014 | 0 | 0 | 0 | 0 | 5 |
+------+------+------+------+------+-----+
The output I want is as below
+------+-------+------+------+------+
| | Total | 2012 | 2013 | 2014 |
+------+-------+------+------+------+
| col1 | 17 | 9 | 6 | 2 |
| col2 | 23 | 14 | 9 | 0 |
| col3 | 29 | 9 | 6 | 14 |
| col4 | 17 | 9 | 6 | 2 |
+------+-------+------+------+------+
For row col1 in my output table
The column `Total` is `SUM(PQR)` when `col1` is 1 my input table
The value `17` is `SUM(PQR)` when `col1` is 1 in my input table
The value in col `2012` is `SUM(PQR)` when `col1` is 1 and `Yr=2012` in my input table
The value `9` is `SUM(PQR)` when `col1` is 1 and `Yr=2012` in my input table
Similarly 6 in column 2013 is SUM(PQR) when col1 is 1 and Yr is 2013
Hope the process to get output table is understood
I want to achieve the above result with SAS.
Any help will be really appreciated
Transpose the data into a categorical form and use PQR as a weight in your aggregating sum. Proc TABULATE is very adept at creating such tabulations.
data have;
infile datalines dlm='|'; input
Yr col1 col2 col3 col4 PQR ; datalines;
| 2012 | 1 | 0 | 1 | 1 | 2 |
| 2012 | 0 | 1 | 0 | 0 | 4 |
| 2013 | 1 | 1 | 1 | 1 | 6 |
| 2014 | 0 | 0 | 0 | 0 | 8 |
| 2012 | 1 | 0 | 1 | 1 | 7 |
| 2013 | 0 | 1 | 0 | 0 | 3 |
| 2014 | 1 | 0 | 1 | 1 | 2 |
| 2012 | 0 | 1 | 0 | 0 | 10 |
| 2014 | 0 | 0 | 1 | 0 | 12 |
| 2014 | 0 | 0 | 0 | 0 | 5 |
run;
data have_row_id / view=have_row_id;
set have;
rowid+1;
run;
proc transpose data=have_row_id out=have_categorical;
by rowid yr pqr;
run;
proc tabulate data=have_categorical;
class yr _name_;
var col1;
weight pqr;
table _name_='', col1='' * sum=''*f=8. * (all='Total' yr='') / nocellmerge;
run;
The ='' removes labelling cells and compactifies the output.
I have simplified my problem to solve. Lets suppose I have three tables. One containing data and specific codes that identify objects lets say Apples.
+-------------+------------+-----------+
| Data picked | Color code | Size code |
+-------------+------------+-----------+
| 1-8-2018 | 1 | 1 |
| 1-8-2018 | 1 | 3 |
| 1-8-2018 | 2 | 2 |
| 1-8-2018 | 2 | 3 |
| 1-8-2018 | 2 | 2 |
| 1-8-2018 | 3 | 3 |
| 1-8-2018 | 4 | 1 |
| 1-8-2018 | 4 | 1 |
| 1-8-2018 | 5 | 3 |
| 1-8-2018 | 6 | 1 |
| 1-8-2018 | 6 | 2 |
| 1-8-2018 | 6 | 2 |
+-------------+------------+-----------+
And i have two related helping tables to help understand the codes (their relationships are inactive in the model due to ambiguity with other tables in the real case).
+-----------+--------+
| Size code | Size |
+-----------+--------+
| 1 | Small |
| 2 | Medium |
| 3 | Large |
+-----------+--------+
and
+------------+----------------+-------+
| Color code | Color specific | Color |
+------------+----------------+-------+
| 1 | Light green | Green |
| 2 | Green | Green |
| 3 | Semi green | Green |
| 4 | Red | Red |
| 5 | Dark | Red |
| 6 | Pink | Red |
+------------+----------------+-------+
Lets say that I want to create an extra column in the original table to determine which apples are class A and class B given that medium green Apples are class A and large Red apples are class B, the other remain blank as the example below.
+-------------+------------+-----------+-------+
| Data picked | Color code | Size code | Class |
+-------------+------------+-----------+-------+
| 1-8-2018 | 1 | 1 | |
| 1-8-2018 | 1 | 3 | |
| 1-8-2018 | 2 | 2 | A |
| 1-8-2018 | 2 | 3 | |
| 1-8-2018 | 2 | 2 | A |
| 1-8-2018 | 3 | 3 | |
| 1-8-2018 | 4 | 1 | |
| 1-8-2018 | 4 | 1 | |
| 1-8-2018 | 5 | 3 | B |
| 1-8-2018 | 6 | 1 | |
| 1-8-2018 | 6 | 2 | |
| 1-8-2018 | 6 | 2 | |
+-------------+------------+-----------+-------+
What's the proper DAX to use given the relationships are initially inactive. Preferably solvable without creating any further additional columns in any table. I already tried codes like:
CALCULATE (
"A" ;
FILTER ( 'Size Table' ; 'Size Table'[Size] = "Medium");
FILTER ( 'Color Table' ; 'Color Table'[Color] = "Green")
)
And many variations on the same principle
Given that the relationships are inactive, I'd suggest using LOOKUPVALUE to match ID values on the other tables. You should be able to create a calculated column as follows:
Class =
VAR Size = LOOKUPVALUE('Size Table'[Size],
'Size Table'[Size code], 'Data Table'[Size code])
VAR Color = LOOKUPVALUE('Color Table'[Color],
'Color Table'[Color code], 'Data Table'[Color code])
RETURN SWITCH(TRUE(),
(Size = "Medium") && (Color = "Green"), "A",
(Size = "Large") && (Color = "Red"), "B", BLANK())
If your relationships are active, then you don't need the lookups:
Class = SWITCH(TRUE(),
(RELATED('Size Table'[Size]) = "Medium") &&
(RELATED('Color Table'[Color]) = "Green"),
"A",
(RELATED('Size Table'[Size]) = "Large") &&
(RELATED('Color Table'[Color]) = "Red"),
"B",
BLANK())
Or a bit more elegantly written (especially for more classes):
Class =
VAR SizeColor = RELATED('Size Table'[Size]) & " " & RELATED('Color Table'[Color])
RETURN SWITCH(TRUE(),
SizeColor = "Medium Green", "A",
SizeColor = "Large Red", "B",
BLANK())