I am looking to join two tables together
Table 1 - The baseball dataset
DATA baseball;
SET sashelp.baseball
(KEEP = crhits);
RUN;
Table 2 - A table containing the percentiles of CRhits
PROC STDIZE
DATA = baseball
OUT=_NULL_
PCTLMTD=ORD_STAT
PCTLDEF=5
OUTSTAT=STDLONGPCTLS
(WHERE = (SUBSTR(_TYPE_,1,1) = "P"))
pctlpts = 1 TO 99 BY 1;
RUN;
I would like to join these tables together to create a table that contains the values for crhits and then a column identifying which percentile that value belongs to like below
crhits percentile percentile_value
54 p3 54
66 p5 66
825 p63 825
1134 p76 1133
The last column indicates the percentile value given by stdlongpctls
I currently use the following code to calculate the percentiles and a loop to count the number of "Events" per percentile, per factor
I have tried a cross-join but I am having trouble visualising how to join these two tables without an explicit key
PROC SQL;
CREATE TABLE cross_join_table AS
SELECT
a.crhits
, b._TYPE_
, CASE WHEN
a.crhits < b.type THEN b._TYPE_ END AS percentile
FROM
baseball a
CROSS JOIN
stdlongpctls b;
QUIT;
If there is another easier / more efficient way to find the number of observations and number of dependent variables (eg I am modelling on a default flag event in my actual dataset, so the sum of 1's per percentile group, I would appreciate it)
Use PROC RANK instead to group it into the percentiles.
proc rank data=sashelp.baseball out=baseball_ranks group=100;
var crhits;
rank rank_crhits;
run;
You can then summarize it using PROC MEANS.
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.