I'm trying to recreate some trellis graphs I've successfully created using PROC R, but with Python, and failing at the initial stage of importing SAS data sets into Python.
OPTIONS SET = PYTHONHOME 'F:\ProgramData\anaconda3';
DATA sasuser.v_prdsale / VIEW = sasuser.v_prdsale;
SET sashelp9.prdsale;
LENGTH yyq $6;
yyqtr = year + (quarter - 1) / 4;
mon = MONTH(month);
yyq = PUT(month, YYQ6.);
yq = INTCK('QTR', '31dec1992'd, month);
SELECT (country);
WHEN ('U.S.A.') cntry = 'USA';
WHEN ('GERMANY') cntry = 'DE';
WHEN ('CANADA') cntry = 'CA';
OTHERWISE;
END;
RUN;
PROC SUMMARY DATA = sasuser.v_prdsale MISSING NWAY;
CLASS cntry yq product;
VAR actual;
OUTPUT OUT = prdsale (DROP = _:) SUM=;
FORMAT _ALL_;
RUN;
PROC PRINT DATA = prdsale;
TITLE 'PRDSALE summary';
RUN;
ODS ESCAPECHAR='^';
ODS HTML FILE = "./python_plotly_WPS.html" STYLE=minimal GTITLE GFOOTNOTE GPATH="./images";
PROC PYTHON TERMINATE;
EXPORT DATA = prdsale PYTHON = sasdata;
SUBMIT;
print(sasdata)
ENDSUBMIT;
RUN;
ODS HTML CLOSE;
What I get are the following Python messages:
NOTE: Submitting statements to Python:
NOTE: File "<string>", line 2
NOTE: print(sasdata)
NOTE: IndentationError
NOTE: :
NOTE: unexpected indent
The SAS data set converted to the Python dataframe is:
cntry yq PRODUCT ACTUAL
CA 1 BED 4337
CA 1 CHAIR 5115
CA 1 DESK 6644
CA 1 SOFA 6931
CA 1 TABLE 5977
CA 2 BED 6459
CA 2 CHAIR 4334
CA 2 DESK 6906
CA 2 SOFA 7505
CA 2 TABLE 5611
CA 3 BED 5199
CA 3 CHAIR 7908
CA 3 DESK 5441
CA 3 SOFA 6628
CA 3 TABLE 5870
CA 4 BED 5849
CA 4 CHAIR 7105
CA 4 DESK 6684
CA 4 SOFA 5656
CA 4 TABLE 4861
CA 5 BED 6787
CA 5 CHAIR 6888
CA 5 DESK 6668
CA 5 SOFA 5532
CA 5 TABLE 5425
CA 6 BED 7377
CA 6 CHAIR 7275
CA 6 DESK 6408
CA 6 SOFA 6514
CA 6 TABLE 7000
CA 7 BED 7207
CA 7 CHAIR 5219
CA 7 DESK 5538
CA 7 SOFA 5544
CA 7 TABLE 6345
CA 8 BED 4514
CA 8 CHAIR 6395
CA 8 DESK 7898
CA 8 SOFA 5825
CA 8 TABLE 5611
DE 1 BED 5026
DE 1 CHAIR 6276
DE 1 DESK 4330
DE 1 SOFA 8915
DE 1 TABLE 5761
DE 2 BED 6511
DE 2 CHAIR 6098
DE 2 DESK 7207
DE 2 SOFA 7272
DE 2 TABLE 7792
DE 3 BED 6887
DE 3 CHAIR 4697
DE 3 DESK 7743
DE 3 SOFA 8267
DE 3 TABLE 5039
DE 4 BED 5094
DE 4 CHAIR 6074
DE 4 DESK 5878
DE 4 SOFA 6274
DE 4 TABLE 6263
DE 5 BED 6172
DE 5 CHAIR 5583
DE 5 DESK 5038
DE 5 SOFA 6215
DE 5 TABLE 7182
DE 6 BED 4568
DE 6 CHAIR 7661
DE 6 DESK 4447
DE 6 SOFA 6720
DE 6 TABLE 5616
DE 7 BED 4943
DE 7 CHAIR 5333
DE 7 DESK 6397
DE 7 SOFA 4600
DE 7 TABLE 7231
DE 8 BED 6933
DE 8 CHAIR 5383
DE 8 DESK 7462
DE 8 SOFA 6797
DE 8 TABLE 4313
USA 1 BED 4665
USA 1 CHAIR 5709
USA 1 DESK 7003
USA 1 SOFA 5563
USA 1 TABLE 7018
USA 2 BED 7371
USA 2 CHAIR 4435
USA 2 DESK 7027
USA 2 SOFA 4160
USA 2 TABLE 7115
USA 3 BED 5895
USA 3 CHAIR 7609
USA 3 DESK 5829
USA 3 SOFA 5732
USA 3 TABLE 4690
USA 4 BED 6170
USA 4 CHAIR 7660
USA 4 DESK 5475
USA 4 SOFA 6529
USA 4 TABLE 5398
USA 5 BED 4562
USA 5 CHAIR 5706
USA 5 DESK 7238
USA 5 SOFA 5071
USA 5 TABLE 5696
USA 6 BED 6137
USA 6 CHAIR 6344
USA 6 DESK 4985
USA 6 SOFA 6138
USA 6 TABLE 6169
USA 7 BED 6368
USA 7 CHAIR 7469
USA 7 DESK 5845
USA 7 SOFA 6363
USA 7 TABLE 4647
USA 8 BED 7006
USA 8 CHAIR 6004
USA 8 DESK 5141
USA 8 SOFA 3837
USA 8 TABLE 5570
