ERROR: Column itmCode_id could not be found in the table/view identified with the correlation name

Afor910327 — Tue, 27 Aug 2019 18:29:00 GMT

Does anyone know why I get this error at the end? I ran out of ideas.

Thank you!



12141  dm "log; clear;";
12142  ************************************************************;
12143
12144  %let drive=j:\IEA Products\ACPSA;
12145
12146  %let acpsaItemConc = acpsa_item_concord_2012naics;
12147  %let acpsaitemcc = acpsa_item_concord_2012naics;
12148  %let summaryConc = itemacpsa_sum_conc_naics2012;
12149  %let summaryOrder = itemacpsa_sum_order_naics2012;
12150
12151
12152  %let dsName = 'Annual17';
12153
12154  %let prodyr=2019;
12155
12156  %let b_ioyear = 1998;   * Beginning year for the macro called "price_series";
12157      /*  Note:  The price data set up so the output dataset (p_q_relatives_&currioyr.) contains the price relatives
12158                  for the year in the dataset name (b_ioear) and the year before.  That means that "p_q_relatives_1998"
12159                  dataset are the price relatives between 1997 and 1998.      */
12160  %let e_ioyear = 1998;   * Ending year for the macro called "price_series";
12161
12162  %let refyr=2012;
12163
12164  ************************************************************;
12165  ************************************************************;
12166  libname TRN odbc dsn="IEtest17" schema=trn;
NOTE: Libref TRN was successfully assigned as follows:
      Engine:        ODBC
      Physical Name: IEtest17
12167  libname MAR odbc dsn="IEtest17" schema=mar;
NOTE: Libref MAR was successfully assigned as follows:
      Engine:        ODBC
      Physical Name: IEtest17
12168  libname TCC odbc dsn="IEtest17" schema=tcc;
NOTE: Libref TCC was successfully assigned as follows:
      Engine:        ODBC
      Physical Name: IEtest17
12169  libname sql_iips odbc dsn="IEtest17" schema=dbo;
NOTE: Libref SQL_IIPS was successfully assigned as follows:
      Engine:        ODBC
      Physical Name: IEtest17
12170  libname DBO odbc dsn="IEtest17" schema=dbo;
NOTE: Libref DBO was successfully assigned as follows:
      Engine:        ODBC
      Physical Name: IEtest17
12171  libname CDE odbc dsn="IEtest17" schema=cde;
NOTE: Libref CDE was successfully assigned as follows:
      Engine:        ODBC
      Physical Name: IEtest17
12172  libname ICC odbc dsn="IEtest17" schema=icc;
NOTE: Libref ICC was successfully assigned as follows:
      Engine:        ODBC
      Physical Name: IEtest17
12173  libname occ odbc dsn="IEtest17" schema=occ;
NOTE: Libref OCC was successfully assigned as follows:
      Engine:        ODBC
      Physical Name: IEtest17
12174  libname concord "&drive\Concordances";
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
NOTE: Libref CONCORD was successfully assigned as follows:
      Engine:        V9
      Physical Name: j:\IEA Products\ACPSA\Concordances
12175  libname int_sas "&drive\Estimates\Intermediate\SAS\&prodyr";
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
NOTE: Libref INT_SAS was successfully assigned as follows:
      Engine:        V9
      Physical Name: j:\IEA Products\ACPSA\Estimates\Intermediate\SAS\2019
12176  libname TEMPSAS "c:\sas";
NOTE: Libref TEMPSAS was successfully assigned as follows:
      Engine:        V9
      Physical Name: c:\sas
12177
12178  *********************************************************************************************;
12179  proc datasets library=work kill;
NOTE: Deleting WORK.SASMACR (memtype=CATALOG).
NOTE: File WORK.SASMACR (memtype=CATALOG) cannot be deleted because it is in use.

NOTE: PROCEDURE DATASETS used (Total process time):
      real time           0.02 seconds
      cpu time            0.01 seconds


12180  proc datasets library=tempsas kill;
NOTE: Deleting TEMPSAS.ALL_PARTIALS_REMERGED (memtype=DATA).
NOTE: Deleting TEMPSAS.ALL_PARTIALS_REMERGED_SORT (memtype=DATA).
NOTE: Deleting TEMPSAS.BAD_CONC (memtype=DATA).
NOTE: Deleting TEMPSAS.CURRENT_ITEM_CONCORDANCE (memtype=DATA).
NOTE: Deleting TEMPSAS.CURRENT_ITEM_CONCORDANCE_SORT (memtype=DATA).
NOTE: Deleting TEMPSAS.CURRENT_ITEM_CONCORDANCE_SUM (memtype=DATA).
NOTE: Deleting TEMPSAS.GOOD_CONC (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_23 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_3X (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_51 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_54 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_56 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_61 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_71 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_81 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_99 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_INTERP (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_PARTIAL_COMBINE (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_PARTIAL_COMBINE_0 (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_PARTIAL_COMBINE_SORT (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEMACPSA_PARTIAL_SUMMARY (memtype=DATA).
NOTE: Deleting TEMPSAS.ITEM_CONC (memtype=DATA).
NOTE: Deleting TEMPSAS.NEW_ITEM_CONC (memtype=DATA).
NOTE: Deleting TEMPSAS.NEW_ITEM_CONC_SORT (memtype=DATA).
NOTE: Deleting TEMPSAS.NEW_ITEM_CONC_SUMMARY (memtype=DATA).
NOTE: Deleting TEMPSAS.NO_UPDATE (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ACPSA_NOT1 (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ACPSA_NOT1_SORT (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ACPSA_REMERGE (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ACPSA_SUM1 (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ACPSA_SUM_CHECK (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ALL_OTHER (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ITEM_ACPSA (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ITEM_ACPSA_FORMAT (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ITEM_ACPSA_SORT (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_ITEM_ACPSA_SUMMARY (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_NOT1_ADJ (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_NOT1_ADJ_SORT (memtype=DATA).
NOTE: Deleting TEMPSAS.PARTIAL_NOT1_CORRECTION (memtype=DATA).
NOTE: Deleting TEMPSAS.TEMP_PI_AFOR1 (memtype=DATA).
12181  run;

12182  quit;

NOTE: PROCEDURE DATASETS used (Total process time):
      real time           0.19 seconds
      cpu time            0.10 seconds


12183  **************************************************************************************************************;
12184  *********************** Item weight Excel imports   **********************************************************;
12185  **************************************************************************************************************;
12186
12187  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_23.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12188              OUT= tempsas.itemACPSA_23
12189              DBMS=xlsx;
12190              SHEET="Item_Partial_List_23";
12191              GETNAMES=YES;
12192
12193  run;

NOTE: The import data set has 9 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_23 data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.04 seconds
      cpu time            0.01 seconds


12194
12195  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_3X.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12196              OUT= tempsas.itemACPSA_3X
12197              DBMS=xlsx;
12198              SHEET="Item_Partial_List_3X";
12199              GETNAMES=YES;
12200
12201  run;

NOTE: The import data set has 35 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_3X data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.05 seconds
      cpu time            0.03 seconds


12202
12203  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_51.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12204              OUT= tempsas.itemACPSA_51
12205              DBMS=xlsx;
12206              SHEET="Item_Partial_List_51";
12207              GETNAMES=YES;
12208
12209  run;

NOTE: The import data set has 35 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_51 data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.04 seconds
      cpu time            0.03 seconds


12210
12211  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_54.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12212              OUT= tempsas.itemACPSA_54
12213              DBMS=xlsx;
12214              SHEET="Item_Partial_List_54";
12215              GETNAMES=YES;
12216
12217  run;

NOTE: The import data set has 14 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_54 data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.04 seconds
      cpu time            0.01 seconds


12218
12219  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_56.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12220              OUT= tempsas.itemACPSA_56
12221              DBMS=xlsx;
12222              SHEET="Item_Partial_List_56";
12223              GETNAMES=YES;
12224
12225  run;

NOTE: The import data set has 1 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_56 data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.03 seconds
      cpu time            0.01 seconds


12226
12227  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_61.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12228              OUT= tempsas.itemACPSA_61
12229              DBMS=xlsx;
12230              SHEET="Item_Partial_List_61";
12231              GETNAMES=YES;
12232
12233  run;

NOTE: The import data set has 9 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_61 data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.04 seconds
      cpu time            0.03 seconds


12234
12235  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_71.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12236              OUT= tempsas.itemACPSA_71
12237              DBMS=xlsx;
12238              SHEET="Item_Partial_List_71";
12239              GETNAMES=YES;
12240
12241  run;

NOTE: The import data set has 61 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_71 data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.05 seconds
      cpu time            0.06 seconds


12242
12243  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_81.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12244              OUT= tempsas.itemACPSA_81
12245              DBMS=xlsx;
12246              SHEET="Item_Partial_List_81";
12247              GETNAMES=YES;
12248
12249  run;

NOTE: The import data set has 6 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_81 data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.04 seconds
      cpu time            0.01 seconds


12250
12251  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Items_Partials_99.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12252              OUT= tempsas.itemACPSA_99
12253              DBMS=xlsx;
12254              SHEET="Item_Partial_List_99";
12255              GETNAMES=YES;
12256
12257  run;

NOTE: The import data set has 6 observations and 28 variables.
NOTE: TEMPSAS.ITEMACPSA_99 data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.03 seconds
      cpu time            0.01 seconds


12258
12259  PROC IMPORT DATAFILE= "&drive\ACPSA_Items\Item_Partials\&prodyr\ACPSA_Partial_Item_Ratio_Interpolation.xlsx"
SYMBOLGEN:  Macro variable DRIVE resolves to j:\IEA Products\ACPSA
SYMBOLGEN:  Macro variable PRODYR resolves to 2019
12260              OUT= tempsas.itemACPSA_Interp
12261              DBMS=xlsx
12262              replace;
12263              SHEET="Item_Partial_List_Interp";
12264              GETNAMES=YES;
12265
12266  run;

NOTE: The import data set has 58 observations and 27 variables.
NOTE: TEMPSAS.ITEMACPSA_INTERP data set was successfully created.
NOTE: PROCEDURE IMPORT used (Total process time):
      real time           0.04 seconds
      cpu time            0.03 seconds


12267  *********************************************************************************************************;
12268
12269  %macro prep_series;
12270      %do ioyear = &b_ioYear %to &e_ioyear;
12271
12272  **************************************************************************************************************;
12273  *******************************  Item concordance weight update **********************************************;
12274  /*
12275
12276  This section updates the weights in the item concordance for the item partials.  Some of the itemCodes have weights
12277  that change from year to year.  To incorporate those into the ACPSA, the item concordance needs to be changed for
12278  each processing year.  The weights that don't change will remain as they were but the ones that do change will
12279  be updated.
12280
12281  */
12282  ***************************************************************************************************************;
12283
12284
12285  data tempsas.current_item_concordance;
12286  set concord.&acpsaitemcc;
12287
12288  proc sort data=tempsas.current_item_concordance out=tempsas.current_item_concordance_sort;
12289  by itemCode itemACPSA;
12290  run;
12291
12292  data tempsas.itemACPSA_partial_combine_0;
12293  length itemCode $ 20 itemDescr $ 300 itemACPSA $ 9 itemACPSADescr $ 90;
12294  set tempsas.itemACPSA_23 tempsas.itemACPSA_3X tempsas.itemACPSA_51 tempsas.itemACPSA_54 tempsas.itemACPSA_56
12294! tempsas.itemACPSA_61 tempsas.itemACPSA_71 tempsas.itemACPSA_81 tempsas.itemACPSA_99;
12295
12296  where upcase(isInterp) ne 'Y';
12297
12298  format itemCode $20. itemDescr $300. itemACPSA $9. itemACPSADescr $90.;
12299
12300  data tempsas.itemACPSA_partial_combine;
12301  set tempsas.itemACPSA_partial_combine_0 tempsas.itemACPSA_Interp;
12302
12303  proc sort data=tempsas.itemACPSA_partial_combine out=tempsas.itemACPSA_partial_combine_sort;
12304  by itemCode itemACPSA;
12305
12306  proc summary data=tempsas.current_item_concordance_sort;
12307  by itemCode;
12308  id itemDescr;
12309  var weight;
12310  output out=tempsas.current_item_concordance_sum(drop=_type_) sum= ;
12311  run;
12312
12313  /* itemCode weight check */
12314  proc summary data=tempsas.itemACPSA_partial_combine_sort;
12315  by itemCode;
12316  id itemDescr;
12317  var y1997 - y2017;
12318  output out=tempsas.itemACPSA_partial_summary(drop=_type_) sum= ;
12319  run;
12320
12321  data    tempsas.partial_item_ACPSA
12322          tempsas.partial_all_other
12323          tempsas.no_update (keep=itemCode_id itemCode itemDescr partial weight itemACPSA itemACPSADescr);
12324  merge tempsas.current_item_concordance_sort(in=a) tempsas.itemACPSA_partial_combine_sort (in=b);
12325  by itemCode;
12326
12327  if b=1 and itemACPSA ne 'item99' then output tempsas.partial_item_ACPSA;
12328  else if b=1 and itemACPSA = 'item99' then output tempsas.partial_all_other;
12329  else output tempsas.no_update;
12330
12331  run;
12332
12333  data tempsas.partial_item_ACPSA_format;
12334  set tempsas.partial_item_ACPSA;
12335
12336  weight = y&ioyear;
12337
12338  keep itemCode_id itemCode itemDescr partial weight itemACPSA itemACPSADescr;
12339  run;
12340
12341  proc sort data=tempsas.partial_item_ACPSA_format out=tempsas.partial_item_ACPSA_sort;
12342  by itemCode_id itemCode;
12343
12344  proc summary data=tempsas.partial_item_ACPSA_sort;
12345  by itemCode_id itemCode;
12346  id itemDescr;
12347  var weight;
12348  output out=tempsas.partial_item_ACPSA_summary(drop=_type_) sum=;
12349  run;
12350
12351  data tempsas.partial_ACPSA_sum1
12352      tempsas.partial_ACPSA_not1;
12353  set tempsas.partial_item_ACPSA_summary;
12354
12355  if weight < 0.999 then output tempsas.partial_ACPSA_not1;
12356  else output tempsas.partial_ACPSA_sum1;
12357
12358  run;
12359
12360  proc sort data=tempsas.partial_ACPSA_not1 out=tempsas.partial_ACPSA_not1_sort;
12361  by itemCode_id itemCode;
12362
12363  data tempsas.partial_not1_adj;
12364  merge tempsas.partial_ACPSA_not1_sort(in=a rename=(weight=total_weight)) tempsas.partial_item_ACPSA_sort;
12365  by itemCode_id;
12366
12367  if a=1;
12368
12369  weight = 1 - total_weight;
12370  itemACPSA = 'item99';
12371  itemACPSADescr = 'All Other Commodities';
12372
12373  drop _freq_ total_weight;
12374
12375  run;
12376
12377  proc sort data=tempsas.partial_not1_adj out=tempsas.partial_not1_adj_sort;
12378  by itemCode_id itemCode itemDescr partial weight itemACPSA itemACPSADescr;
12379
12380  proc summary data=tempsas.partial_not1_adj_sort;
12381  by itemCode_id itemCode itemDescr partial weight itemACPSA itemACPSADescr;
12382  output out=tempsas.partial_not1_correction(drop=_type_ _freq_);
12383  run;
12384
12385  data tempsas.partial_ACPSA_remerge;
12386  set tempsas.partial_item_ACPSA_format tempsas.partial_not1_correction;
12387  run;
12388
12389  *****************   Checks the sum of partial ACPSA items.  Weights should sum to 1.    **************;
12390  data tempsas.all_partials_remerged;
12391  set tempsas.partial_ACPSA_remerge;
12392
12393  proc sort data=tempsas.all_partials_remerged out=tempsas.all_partials_remerged_sort;
12394  by itemCode;
12395
12396  proc summary data=tempsas.all_partials_remerged_sort;
12397  by itemCode;
12398  id itemDescr;
12399  var weight;
12400  output out=tempsas.partial_ACPSA_sum_check(drop=_type_ _freq_) sum= ;
12401  run;  /*sbo 9.2.2016 - Check works for 2012  */
12402
12403  proc print data=tempsas.partial_ACPSA_sum_check noobs;
12404  title3 "Partial ACPSA item weight check, &ioYear";
12405  TITLE4 "%sysfunc(today(),weekdate.), %sysfunc(time(),time8.)";
12406  var itemCode weight;
12407  run;
12408  ****************************************************************************;
12409
12410  data tempsas.new_item_conc;
12411  set tempsas.partial_ACPSA_remerge tempsas.no_update;
12412
12413  itemACPSADescr = propcase(itemACPSADescr);
12414
12415  proc sort data=tempsas.new_item_conc out=tempsas.new_item_conc_sort;
12416  by itemCode itemACPSA;
12417
12418  *******************************************************************************************;
12419  /* Check on new concordance to make sure weights sum to 1  */
12420  proc summary data = tempsas.new_item_conc_sort;
12421  by itemCode;
12422  id itemDescr;
12423  var weight;
12424  output out=tempsas.new_item_conc_summary(drop=_type_ _freq_) sum= ;
12425  run;
12426
12427  data tempsas.good_conc
12428      tempsas.bad_conc;
12429  set tempsas.new_item_conc_summary;
12430
12431  if weight ne 1 then output tempsas.bad_conc;
12432  else output tempsas.good_conc;
12433
12434  run;
12435
12436  ******************************************************************************************
12437  *****************************************************************************************************
12438  ACPSA item concordance
12439  *****************************************************************************************************;
12440
12441  data tempsas.item_conc;
12442  set tempsas.new_item_conc_sort;
12443
12444  itemACPSADescr = propcase(itemACPSADescr);
12445
12446
12447  /*
12448  The following program creates three tables for used in calculating Laspeyres and Pasche quantity and price
12449  indices.  The methodology follows that of a program written by Gabriel Medeiros to calculate prices for annual
12450  IO.
12451  */
12452
12453  proc sql;
12454
12455  connect to odbc as IEtest17
12456     (datasrc="IEtest17");
12457
12458  create table tempsas.temp_PI_afor1 as
12459
12460     select *
12461     from connection to IEtest17
12462
12463  (select riv.itmCode_id as item_id
12464      , riv.itmCode as itemCode
12465      , riv.period as ioYear
12466      , riv.basePeriod as basingYear
12467      , riv.pRelGO as PI
12468      , oiv.val as basicVal
12469  from rel_itmView riv
12470      join occ.itmView oiv
12471          on riv.itmCode_id = oiv.itmCode_id
12472              and riv.datasetPeriod_id = oiv.datasetPeriod_id
12473              and riv.dataSet_id = oiv.dataSet_id
12474  where riv.datasetName = 'annual17'
12475      and riv.valType = 'DOM'
12476      and oiv.period = '1998'
12477      and riv.period = '1998'
12478  order by riv.itmCode, riv.period
12479  );
12480
12481  disconnect from IETest17;
12482
12483  proc sql;
12484  create table tempsas.temp_PI_&ioYear as
12485
12486  select tab.itmCode_id as item_id label="item_id"
12487      , tab.itmCode as itemCode label="itemCode"
12488      , &ioYear as ioYear label="ioYear"
12489      , tab.basePeriod as basingYear label="basingYear"
12490      , tab.pRelGO as PI label="PI"
12491      , tab.basival as basicVal
12492      , ic.itemACPSA
12493      , ic.itemACPSADescr
12494  from tempsas.temp_PI_afor1 tab
12495      join tempsas.item_conc ic
12496      on tab.itemCode = ic.itemCode
12497  /*where tab.datasetName = &dsName
12498      and tab.valType = 'DOM'
12499      and oiv.period = "&ioYear"
12500      and tab.period = &ioYear.*/
12501  ;
12502  quit;
12503
12504
12505  %end;
12506  %mend prep_series;
12507
12508  %prep_series
SYMBOLGEN:  Macro variable B_IOYEAR resolves to 1998
SYMBOLGEN:  Macro variable E_IOYEAR resolves to 1998
MPRINT(PREP_SERIES):
**************************************************************************************************************;
MPRINT(PREP_SERIES):   ******************************* Item concordance weight update
**********************************************;
MPRINT(PREP_SERIES):
***************************************************************************************************************;
MPRINT(PREP_SERIES):   data tempsas.current_item_concordance;
SYMBOLGEN:  Macro variable ACPSAITEMCC resolves to acpsa_item_concord_2012naics
MPRINT(PREP_SERIES):   set concord.acpsa_item_concord_2012naics;

NOTE: There were 5318 observations read from the data set CONCORD.ACPSA_ITEM_CONCORD_2012NAICS.
NOTE: The data set TEMPSAS.CURRENT_ITEM_CONCORDANCE has 5318 observations and 7 variables.
NOTE: DATA statement used (Total process time):
      real time           0.10 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   proc sort data=tempsas.current_item_concordance out=tempsas.current_item_concordance_sort;
MPRINT(PREP_SERIES):   by itemCode itemACPSA;
MPRINT(PREP_SERIES):   run;

NOTE: There were 5318 observations read from the data set TEMPSAS.CURRENT_ITEM_CONCORDANCE.
NOTE: The data set TEMPSAS.CURRENT_ITEM_CONCORDANCE_SORT has 5318 observations and 7 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.03 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   data tempsas.itemACPSA_partial_combine_0;
MPRINT(PREP_SERIES):   length itemCode $ 20 itemDescr $ 300 itemACPSA $ 9 itemACPSADescr $ 90;
MPRINT(PREP_SERIES):   set tempsas.itemACPSA_23 tempsas.itemACPSA_3X tempsas.itemACPSA_51 tempsas.itemACPSA_54
tempsas.itemACPSA_56 tempsas.itemACPSA_61 tempsas.itemACPSA_71 tempsas.itemACPSA_81 tempsas.itemACPSA_99;
MPRINT(PREP_SERIES):   where upcase(isInterp) ne 'Y';
MPRINT(PREP_SERIES):   format itemCode $20. itemDescr $300. itemACPSA $9. itemACPSADescr $90.;

NOTE: There were 9 observations read from the data set TEMPSAS.ITEMACPSA_23.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: There were 35 observations read from the data set TEMPSAS.ITEMACPSA_3X.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: There were 35 observations read from the data set TEMPSAS.ITEMACPSA_51.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: There were 12 observations read from the data set TEMPSAS.ITEMACPSA_54.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: There were 1 observations read from the data set TEMPSAS.ITEMACPSA_56.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: There were 9 observations read from the data set TEMPSAS.ITEMACPSA_61.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: There were 10 observations read from the data set TEMPSAS.ITEMACPSA_71.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: There were 6 observations read from the data set TEMPSAS.ITEMACPSA_81.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: There were 1 observations read from the data set TEMPSAS.ITEMACPSA_99.
      WHERE UPCASE(isInterp) not = 'Y';
NOTE: The data set TEMPSAS.ITEMACPSA_PARTIAL_COMBINE_0 has 118 observations and 28 variables.
NOTE: DATA statement used (Total process time):
      real time           0.02 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   data tempsas.itemACPSA_partial_combine;
MPRINT(PREP_SERIES):   set tempsas.itemACPSA_partial_combine_0 tempsas.itemACPSA_Interp;
NOTE: There were 118 observations read from the data set TEMPSAS.ITEMACPSA_PARTIAL_COMBINE_0.
NOTE: There were 58 observations read from the data set TEMPSAS.ITEMACPSA_INTERP.
NOTE: The data set TEMPSAS.ITEMACPSA_PARTIAL_COMBINE has 176 observations and 28 variables.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   proc sort data=tempsas.itemACPSA_partial_combine out=tempsas.itemACPSA_partial_combine_sort;
MPRINT(PREP_SERIES):   by itemCode itemACPSA;
NOTE: There were 176 observations read from the data set TEMPSAS.ITEMACPSA_PARTIAL_COMBINE.
NOTE: The data set TEMPSAS.ITEMACPSA_PARTIAL_COMBINE_SORT has 176 observations and 28 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   proc summary data=tempsas.current_item_concordance_sort;
MPRINT(PREP_SERIES):   by itemCode;
MPRINT(PREP_SERIES):   id itemDescr;
MPRINT(PREP_SERIES):   var weight;
MPRINT(PREP_SERIES):   output out=tempsas.current_item_concordance_sum(drop=_type_) sum= ;
MPRINT(PREP_SERIES):   run;

NOTE: There were 5318 observations read from the data set TEMPSAS.CURRENT_ITEM_CONCORDANCE_SORT.
NOTE: The data set TEMPSAS.CURRENT_ITEM_CONCORDANCE_SUM has 4708 observations and 4 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
      real time           0.05 seconds
      cpu time            0.04 seconds


MPRINT(PREP_SERIES):   proc summary data=tempsas.itemACPSA_partial_combine_sort;
MPRINT(PREP_SERIES):   by itemCode;
MPRINT(PREP_SERIES):   id itemDescr;
MPRINT(PREP_SERIES):   var y1997 - y2017;
MPRINT(PREP_SERIES):   output out=tempsas.itemACPSA_partial_summary(drop=_type_) sum= ;
MPRINT(PREP_SERIES):   run;

NOTE: There were 176 observations read from the data set TEMPSAS.ITEMACPSA_PARTIAL_COMBINE_SORT.
NOTE: The data set TEMPSAS.ITEMACPSA_PARTIAL_SUMMARY has 120 observations and 24 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
      real time           0.02 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   data tempsas.partial_item_ACPSA tempsas.partial_all_other tempsas.no_update (keep=itemCode_id itemCode
itemDescr partial weight itemACPSA itemACPSADescr);
MPRINT(PREP_SERIES):   merge tempsas.current_item_concordance_sort(in=a) tempsas.itemACPSA_partial_combine_sort (in=b);
MPRINT(PREP_SERIES):   by itemCode;
MPRINT(PREP_SERIES):   if b=1 and itemACPSA ne 'item99' then output tempsas.partial_item_ACPSA;
MPRINT(PREP_SERIES):   else if b=1 and itemACPSA = 'item99' then output tempsas.partial_all_other;
MPRINT(PREP_SERIES):   else output tempsas.no_update;
MPRINT(PREP_SERIES):   run;

WARNING: Multiple lengths were specified for the variable itemDescr by input data set(s). This may cause truncation of data.
WARNING: Multiple lengths were specified for the variable itemACPSA by input data set(s). This may cause truncation of data.
WARNING: Multiple lengths were specified for the variable itemACPSADescr by input data set(s). This may cause truncation of data.
NOTE: MERGE statement has more than one data set with repeats of BY values.
NOTE: There were 5318 observations read from the data set TEMPSAS.CURRENT_ITEM_CONCORDANCE_SORT.
NOTE: There were 176 observations read from the data set TEMPSAS.ITEMACPSA_PARTIAL_COMBINE_SORT.
NOTE: The data set TEMPSAS.PARTIAL_ITEM_ACPSA has 177 observations and 29 variables.
NOTE: The data set TEMPSAS.PARTIAL_ALL_OTHER has 115 observations and 29 variables.
NOTE: The data set TEMPSAS.NO_UPDATE has 5027 observations and 7 variables.
NOTE: DATA statement used (Total process time):
      real time           0.05 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   data tempsas.partial_item_ACPSA_format;
MPRINT(PREP_SERIES):   set tempsas.partial_item_ACPSA;
SYMBOLGEN:  Macro variable IOYEAR resolves to 1998
MPRINT(PREP_SERIES):   weight = y1998;
MPRINT(PREP_SERIES):   keep itemCode_id itemCode itemDescr partial weight itemACPSA itemACPSADescr;
MPRINT(PREP_SERIES):   run;

NOTE: There were 177 observations read from the data set TEMPSAS.PARTIAL_ITEM_ACPSA.
NOTE: The data set TEMPSAS.PARTIAL_ITEM_ACPSA_FORMAT has 177 observations and 7 variables.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.00 seconds


MPRINT(PREP_SERIES):   proc sort data=tempsas.partial_item_ACPSA_format out=tempsas.partial_item_ACPSA_sort;
MPRINT(PREP_SERIES):   by itemCode_id itemCode;

NOTE: There were 177 observations read from the data set TEMPSAS.PARTIAL_ITEM_ACPSA_FORMAT.
NOTE: The data set TEMPSAS.PARTIAL_ITEM_ACPSA_SORT has 177 observations and 7 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.00 seconds


MPRINT(PREP_SERIES):   proc summary data=tempsas.partial_item_ACPSA_sort;
MPRINT(PREP_SERIES):   by itemCode_id itemCode;
MPRINT(PREP_SERIES):   id itemDescr;
MPRINT(PREP_SERIES):   var weight;
MPRINT(PREP_SERIES):   output out=tempsas.partial_item_ACPSA_summary(drop=_type_) sum=;
MPRINT(PREP_SERIES):   run;

NOTE: There were 177 observations read from the data set TEMPSAS.PARTIAL_ITEM_ACPSA_SORT.
NOTE: The data set TEMPSAS.PARTIAL_ITEM_ACPSA_SUMMARY has 121 observations and 5 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
      real time           0.03 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   data tempsas.partial_ACPSA_sum1 tempsas.partial_ACPSA_not1;
MPRINT(PREP_SERIES):   set tempsas.partial_item_ACPSA_summary;
MPRINT(PREP_SERIES):   if weight < 0.999 then output tempsas.partial_ACPSA_not1;
MPRINT(PREP_SERIES):   else output tempsas.partial_ACPSA_sum1;
MPRINT(PREP_SERIES):   run;

NOTE: There were 121 observations read from the data set TEMPSAS.PARTIAL_ITEM_ACPSA_SUMMARY.
NOTE: The data set TEMPSAS.PARTIAL_ACPSA_SUM1 has 9 observations and 5 variables.
NOTE: The data set TEMPSAS.PARTIAL_ACPSA_NOT1 has 112 observations and 5 variables.
NOTE: DATA statement used (Total process time):
      real time           0.02 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   proc sort data=tempsas.partial_ACPSA_not1 out=tempsas.partial_ACPSA_not1_sort;
MPRINT(PREP_SERIES):   by itemCode_id itemCode;
NOTE: There were 112 observations read from the data set TEMPSAS.PARTIAL_ACPSA_NOT1.
NOTE: The data set TEMPSAS.PARTIAL_ACPSA_NOT1_SORT has 112 observations and 5 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   data tempsas.partial_not1_adj;
MPRINT(PREP_SERIES):   merge tempsas.partial_ACPSA_not1_sort(in=a rename=(weight=total_weight)) tempsas.partial_item_ACPSA_sort;
MPRINT(PREP_SERIES):   by itemCode_id;
MPRINT(PREP_SERIES):   if a=1;
MPRINT(PREP_SERIES):   weight = 1 - total_weight;
MPRINT(PREP_SERIES):   itemACPSA = 'item99';
MPRINT(PREP_SERIES):   itemACPSADescr = 'All Other Commodities';
MPRINT(PREP_SERIES):   drop _freq_ total_weight;
MPRINT(PREP_SERIES):   run;

NOTE: There were 112 observations read from the data set TEMPSAS.PARTIAL_ACPSA_NOT1_SORT.
NOTE: There were 177 observations read from the data set TEMPSAS.PARTIAL_ITEM_ACPSA_SORT.
NOTE: The data set TEMPSAS.PARTIAL_NOT1_ADJ has 114 observations and 7 variables.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   proc sort data=tempsas.partial_not1_adj out=tempsas.partial_not1_adj_sort;
MPRINT(PREP_SERIES):   by itemCode_id itemCode itemDescr partial weight itemACPSA itemACPSADescr;

NOTE: There were 114 observations read from the data set TEMPSAS.PARTIAL_NOT1_ADJ.
NOTE: The data set TEMPSAS.PARTIAL_NOT1_ADJ_SORT has 114 observations and 7 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   proc summary data=tempsas.partial_not1_adj_sort;
MPRINT(PREP_SERIES):   by itemCode_id itemCode itemDescr partial weight itemACPSA itemACPSADescr;
MPRINT(PREP_SERIES):   output out=tempsas.partial_not1_correction(drop=_type_ _freq_);
MPRINT(PREP_SERIES):   run;

NOTE: There were 114 observations read from the data set TEMPSAS.PARTIAL_NOT1_ADJ_SORT.
NOTE: The data set TEMPSAS.PARTIAL_NOT1_CORRECTION has 112 observations and 7 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
      real time           0.02 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   data tempsas.partial_ACPSA_remerge;
MPRINT(PREP_SERIES):   set tempsas.partial_item_ACPSA_format tempsas.partial_not1_correction;
MPRINT(PREP_SERIES):   run;

NOTE: There were 177 observations read from the data set TEMPSAS.PARTIAL_ITEM_ACPSA_FORMAT.
NOTE: There were 112 observations read from the data set TEMPSAS.PARTIAL_NOT1_CORRECTION.
NOTE: The data set TEMPSAS.PARTIAL_ACPSA_REMERGE has 289 observations and 7 variables.
NOTE: DATA statement used (Total process time):
      real time           0.02 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   ***************** Checks the sum of partial ACPSA items. Weights should sum to 1. **************;
MPRINT(PREP_SERIES):   data tempsas.all_partials_remerged;
MPRINT(PREP_SERIES):   set tempsas.partial_ACPSA_remerge;

NOTE: There were 289 observations read from the data set TEMPSAS.PARTIAL_ACPSA_REMERGE.
NOTE: The data set TEMPSAS.ALL_PARTIALS_REMERGED has 289 observations and 7 variables.
NOTE: DATA statement used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   proc sort data=tempsas.all_partials_remerged out=tempsas.all_partials_remerged_sort;
MPRINT(PREP_SERIES):   by itemCode;

NOTE: There were 289 observations read from the data set TEMPSAS.ALL_PARTIALS_REMERGED.
NOTE: The data set TEMPSAS.ALL_PARTIALS_REMERGED_SORT has 289 observations and 7 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.01 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   proc summary data=tempsas.all_partials_remerged_sort;
MPRINT(PREP_SERIES):   by itemCode;
MPRINT(PREP_SERIES):   id itemDescr;
MPRINT(PREP_SERIES):   var weight;
MPRINT(PREP_SERIES):   output out=tempsas.partial_ACPSA_sum_check(drop=_type_ _freq_) sum= ;
MPRINT(PREP_SERIES):   run;

NOTE: There were 289 observations read from the data set TEMPSAS.ALL_PARTIALS_REMERGED_SORT.
NOTE: The data set TEMPSAS.PARTIAL_ACPSA_SUM_CHECK has 120 observations and 3 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
      real time           0.03 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   proc print data=tempsas.partial_ACPSA_sum_check noobs;
SYMBOLGEN:  Macro variable IOYEAR resolves to 1998
MPRINT(PREP_SERIES):   title3 "Partial ACPSA item weight check, 1998";
MPRINT(PREP_SERIES):   TITLE4 "     Tuesday, August 27, 2019, 14:20:49";
MPRINT(PREP_SERIES):   var itemCode weight;
MPRINT(PREP_SERIES):   run;

NOTE: There were 120 observations read from the data set TEMPSAS.PARTIAL_ACPSA_SUM_CHECK.
NOTE: PROCEDURE PRINT used (Total process time):
      real time           0.02 seconds
      cpu time            0.00 seconds


MPRINT(PREP_SERIES):   ****************************************************************************;
MPRINT(PREP_SERIES):   data tempsas.new_item_conc;
MPRINT(PREP_SERIES):   set tempsas.partial_ACPSA_remerge tempsas.no_update;
MPRINT(PREP_SERIES):   itemACPSADescr = propcase(itemACPSADescr);

NOTE: There were 289 observations read from the data set TEMPSAS.PARTIAL_ACPSA_REMERGE.
NOTE: There were 5027 observations read from the data set TEMPSAS.NO_UPDATE.
NOTE: The data set TEMPSAS.NEW_ITEM_CONC has 5316 observations and 7 variables.
NOTE: DATA statement used (Total process time):
      real time           0.02 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   proc sort data=tempsas.new_item_conc out=tempsas.new_item_conc_sort;
MPRINT(PREP_SERIES):   by itemCode itemACPSA;
MPRINT(PREP_SERIES):   *******************************************************************************************;

NOTE: There were 5316 observations read from the data set TEMPSAS.NEW_ITEM_CONC.
NOTE: The data set TEMPSAS.NEW_ITEM_CONC_SORT has 5316 observations and 7 variables.
NOTE: PROCEDURE SORT used (Total process time):
      real time           0.03 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   proc summary data = tempsas.new_item_conc_sort;
MPRINT(PREP_SERIES):   by itemCode;
MPRINT(PREP_SERIES):   id itemDescr;
MPRINT(PREP_SERIES):   var weight;
MPRINT(PREP_SERIES):   output out=tempsas.new_item_conc_summary(drop=_type_ _freq_) sum= ;
MPRINT(PREP_SERIES):   run;

NOTE: There were 5316 observations read from the data set TEMPSAS.NEW_ITEM_CONC_SORT.
NOTE: The data set TEMPSAS.NEW_ITEM_CONC_SUMMARY has 4709 observations and 3 variables.
NOTE: PROCEDURE SUMMARY used (Total process time):
      real time           0.05 seconds
      cpu time            0.06 seconds


MPRINT(PREP_SERIES):   data tempsas.good_conc tempsas.bad_conc;
MPRINT(PREP_SERIES):   set tempsas.new_item_conc_summary;
MPRINT(PREP_SERIES):   if weight ne 1 then output tempsas.bad_conc;
MPRINT(PREP_SERIES):   else output tempsas.good_conc;
MPRINT(PREP_SERIES):   run;

NOTE: There were 4709 observations read from the data set TEMPSAS.NEW_ITEM_CONC_SUMMARY.
NOTE: The data set TEMPSAS.GOOD_CONC has 4336 observations and 3 variables.
NOTE: The data set TEMPSAS.BAD_CONC has 373 observations and 3 variables.
NOTE: DATA statement used (Total process time):
      real time           0.03 seconds
      cpu time            0.01 seconds


MPRINT(PREP_SERIES):   ******************************************************************************************
***************************************************************************************************** ACPSA item concordance
*****************************************************************************************************;
MPRINT(PREP_SERIES):   data tempsas.item_conc;
MPRINT(PREP_SERIES):   set tempsas.new_item_conc_sort;
MPRINT(PREP_SERIES):   itemACPSADescr = propcase(itemACPSADescr);

NOTE: There were 5316 observations read from the data set TEMPSAS.NEW_ITEM_CONC_SORT.
NOTE: The data set TEMPSAS.ITEM_CONC has 5316 observations and 7 variables.
NOTE: DATA statement used (Total process time):
      real time           0.02 seconds
      cpu time            0.03 seconds


MPRINT(PREP_SERIES):   proc sql;
MPRINT(PREP_SERIES):   connect to odbc as IEtest17 (datasrc="IEtest17");
MPRINT(PREP_SERIES):   create table tempsas.temp_PI_afor1 as select * from connection to IEtest17 (select riv.itmCode_id as
item_id , riv.itmCode as itemCode , riv.period as ioYear , riv.basePeriod as basingYear , riv.pRelGO as PI , oiv.val as basicVal
from rel_itmView riv join occ.itmView oiv on riv.itmCode_id = oiv.itmCode_id and riv.datasetPeriod_id = oiv.datasetPeriod_id and
riv.dataSet_id = oiv.dataSet_id where riv.datasetName = 'annual17' and riv.valType = 'DOM' and oiv.period = '1998' and riv.period
= '1998' order by riv.itmCode, riv.period );
NOTE: Table TEMPSAS.TEMP_PI_AFOR1 created, with 5505 rows and 6 columns.

MPRINT(PREP_SERIES):   disconnect from IETest17;
NOTE: PROCEDURE SQL used (Total process time):
      real time           0.75 seconds
      cpu time            0.04 seconds


MPRINT(PREP_SERIES):   proc sql;
SYMBOLGEN:  Macro variable IOYEAR resolves to 1998
SYMBOLGEN:  Macro variable IOYEAR resolves to 1998
MPRINT(PREP_SERIES):   create table tempsas.temp_PI_1998 as select tab.itmCode_id as item_id label="item_id" , tab.itmCode as
itemCode label="itemCode" , 1998 as ioYear label="ioYear" , tab.basePeriod as basingYear label="basingYear" , tab.pRelGO as PI
label="PI" , tab.basival as basicVal , ic.itemACPSA , ic.itemACPSADescr from tempsas.temp_PI_afor1 tab join tempsas.item_conc ic
on tab.itemCode = ic.itemCode ;
ERROR: Column itmCode_id could not be found in the table/view identified with the correlation name TAB.
ERROR: Column itmCode could not be found in the table/view identified with the correlation name TAB.
ERROR: Column basePeriod could not be found in the table/view identified with the correlation name TAB.
ERROR: Column pRelGO could not be found in the table/view identified with the correlation name TAB.
ERROR: Column basival could not be found in the table/view identified with the correlation name TAB.
MPRINT(PREP_SERIES):   quit;
NOTE: The SAS System stopped processing this step because of errors.
NOTE: PROCEDURE SQL used (Total process time):
      real time           0.00 seconds
      cpu time            0.01 seconds
topic Re: ERROR: Column itmCode_id could not be found in the table/view identified with the correlation na in SAS Programming

ERROR: Column itmCode_id could not be found in the table/view identified with the correlation name

Re: ERROR: Column itmCode_id could not be found in the table/view identified with the correlation na

Re: ERROR: Column itmCode_id could not be found in the table/view identified with the correlation na
