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France · ‎01-16-2019

hello EJAA, I am trying to match two datasets by company name now. could you please share your code with me ? thanks in advacne best regards, France

France · ‎01-16-2019

dear all, I have imported an .XLSX file into SAS by the following code, proc import datafile = 'C:\Users\70660\Desktop\Datastream_GB.xlsx' OUT=sa_step5.DATASTREAM_GB1 DBMS=XLSX replace; Sheet='Total1'; RANGE='A1: I16458'; GETNAMES=YES; run; But I confuse what should I do if I expect to define the FORMAT of the variable during the proc import step. could you please give me some suggestions? thanks in advance.

France · ‎01-15-2019

dear all, why some of the observation cannot be matched? I am trying to clean the company name and merge two excel based on the cleaned company name. I process the excel Step5.DATASTREAM_GB2 by following codes, data Step3.Datastream_gb_export_2nd; set Step5.Datastream_gb2; COMPANY_NAME = prxChange("s/,?\s*(incorporated|incorporation|INCORP|COMPANY|inco|inc|corporation|corp|limited|ltd|plc|ag|s\.a\.|sa)\.?\s*$//io",1,COMPANY_NAME); COMPANY_NAME_1 = prxChange("s/,?\s*(incorporated|incorporation|INCORP|COMPANY|inco|inc|corporation|corp|limited|ltd|plc|ag|s\.a\.|sa)\.?\s*$//io",1,COMPANY_NAME_1); COMPANY_NAME___SHORT = prxChange("s/,?\s*(incorporated|incorporation|INCORP|COMPANY|inco|inc|corporation|corp|limited|ltd|plc|ag|s\.a\.|sa)\.?\s*$//io",1,COMPANY_NAME___SHORT); PREVIOUS_NAME = prxChange("s/,?\s*(incorporated|incorporation|INCORP|COMPANY|inco|inc|corporation|corp|limited|ltd|plc|ag|s\.a\.|sa)\.?\s*$//io",1,PREVIOUS_NAME); run; data Step3.Datastream_gb_export_2nd; set Step3.Datastream_gb_export_2nd; if GEOGRAPHIC_DESCR_='NETHERLANDS' then do; COMPANY_NAME = prxchange('s/(NV|N\.V\.)$//',1,trim(COMPANY_NAME )); COMPANY_NAME_1 = prxchange('s/(NV|N\.V\.)$//',1,trim(COMPANY_NAME_1)); COMPANY_NAME___SHORT = prxchange('s/(NV|N\.V\.)$//',1,trim(COMPANY_NAME___SHORT)); PREVIOUS_NAME = prxchange('s/(NV|N\.V\.)$//',1,trim(PREVIOUS_NAME)); end; if GEOGRAPHIC_DESCR_='SWEDEN' then do; COMPANY_NAME = prxchange('s/(AB)$//',1,trim(COMPANY_NAME )); COMPANY_NAME_1 = prxchange('s/(AB)$//',1,trim(COMPANY_NAME_1)); COMPANY_NAME___SHORT = prxchange('s/(AB)$//',1,trim(COMPANY_NAME___SHORT)); PREVIOUS_NAME = prxchange('s/(AB)$//',1,trim(PREVIOUS_NAME)); end; if GEOGRAPHIC_DESCR_='FINLAND' then do; COMPANY_NAME = prxchange('s/(AB|OYJ)$//',1,trim(COMPANY_NAME )); COMPANY_NAME_1 = prxchange('s/(AB|OYJ)$//',1,trim(COMPANY_NAME_1)); COMPANY_NAME___SHORT = prxchange('s/(AB|OYJ)$//',1,trim(COMPANY_NAME___SHORT)); PREVIOUS_NAME = prxchange('s/(AB|OYJ)$//',1,trim(PREVIOUS_NAME)); end; if GEOGRAPHIC_DESCR_='ITALY' then do; COMPANY_NAME = prxchange('s/(SPA|S\.P\.A\.)$//',1,trim(COMPANY_NAME )); COMPANY_NAME_1 = prxchange('s/(SPA|S\.P\.A\.)$//',1,trim(COMPANY_NAME_1)); COMPANY_NAME___SHORT = prxchange('s/(SPA|S\.P\.A\.)$//',1,trim(COMPANY_NAME___SHORT)); PREVIOUS_NAME = prxchange('s/(SPA|S\.P\.A\.)$//',1,trim(PREVIOUS_NAME)); end; if GEOGRAPHIC_DESCR_='NORWAY' then do; COMPANY_NAME = prxchange('s/(ASA)$//',1,trim(COMPANY_NAME )); COMPANY_NAME_1 = prxchange('s/(ASA)$//',1,trim(COMPANY_NAME_1)); COMPANY_NAME___SHORT = prxchange('s/(ASA)$//',1,trim(COMPANY_NAME___SHORT)); PREVIOUS_NAME = prxchange('s/(ASA)$//',1,trim(PREVIOUS_NAME)); end; run; then match the processed Step5.DATASTREAM_GB2 (i.e.,Step3.Datastream_gb_export_2nd) with Step5.PATSTAT_GB2 by following codes, data Step3.Datastream_gb_export_2nd; set Step3.Datastream_gb_export_2nd; run; data Step3.Datastream_gb2; set Step2.Datastream_gb_export_2nd; rename name=psn_name; run; proc sort data= Step3.Datastream_gb2; by psn_name; run; proc sort data= Step5.PATSTAT_GB2; by psn_name; run; data STEP6.Datastream_Patstat1(keep=psn_name Type) step4.Patstat_gb_simple2 step3.Datastream_gb3; merge Step5.PATSTAT_GB2 (in=ina) Step3.Datastream_gb2 (in=inb) ; by psn_name; if ina and inb then output STEP6.Datastream_Patstat1; else if ina then output step4.Patstat_gb_simple2; else if inb then output step3.Datastream_gb3; run; data step3.Datastream_gb3; set step3.Datastream_gb3; drop psn_name; rename COMPANY_NAME=psn_name; run; proc sort data=step3.Datastream_gb3; by psn_name; run; proc sort data=step4.Patstat_gb_simple2; by psn_name; run; data STEP6.Datastream_Patstat2(keep=psn_name Type) step4.Patstat_gb_simple3 step3.Datastream_gb4; merge step4.Patstat_gb_simple2 (in=ina) step3.Datastream_gb3 (in=inb) ; by psn_name; if ina and inb then output STEP6.Datastream_Patstat2; else if ina then output step4.Patstat_gb_simple3; else if inb then output step3.Datastream_gb4; run; data step3.Datastream_gb4; set step3.Datastream_gb4; drop psn_name; rename COMPANY_NAME_1=psn_name; run; proc sort data=step3.Datastream_gb4; by psn_name; run; proc sort data=step4.Patstat_gb_simple3; by psn_name; run; data STEP6.Datastream_Patstat3(keep=psn_name Type) step4.Patstat_gb_simple4 step3.Datastream_gb5; merge step4.Patstat_gb_simple3 (in=ina) step3.Datastream_gb4 (in=inb) ; by psn_name; if ina and inb then output STEP6.Datastream_Patstat3; else if ina then output step4.Patstat_gb_simple4; else if inb then output step3.Datastream_gb5; run; data step3.Datastream_gb5; set step3.Datastream_gb5; drop psn_name; rename COMPANY_NAME___SHORT=psn_name; run; proc sort data=step3.Datastream_gb5; by psn_name; run; proc sort data=step4.Patstat_gb_simple4; by psn_name; run; data STEP6.Datastream_Patstat4(keep=psn_name Type) step4.Patstat_gb_simple5 step3.Datastream_gb6; merge step4.Patstat_gb_simple4 (in=ina) step3.Datastream_gb5 (in=inb) ; by psn_name; if ina and inb then output STEP6.Datastream_Patstat4; else if ina then output step4.Patstat_gb_simple5; else if inb then output step3.Datastream_gb6; run; data step3.Datastream_gb6; set step3.Datastream_gb6; drop psn_name; rename PREVIOUS_NAME=psn_name; run; proc sort data=step3.Datastream_gb6; by psn_name; run; proc sort data=step4.Patstat_gb_simple5; by psn_name; run; data STEP6.Datastream_Patstat5(keep=psn_name Type) step4.Patstat_gb_simple6 step3.Datastream_gb7; merge step4.Patstat_gb_simple5 (in=ina) step3.Datastream_gb6 (in=inb) ; by psn_name; if ina and inb then output STEP6.Datastream_Patstat5; else if ina then output step4.Patstat_gb_simple6; else if inb then output step3.Datastream_gb7; run; data step7.Datastream_patstat_match2; set Step6.Datastream_patstat: ; run; however, some of the observations cannot be matched together even though they have been processed and are same. for example, the 'ALSTOM' in the processed table 'Step3.Datastream_gb_export_2nd'(i.e., the table has been added in the attachment as an excel'Datastream_gb_export_2nd.xlsx'), however, it cannot be matched with the same character 'ALSTOM' in the table'Step5.PATSTAT_GB2' (excel'DATASTREAM_GB2.xlsx') could you please give me some suggestion about this? why I cannot merge them together? thanks in advance.

France · ‎01-15-2019

dear all, how can I exclude the specific character for all four variables (i.e., COMPANY_NAME, COMPANY_NAME_1, COMPANY_NAME___SHORT, PREVIOUS_NAME) based on the country code for the following excel. COMPANY_NAME COMPANY_NAME_1 COMPANY_NAME___SHORT PREVIOUS_NAME GEOGRAPHIC_DESCR_ NORSK HYDRO ASA NORSK HYDRO ASA NORSK HYDRO ASA NORSK HYDRO ADR (XSQ) NORWAY SIRTI SPA SIRTI SPA SIRTI SPA SIRTI (XSQ) ITALY EVC INTERNATIONAL NV EVC INTERNATIONAL NV EVC INTERNATIONAL NV EVC INTL. (XSQ) NETHERLANDS CARDO AB CARDO AB CARDO AB CARDO (XSQ) SWEDEN HASLEMERE NV HASLEMERE NV HASLEMERE NV NETHERLANDS IRO AB IRO AB IRO AB IRO (XSQ) SWEDEN ALLEANZA ASSICURAZIONI S.P.A. ALLEANZA ALLEANZA ASSICUR. ITALY POLYGRAM N.V. POLYGRAM POLYGRAM N.V. NETHERLANDS HEINEKEN NV HEINEKEN NV HEINEKEN N.V. NETHERLANDS SAMPO OYJ SAMPO OYJ SAMPO OYJ SAMPO 'A' (XSQ) FINLAND I expect the exclude the specific character if 1) the character is the last character of a 'company name' (i.e., all of these four variables, which are COMPANY_NAME, COMPANY_NAME_1, COMPANY_NAME___SHORT, PREVIOUS_NAME) text. 2) it is 'AB' if GEOGRAPHIC_DESCR_ is SWEDEN or Finland, it is 'SPA' or 'S.P.A' if GEOGRAPHIC_DESCR_ is ITALY, it is 'NV' or 'N.V' if GEOGRAPHIC_DESCR_ is Netherlands or Belgium or Indonesia or Suriname, it is 'ASA' if GEOGRAPHIC_DESCR_ is NORWAY, it is 'OYJ' if GEOGRAPHIC_DESCR_ is FINLAND. Could you please give me some suggestions about this. thanks in advance.

France · ‎01-15-2019

dear all I face trouble when I clean the company name by using following code to exclude the PLC. etc. data Step3.Datastream_gb_export_2nd; set Step5.Datastream_gb2; call scan(COMPANY_NAME, -1, position, length); if scan(COMPANY_NAME,-1) in ('LTD' ,'LTD.' ,'LIMITED' ,'PLC' ,'PLC.' ,'AG' ,'S.A.' ,'SA' ,'corporation' ,'CORP.' 'CORP' ,'INC.' ,'INC' ,'COMPANY') then substr(COMPANY_NAME,position)=' '; drop position length; run; data Step3.Datastream_gb_export_2nd; set Step3.Datastream_gb_export_2nd; call scan(COMPANY_NAME_1, -1, position, length); if scan(COMPANY_NAME_1,-1) in ('LTD' ,'LTD.' ,'LIMITED' ,'PLC' ,'PLC.' ,'AG' ,'S.A.' ,'SA' ,'corporation' ,'CORP.' 'CORP' ,'INC.' ,'INC' ,'COMPANY') then substr(COMPANY_NAME_1,position)=' '; drop position length; run; data Step3.Datastream_gb_export_2nd; set Step3.Datastream_gb_export_2nd; call scan(COMPANY_NAME___SHORT, -1, position, length); if scan(COMPANY_NAME___SHORT,-1) in ('LTD' ,'LTD.' ,'LIMITED' ,'PLC' ,'PLC.' ,'AG' ,'S.A.' ,'SA' ,'corporation' ,'CORP.' 'CORP' ,'INC.' ,'INC' ,'COMPANY') then substr(COMPANY_NAME___SHORT,position)=' '; drop position length; run; data Step3.Datastream_gb_export_2nd; set Step3.Datastream_gb_export_2nd; call scan(PREVIOUS_NAME, -1, position, length); if scan(PREVIOUS_NAME,-1) in ('LTD' ,'LTD.' ,'LIMITED' ,'PLC' ,'PLC.' ,'AG' ,'S.A.' ,'SA' ,'corporation' ,'CORP.' 'CORP' ,'INC.' ,'INC' ,'COMPANY') then substr(PREVIOUS_NAME,position)=' '; drop position length; run; I did not exclude all of them successfully. For example 'S.A.' 'Corporation'. I have added the source excel( Step5.Datastream_gb2) and result excel (Step3.Datastream_gb_export_2nd) in the attachments. Could you please give me some suggestions? thanks in advance.

France · ‎01-14-2019

Dear all, How can I clean the company name in the below table, namely, delete LTD LTD. LIMITED PLC PLC.? table 1 data company_name; infile datalines truncover; input city $100.; datalines; ALTERNATIVE ASSET OPPS PCC LTD ALTADIS SA ALTANA AG ALTERA CORPORATION ALTERIAN LIMITED ALTERNATIVE INVESTMENTS STRATEGIES LIMITED ALTERNATIVE LIQUIDITY FUND LTD DAISY CORPORATE SERVICES TRADING LTD ALTIN AG ALTITUDE GROUP PLC ALTONA ENERGY PLC ALTRIA GROUP, INC. ALTUS RESOURCE CAPITAL LTD ALTUS STRATEGIES PLC ALTYN PLC ALUSUISSE GROUP AG ALUSUISSE GROUP AG ALVIS PLC AM N.V. AMADEUS GLOBAL TRAVEL DISTRIBUTION, S.A. ABSA GROUP LTD AMALGAMATED METAL CORPORATION PLC AMARA MINING PLC ALT.ASST.OPPS.PCC LTD. ALTADIS SA ALTANA AG ALTERA CORP. ALTERIAN PLC. ALT.INV.STGIS.LTD. ALT.INV.STGIS.LTD. ALTERNATIVE LQY.LTD. ALTERNATIVE NETWKS.PLC. ALTIFUND CAPITAL ALTIFUND INCOME ALTIN AG ALTITUDE GROUP PLC. ALTONA ENERGY PLC. ALTRIA GROUP INCO. ALTUS RESOURCE CAP.LTD. ; run; logic: 1splite each observation based on the blank. 2delete the character if 1)that character is the last character of the company name, and 2) equals 'LTD' 'LTD.' 'LIMITED' 'PLC' 'PLC.'. 3merge the rest of them together for example, for company_name ' ALTRIA GROUP, INC. in the first step, it should be split into three variables, which like ALTRIA GROUP, INC. in the second step, the 'PLC' which is the last character of the company_name variable should be deleted, like ALTRIA GROUP in the third step, the rest character should be merged together, like ALTRIA GROUP, could you please give me some suggestion about this. thanks in advance.

France · ‎01-06-2019

Dear Reeza, Just remind. thanks in advance.

France · ‎01-06-2019

Dear Patrick, thank you for your help. I will post sample data in the form of a data step in the future. besides, I have one more question. How can I select the city if the name of a city is constructed by two or three characters? for example 'Greater Manchester' thanks in advance.

France · ‎01-06-2019

Dear all, I'd like to select most likely UK city for each company in table 1. logic: 1 group by each 'company_name'. 2 split text in 'persn_address' by black, comma and semicolon 3 select the most frequent character which matched the city name in table 2. 4 keep them all if they appear equally often. by using a sample in Table 1. company_nmae country person_address 2K POLYMER SYSTEMS GB 2K POLYMER SYSTEMS GB 21 Warple Way,London, Greater London W3 0RX 2K POLYMER SYSTEMS GB London 2MEE GB 2MEE GB York 2S AIRCHANGERS GB 2S AIRCHANGERS GB BEECH HOUSE, 4 CARRICKNAVEAGH ROAD, LISBURN, ANTRIM BT27 6UB 2S AIRCHANGERS GB BEECH HOUSE;4 CARRICKNAVEAGH ROAD;LISBURN ANTRIM BT27 6UB 2S AIRCHANGERS GB BROOK HOUSE,DUNMURRY INDUSTRIAL ESTATE,DUNMURRY,BELFAST,BT17 9HU 2S AIRCHANGERS GB Beech House, 4 Carricknaveagh Road,Lisburn, Antrim BT27 6UB 2S-SOFISTIKEJTED SISTEMS GB 2S-SOPHISTICATED SYSTEMS GB 2S-SOPHISTICATED SYSTEMS GB 10 Cromwell Place South Kensington,London SW7 2JN 2S-SOPHISTICATED SYSTEMS GB 10 Cromwell Place, South Kensington,London SW7 2JN 2S-SOPHISTICATED SYSTEMS GB London 2VU GB 3 SPACE SOFTWARE GB 3 SPACE SOFTWARE GB 3 Soho Street,London W1V 5FA 3-D COMPOSITS GB Cumbria 32 DEGREES GB 32 DEGREES GB Lynton House,7-12 Tavistock Square,London WC1H 9BQ 32 DEGREES GB Nottingham table 2 City Aberdeen Armagh Bangor Bath Belfast Birmingham Bradford Brighton & Hove Bristol Cambridge Canterbury Cardiff Carlisle Chelmsford Chester Chichester Coventry Derby Derry Dundee Durham Edinburgh Ely Exeter Glasgow Gloucester Hereford Inverness Kingston upon Hull Lancaster Leeds Leicester Lichfield Lincoln Lisburn Liverpool London Manchester Newcastle upon Tyne Newport Newry Norwich Nottingham Oxford Perth Peterborough Plymouth Portsmouth Preston Ripon St Albans St Asaph St Davids Salford Salisbury Sheffield Southampton Stirling Stoke-on-Trent Sunderland Swansea Truro Wakefield Wells Westminster Winchester Wolverhampton Worcester York the first sample. 1 group the rows based on 'company_name' --'2K POLYMER SYSTEMS' company_nmae country person_address 2K POLYMER SYSTEMS GB 2K POLYMER SYSTEMS GB 21 Warple Way,London, Greater London W3 0RX 2K POLYMER SYSTEMS GB London 2 spilt the text in 'person_address' based on the blank, comma and semicolon. company_nmae country person_address 2K POLYMER SYSTEMS GB 2K POLYMER SYSTEMS GB 21 Warple Way London Greater London W3 0RX 2K POLYMER SYSTEMS GB London 3 select the most frequent character which matched the city name in table 2. the most frequent character is 'London'. it also matches the city name in table 2 (i.e., London) So the city of company '2K POLYMER SYSTEMS' is 'London'. the second example. 32 DEGREES GB 32 DEGREES GB Lynton House,7-12 Tavistock Square,London WC1H 9BQ 32 DEGREES GB Nottingham the result should be 32 DEGREES GB London 32 DEGREES GB Nottingham could you please give me some suggestion about this? thanks in advance.

France · ‎01-04-2019

Dear novinosrin, Thank you for your advice. However, my sample covers thousands of companies. besides, I would like to explain my requirements. I expect to include all companies which are relevant with 'GB' country. and there are two types of revelations. the first is that the 'company_name' is directly related to 'GB' country, such as company_name, country Tesco, GB I would like to include this row in the new dataset. the second is, the 'company_name' is related with at least two country records(i.e., other country code or blank), and one of them is 'GB' country, for example, company_name, country Tesco,GB Tesco,US Tesco, I would like to include all these three rows in the new dataset because the company names in the second and third row are as same as the company name in the first row which recorded with 'GB' country. Could you please give me suggestions based on this requirement? many thanks in advance.

France · ‎01-04-2019

Dear all, how can I keep a group of data if one of them satisfy the requirement? for example table 1 company_name, country apple,US apple, apple,UK tesco,UK sony,Japan I would like to keep all rows relevant with company 'apple' and 'Tesco' if a country recorded with them is UK table 2 company_name, country apple,US apple, apple,UK tesco,UK could you please give me some suggestion about this? thanks in advance.

France · ‎12-27-2018

Dear KurtBremser, Thank you for your advice. it is totally correct. However, could you please answer me one more question? How can I keep the 'application' columns for a company name (i.e., psn_name_cited) if the sum number of 'citation' columns for this name is larger than zero? for example.for the dataset have psn_name_cited, earliest_filing_month, application, citation apple, SEP2000,2,1 apple, SEP2001,2,0 I'd like to have the dataset want psn_name_cited, earliest_filing_month, application, citation apple, SEP2000,2,1 apple, SEP2001,2,0 rather than psn_name_cited, earliest_filing_month, application, citation apple, SEP2000,2,1

France · ‎12-27-2018

Dear all, I'd like to merge two datasets (especially two variables) based on name(psn_name_cited) and date(earliest_filling_month) dataset1 psn_name_cited, citation, earliest_filling_month Apple,1,SEP2001 Facebook,2,OCT2002 dataset2 psn_name_cited,application,earliest_filling_month Apple,5,SEP2001 Apple,2,OCT2001 Facebook,7,OCT2001 Uber,10,DEC2001 I'd like to have the following data (Want) like psn_name_cited, earliest_filling_month,application, citation Apple,SEP2001,5,1 Apple,OCT2001,2,0 Facebook,OCT2001,7,2 Uber,DEC2001,10,0 could you please give me some suggestion about this? thanks in advance

France · ‎12-05-2018

Dear mkeintz, thank you for your suggestion. thanks for your description, that is what I need. however, some company_name variables which recorded with unique (non-blank) Matched_company_name variable are also included in the dataset 'want2'. I add a sample in the attachment (include 1000 observations) would you like to check? thanks in advance.

France · ‎12-04-2018

dear all, how can I create dataset A and dataset B based on the original dataset (e.g., dataset C)? for example, for the original dataset (dataset C) Company name Country Matched BvD ID Matched company name 02 MICRO 02 MICRO TW 02 MICRO US 1... GB04165791 BH (CITY FORUM) LIMITED (Previous name: 1) 1... GB GB04165791 BH (CITY FORUM) LIMITED (Previous name: 1) 1... US 21(TWO-ONE) COMPANY 21(TWO-ONE) COMPANY JP 21(TWO-ONE) COMPANY US 3-D MATRIX JP4010001087940 3-D MATRIX,LTD. 3-D MATRIX JP JP4010001087940 3-D MATRIX,LTD. 3-D MATRIX KR 3-D MATRIX US US138675448L MATRIX 3D LLC I would like to have the dataset A like Company name Country Matched BvD ID Matched company name 1... GB04165791 BH (CITY FORUM) LIMITED (Previous name: 1) 1... GB GB04165791 BH (CITY FORUM) LIMITED (Previous name: 1) 1... US in the dataset A each group of Company_name has only one distinct Matched_company_name (which is BH (CITY FORUM) LIMITED (Previous name: 1)). I would like to also create the dataset B like, Company name Country Matched BvD ID Matched company name 3-D MATRIX JP4010001087940 3-D MATRIX,LTD. 3-D MATRIX JP JP4010001087940 3-D MATRIX,LTD. 3-D MATRIX KR 3-D MATRIX US US138675448L MATRIX 3D LLC in dataset B, each group of Company_name has at least two distinct Matched_company_name (which are 3-D MATRIX,LTD. and MATRIX 3D LLC). I would like to exclude observations which Company_name are '02 MICRO' and '21(TWO-ONE) COMPANY' as none of them have Matched_company_name variables. could you please give me some suggestion about this?

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