Dear Statalists,
I have an inquiry about using -matchit- to fuzzy match. I have two datasets: dataset1 has complete company IDs and names, while dataset2 only has company names. Please see the data examples below:
----------------------- dataset1 -----------------------
------------------ copy up to and including the previous line ------------------
Listed 100 out of 122563 observations
Use the count() option to list more
----------------------- dataset2 -----------------------
------------------ copy up to and including the previous line ------------------
Listed 100 out of 158468 observations
Use the count() option to list more
Their company names can be slightly different below. How can I fuzzy match them together so I can obtain complete company IDs for two datasets? Thank you in advance!
I have an inquiry about using -matchit- to fuzzy match. I have two datasets: dataset1 has complete company IDs and names, while dataset2 only has company names. Please see the data examples below:
----------------------- dataset1 -----------------------
Code:
* Example generated by -dataex-. For more info, type help dataex clear input str10 ID str50 cnms "008972" "RAYTHEON" "008972" "RAYTHEON" "008972" "RAYTHEON" "010983" "UTD TECHS" "010983" "UTD TECHS" "010983" "UTD TECHS" "010983" "UTD TECHS" "002322" "BORG-WARNER" "002322" "BORG-WARNER" "003022" "CHRYSLER" "003022" "CHRYSLER" "003022" "CHRYSLER" "003022" "CHRYSLER" "003022" "CHRYSLER" "003022" "CHRYSLER" "003022" "CHRYSLER" "003734" "DANA CORP" "003734" "DANA CORP" "004321" "EMERSON EL" "004321" "EMERSON EL" "004321" "EMERSON EL" "004839" "FORD MTR" "004839" "FORD MTR" "004839" "FORD MTR" "004839" "FORD MTR" "004839" "FORD MTR" "004839" "FORD MTR" "004839" "FORD MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "006674" "LEROY INDS" "004839" "FORD MOTOR" "004839" "FORD MOTOR" "004839" "FORD MOTOR" "004839" "FORD MOTOR" "004839" "FORD MOTOR" "004839" "FORD MOTOR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "005073" "GEN MTR" "001581" "AM TEL & TEL" "001581" "AM TEL & TEL" "001581" "AM TEL & TEL" "001581" "AM TEL &TEL" "001581" "AM TEL &TEL" "001581" "AM TEL &TEL" "009899" "AT&T" "009899" "AT&T" "009899" "AT&T" "009899" "AT&T" "001581" "AT&T CORP" "004961" "GTE CORP" "006066" "INTL BUS MA" "006066" "INTL BUS MA" "006066" "INTL BUS MA" "006066" "INTL BUS MA" "006066" "INTL BUS MA" "006066" "INTL BUS MA" "006066" "INTL BUS MA" "006066" "INTL BUS MA" "006066" "INTL BUS MA" "006864" "MCI COMMUN" "006864" "MCI COMMUN" "002136" "VERIZON COMMUNICATIONS" "002136" "VERIZON COMMUNICATIONS" "002136" "VERIZON COMMUNICATIONS" "002136" "VERIZON COMMUNICATIONS" "002136" "VERIZON COMMUNICATIONS" "002136" "VERIZON COMMUNICATIONS" "002136" "VERIZON COMMUNICATIONS" "002136" "VERIZON COMMUNICATIONS" "025880" "Patterson Dental Co" "061494" "Schein Henry Inc" "061494" "Schein Henry Inc" "061494" "Schein Henry Inc" "061494" "Schein Henry Inc" "011638" "XONICS INC" "011638" "XONICS INC" "001581" "AM TEL & TEL" "001581" "AM TEL & TEL" "001581" "AM TEL & TEL" "001581" "AM TEL & TEL" "002138" "BELL LABS" "002138" "BELL LABS" "002138" "BELL LABS" "001553" "AM SVG-NY" "010199" "SUPERMRKT" "005055" "GEN FOODS" "005055" "GEN FOODS" end
Listed 100 out of 122563 observations
Use the count() option to list more
----------------------- dataset2 -----------------------
Code:
* Example generated by -dataex-. For more info, type help dataex clear input str50 cnms "RAYTHEON" "DAGE CORP" "UTD TECHS" "UTD TECHS" "DAGE CORP" "RAYTHEON" "DECCA ELECTR" "DECCA ELECTR" "DECCA ELECTR" "BRIDGE ENGR" "DINAS ENGR" "EMERSON EL" "GEN MTR" "NEW PROC GEAR" "GEN MTR" "EMERSON EL" "DANA CORP" "DANA CORP" "GEN MTR" "GKN" "NEW PROC GEAR" "CHRYSLER" "GEN MTR" "LEROY INDS" "GKN" "CHRYSLER" "GKN" "GEN MTR" "GKN" "CHRYSLER" "BORG-WARNER" "GEN MTR" "BORG-WARNER" "FORD MTR" "CHRYSLER" "FORD MTR" "CHRYSLER" "FORD MTR" "CHRYSLER" "GEN MTR" "FORD MTR" "CHRYSLER" "GEN MTR" "GKN AUTO INC" "NEW VENTURE" "FORD MTR" "GEN MTR" "FORD MTR" "GEN MTR" "NEW VENTURE" "GKN AUTO INC" "GKN AUTO INC" "NEW VENTURE" "GEN MTR" "FORD MTR" "FORD MOTOR" "GEN MTR" "2 CUSTOMERS" "GEN MTR" "FORD MOTOR" "FORD MOTOR" "GEN MTR" "FORD MOTOR" "GEN MTR" "FORD MOTOR" "FORD MOTOR" "AM TEL & TEL" "INTL BUS MA" "MCI COMMUN" "INTL BUS MA" "AM TEL &TEL" "AM TEL &TEL" "INTL BUS MA" "MCI COMMUN" "AM TEL &TEL" "INTL BUS MA" "GTE CORP" "WESTN UN TE" "INTL BUS MA" "AT&T CORP" "INTL BUS MA" "INTL BUS MA" "VERIZON COMMUNICATIONS" "6 Customers" "4 Customers" "3 Customers" "VERIZON COMMUNICATIONS" "6 Customers" "VERIZON COMMUNICATIONS" "3 Customers" "6 Customers" "6 Customers" "VERIZON COMMUNICATIONS" "3 Customers" "AT&T" "8 Customers" "VERIZON COMMUNICATIONS" "AT&T" "8 Customers" "VERIZON COMMUNICATIONS" end
Listed 100 out of 158468 observations
Use the count() option to list more
Their company names can be slightly different below. How can I fuzzy match them together so I can obtain complete company IDs for two datasets? Thank you in advance!
Code:
RAYTHEON CO RAYTHEON UNITED TECHNOLOGIES CORP UTD TECHS BURNS INTL SERVICES CORP BORG-WARNER CHRYSLER CORP CHRYSLER DANA INC DANA CORP EMERSON ELECTRIC CO EMERSON EL
