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Denali
Quartz | Level 8

Hi, I have about 190 variables to change from character variable to numeric variable.

Since they are questionnaire data, original data in Excel contains text like: 1-not satisfied, 2-likely not satisfied,....,5-very satisfied. I used compress to extract the number only for the health variable and used the traditional way to convert char to num (please see below code). Is there a faster way to do it?

 

data allnew;
set all;
HealthN = compress(Health, '-', 'A');
newHealthN = input(HealthN,1.0);
drop Health HealthN;
rename newHealthN = Health;
run;

 

The previous person who worked on this project wrote this code:

 

/*extract the numbers from categorical variables- to remove format-change to numeric*/
data allnew;
set all;
array sect[*] $ Health Health_later SECT_I_5--SECT_I_38 SECT_IV_a--SECT_VIII_13 Sleep_Quality;
array newsect[*] Health Health_later SECT_I_5--SECT_I_38 SECT_IV_a--SECT_VIII_13 Sleep_Quality;
do i=1 to dim(sect);
newsect[i]=input(substr(sect[i],1,1),1.);
end;
drop i;
run;

 

However, log did not say the right thing:

Numeric values have been converted to character values at the places given by:
(Line):(Column).

6 REPLIES 6
RW9
Diamond | Level 26 RW9
Diamond | Level 26

Will you be creating an SDTM domain for this data?  I ask as SDTM are normalised data structures, and if I had to deal with this type of data the first thing I would do in most cases is to normalise it, this makes most programming tasks simpler in the long run.  So have:

<id variables>  QUESTION      RESPONSE

                      Q1                  1-Happy

                      Q2                  3-Unhappy

...

 

Then you can simply do:

numeric_response=input(scan(response,1,"-"),best.);

 

Now to answer your question, your reading data in from Excel (which is unstructured), and from the warning message we can see that it is trying to convert numeric data to chraracter, so I would assume that something on your import is going wrong and one of the variables is nuemeric rather than text.

Denali
Quartz | Level 8

Please see the proc contents output. They are labeled as char instead of numeric.


SubjectIDChar5$5.$5.SubjectID
VISITChar4$4.$4.VISIT
InterviewerIDNum8  InterviewerID
TodaysDateNum8DATE9.DATE9.TodaysDate
Quality_Of_LifeChar2$2.$2.Quality_Of_Life
Curr_Quality_Of_LifeChar2$2.$2.Curr_Quality_Of_Life
HealthChar11$11.$11.Health
Health_LaterChar36$36.$36.Health_Later
SECT_I_5Char18$18.$18.SECT_I_5
SECT_I_6Char11$11.$11.SECT_I_6
SECT_I_7Char18$18.$18.SECT_I_7
SECT_I_8Char24$24.$24.SECT_I_8
SECT_I_9Char24$24.$24.SECT_I_9
SECT_I_10Char24$24.$24.SECT_I_10
SECT_I_11Char24$24.$24.SECT_I_11
SECT_I_12Char24$24.$24.SECT_I_12
SECT_I_13Char24$24.$24.SECT_I_13
SECT_I_14Char24$24.$24.SECT_I_14
SECT_I_15Char24$24.$24.SECT_I_15
SECT_I_16Char24$24.$24.SECT_I_16
SECT_I_17Char24$24.$24.SECT_I_17
SECT_I_18Char24$24.$24.SECT_I_18
SECT_I_19Char24$24.$24.SECT_I_19
SECT_I_20Char24$24.$24.SECT_I_20
SECT_I_21Char24$24.$24.SECT_I_21
SECT_I_22Char24$24.$24.SECT_I_22
SECT_I_23Char24$24.$24.SECT_I_23
SECT_I_24Char24$24.$24.SECT_I_24
SECT_I_25Char24$24.$24.SECT_I_25
SECT_I_26Char24$24.$24.SECT_I_26
SECT_I_27Char5$5.$5.SECT_I_27
SECT_I_28Char5$5.$5.SECT_I_28
SECT_I_29Char5$5.$5.SECT_I_29
SECT_I_30Char5$5.$5.SECT_I_30
SECT_I_31Char5$5.$5.SECT_I_31
SECT_I_32Char5$5.$5.SECT_I_32
SECT_I_33Char5$5.$5.SECT_I_33
SECT_I_34Char18$18.$18.SECT_I_34
SECT_I_35Char18$18.$18.SECT_I_35
SECT_I_36Char18$18.$18.SECT_I_36
SECT_I_37Char18$18.$18.SECT_I_37
SECT_I_38Char22$22.$22.SECT_I_38
SECT_II_BChar2$2.$2.SECT_II_B
SECT_II_C_ANum8  SECT_II_C_A
SECT_II_C_BNum8  SECT_II_C_B
SECT_II_C_CNum8  SECT_II_C_C
SECT_III_1Char1$1.$1.SECT_III_1
SECT_III_2Char1$1.$1.SECT_III_2
SECT_III_3Char1$1.$1.SECT_III_3
SECT_III_4Char1$1.$1.SECT_III_4
SECT_III_5Char1$1.$1.SECT_III_5
SECT_III_6Char1$1.$1.SECT_III_6
SECT_III_7Char1$1.$1.SECT_III_7
SECT_III_8Char1$1.$1.SECT_III_8
SECT_III_9Char1$1.$1.SECT_III_9
SECT_III_10Char1$1.$1.SECT_III_10
SECT_IV_aChar15$15.$15.SECT_IV_a
SECT_IV_bChar15$15.$15.SECT_IV_b
SECT_IV_cChar15$15.$15.SECT_IV_c
SECT_IV_dChar15$15.$15.SECT_IV_d
SECT_IV_eChar15$15.$15.SECT_IV_e
SECT_IV_fChar15$15.$15.SECT_IV_f
SECT_IV_gChar15$15.$15.SECT_IV_g
SECT_IV_hChar15$15.$15.SECT_IV_h
SECT_IV_iChar15$15.$15.SECT_IV_i
SECT_IV_jChar15$15.$15.SECT_IV_j
SECT_IV_kChar15$15.$15.SECT_IV_k
SECT_IV_lChar15$15.$15.SECT_IV_l
SECT_IV_mChar15$15.$15.SECT_IV_m
SECT_IV_nChar15$15.$15.SECT_IV_n
SECT_IV_oChar15$15.$15.SECT_IV_o
SECT_IV_pChar15$15.$15.SECT_IV_p
SECT_IV_qChar15$15.$15.SECT_IV_q
SECT_IV_rChar15$15.$15.SECT_IV_r
SECT_IV_sChar15$15.$15.SECT_IV_s
SECT_IV_tChar15$15.$15.SECT_IV_t
Phys_Well_1Char14$14.$14.Phys_Well_1
Phys_Well_2Char14$14.$14.Phys_Well_2
Phys_Well_3Char14$14.$14.Phys_Well_3
Phys_Well_4Char14$14.$14.Phys_Well_4
Phys_Well_5Char14$14.$14.Phys_Well_5
Phys_Well_6Char14$14.$14.Phys_Well_6
Phys_Well_7Char14$14.$14.Phys_Well_7
SOCIAL_Well_8Char14$14.$14.SOCIAL_Well_8
SOCIAL_Well_9Char14$14.$14.SOCIAL_Well_9
SOCIAL_Well_10Char14$14.$14.SOCIAL_Well_10
SOCIAL_Well_11Char14$14.$14.SOCIAL_Well_11
SOCIAL_Well_12Char14$14.$14.SOCIAL_Well_12
SOCIAL_Well_13Char14$14.$14.SOCIAL_Well_13
SOCIAL_Well_14Char14$14.$14.SOCIAL_Well_14
EMOT_Well_15Char14$14.$14.EMOT_Well_15
EMOT_Well_16Char14$14.$14.EMOT_Well_16
EMOT_Well_17Char14$14.$14.EMOT_Well_17
EMOT_Well_18Char14$14.$14.EMOT_Well_18
EMOT_Well_19Char14$14.$14.EMOT_Well_19
EMOT_Well_20Char14$14.$14.EMOT_Well_20
FUNCT_Well_21Char14$14.$14.FUNCT_Well_21
FUNCT_Well_22Char14$14.$14.FUNCT_Well_22
FUNCT_Well_23Char14$14.$14.FUNCT_Well_23
FUNCT_Well_24Char14$14.$14.FUNCT_Well_24
FUNCT_Well_25Char14$14.$14.FUNCT_Well_25
FUNCT_Well_26Char14$14.$14.FUNCT_Well_26
FUNCT_Well_27Char14$14.$14.FUNCT_Well_27
ADDL_CONC_28Char14$14.$14.ADDL_CONC_28
ADDL_CONC_29Char14$14.$14.ADDL_CONC_29
ADDL_CONC_30Char14$14.$14.ADDL_CONC_30
ADDL_CONC_31Char14$14.$14.ADDL_CONC_31
ADDL_CONC_32Char14$14.$14.ADDL_CONC_32
ADDL_CONC_33Char14$14.$14.ADDL_CONC_33
ADDL_CONC_34Char14$14.$14.ADDL_CONC_34
ADDL_CONC_35Char14$14.$14.ADDL_CONC_35
ADDL_CONC_36Char14$14.$14.ADDL_CONC_36
ADDL_CONC_37Char14$14.$14.ADDL_CONC_37
ADDL_CONC_38Char14$14.$14.ADDL_CONC_38
ADDL_CONC_39Char14$14.$14.ADDL_CONC_39
ADDL_CONC_40Char14$14.$14.ADDL_CONC_40
ADDL_CONC_41Char14$14.$14.ADDL_CONC_41
ADDL_CONC_42Char14$14.$14.ADDL_CONC_42
ADDL_CONC_43Char14$14.$14.ADDL_CONC_43
ADDL_CONC_44Char14$14.$14.ADDL_CONC_44
ADDL_CONC_45Char14$14.$14.ADDL_CONC_45
ADDL_CONC_46Char14$14.$14.ADDL_CONC_46
ADDL_CONC_47Char14$14.$14.ADDL_CONC_47
ADDL_CONC_48Char14$14.$14.ADDL_CONC_48
ADDL_CONC_49Char14$14.$14.ADDL_CONC_49
ADDL_CONC_50Char14$14.$14.ADDL_CONC_50
ADDL_CONC_51Char14$14.$14.ADDL_CONC_51
ADDL_CONC_52Char14$14.$14.ADDL_CONC_52
ADDL_CONC_53Char14$14.$14.ADDL_CONC_53
ADDL_CONC_54Char14$14.$14.ADDL_CONC_54
ADDL_CONC_55Char14$14.$14.ADDL_CONC_55
FATG_ENRGY_56Char14$14.$14.FATG_ENRGY_56
FATG_ENRGY_57Char14$14.$14.FATG_ENRGY_57
FATG_ENRGY_58Char14$14.$14.FATG_ENRGY_58
FATG_ENRGY_59Char14$14.$14.FATG_ENRGY_59
FATG_ENRGY_60Char14$14.$14.FATG_ENRGY_60
FATG_ENRGY_61Char14$14.$14.FATG_ENRGY_61
FATG_ENRGY_62Char14$14.$14.FATG_ENRGY_62
FATG_ENRGY_63Char14$14.$14.FATG_ENRGY_63
FATG_ENRGY_64Char14$14.$14.FATG_ENRGY_64
FATG_ENRGY_65Char14$14.$14.FATG_ENRGY_65
FATG_ENRGY_66Char14$14.$14.FATG_ENRGY_66
FATG_ENRGY_67Char14$14.$14.FATG_ENRGY_67
FATG_ENRGY_68Char14$14.$14.FATG_ENRGY_68
SECT_VI_1Char14$14.$14.SECT_VI_1
SECT_VI_2Char14$14.$14.SECT_VI_2
SECT_VI_3Char14$14.$14.SECT_VI_3
SECT_VI_4Char14$14.$14.SECT_VI_4
SECT_VI_5Char14$14.$14.SECT_VI_5
SECT_VI_6Char14$14.$14.SECT_VI_6
SECT_VI_7Char14$14.$14.SECT_VI_7
SECT_VI_8Char14$14.$14.SECT_VI_8
SECT_VI_9Char14$14.$14.SECT_VI_9
SECT_VI_10Char14$14.$14.SECT_VI_10
SECT_VI_11Char14$14.$14.SECT_VI_11
SECT_VI_12Char14$14.$14.SECT_VI_12
SECT_VI_13Char14$14.$14.SECT_VI_13
SECT_VI_14Char14$14.$14.SECT_VI_14
SECT_VI_15Char14$14.$14.SECT_VI_15
SECT_VI_16Char14$14.$14.SECT_VI_16
SECT_VI_17Char14$14.$14.SECT_VI_17
SECT_VI_18Char14$14.$14.SECT_VI_18
SECT_VI_19Char14$14.$14.SECT_VI_19
SECT_VI_20Char14$14.$14.SECT_VI_20
SECT_VII_1Char22$22.$22.SECT_VII_1
SECT_VII_2Char22$22.$22.SECT_VII_2
SECT_VII_3Char22$22.$22.SECT_VII_3
SECT_VII_4Char22$22.$22.SECT_VII_4
SECT_VII_5Char22$22.$22.SECT_VII_5
SECT_VII_6Char22$22.$22.SECT_VII_6
SECT_VII_7Char22$22.$22.SECT_VII_7
SECT_VII_8Char22$22.$22.SECT_VII_8
SECT_VII_9Char22$22.$22.SECT_VII_9
SECT_VII_10Char22$22.$22.SECT_VII_10
SECT_VIII_1Char22$22.$22.SECT_VIII_1
SECT_VIII_2Char22$22.$22.SECT_VIII_2
SECT_VIII_3Char22$22.$22.SECT_VIII_3
SECT_VIII_4Char22$22.$22.SECT_VIII_4
SECT_VIII_5Char22$22.$22.SECT_VIII_5
SECT_VIII_6Char22$22.$22.SECT_VIII_6
SECT_VIII_7Char22$22.$22.SECT_VIII_7
SECT_VIII_8Char22$22.$22.SECT_VIII_8
SECT_VIII_9Char22$22.$22.SECT_VIII_9
SECT_VIII_10Char22$22.$22.SECT_VIII_10
SECT_VIII_11Char22$22.$22.SECT_VIII_11
SECT_VIII_12Char22$22.$22.SECT_VIII_12
SECT_VIII_13Char22$22.$22.SECT_VIII_13
BedTimeNum8  BedTime
Fall_To_sleep_MinutesNum8  Fall_To_sleep_Minutes
GetUpTimeNum8  GetUpTime
Sleep_HoursNum8  Sleep_Hours
Sleep_QualityChar13$13.$13.Sleep_Quality
SECT_IX_6Char1$1.$1.SECT_IX_6
SECT_IX_7Char1$1.$1.SECT_IX_7
SECT_IX_8Char1$1.$1.SECT_IX_8
RW9
Diamond | Level 26 RW9
Diamond | Level 26

Your code:

 

array sect[*] $ Health Health_later SECT_I_5--SECT_I_38 SECT_IV_a--SECT_VIII_13 Sleep_Quality;
array newsect[*] Health Health_later SECT_I_5--SECT_I_38 SECT_IV_a--SECT_VIII_13 Sleep_Quality;
do i=1 to dim(sect);
newsect[i]=input(substr(sect[i],1,1),1.);

 

newsect and sect both refer to the same variables.  So Health is a character variable, you are trying to input() the text from Health back into Health, but Health is still a character variable, hence the numeric response from input() is being converted back to character.  Have you second array use new variables:

array newsect[*] num_Health num_Health_later num_SECT_I_5...;

ballardw
Super User

Typically when I get values like 1-not satisfied, 2-likely not satisfied I read the data with custom informats to convert to numeric at reading after saving the Excel as CSV so I know what I have. And then build a display format if needed. A sort of example:

proc format library=work;
invalue satisfaction
'1-not satisfied'       =1
'2-likely not satisfied'=2
'5-very satisfied'      =5
;
Value satisfaction
1  = 'Not satisfied'       
2  = 'Likely not satisfied'
5  = 'Very satisfied'  
;
run;

And then in the data step to read the data I use informat statements to associate the Satisfaction informat with the values.

 

Since surveys often use a number of standard response categories, and the same organization the same categories in multiple surveys, then this becomes a considerable time saver.

Note that you can actually include additional pieces such as special missing to handle responses such as "don't know" "no opinion" or "refused" with the special missing values of .A through .Z.

Shmuel
Garnet | Level 18

Adapt LIBNAME and MEMNAME to your needs, as add excluded variables and unmark it, using next code:

%macro str2num(vx);
   &vx.N = input(scan(&vx,1,'-'),best.);
%mend str2num;

data test(keep=name);
 set sashelp.vcolumn(where=(libname='SASHELP' and memname='AACOMP' and
               type='char' /* and name not in (...excluded names ...) */ 
           ))  end=eof;
           
     if _N_ = 1 then 
        call execute('data want; set sashelp.aacomp;');
     
     call execute('%str2num('||strip(name)||'); DROP '||name||';' );
     
     if eof then call execute('RUN;');
run;
Shmuel
Garnet | Level 18
You may need adapt also dataset names on first call execute statement.

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