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gorkemkilic
‎11-23-2015
  • 4 Posts
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Re: Bar Plot With Specified Bar Values

by Calcite | Level 5 in SAS Enterprise Guide
‎11-23-2015 04:09 AM
‎11-23-2015 04:09 AM
Hi,   You could find the code that generates issue below. Thanks in advance.   PROC SQL;  CREATE VIEW WORK.SORTTempTableSorted AS   SELECT T.days, T.amount  FROM WRK.ding_bar_temp as T ; QUIT; Axis1  STYLE=1  WIDTH=1  MINOR=NONE ; Axis2  STYLE=1  WIDTH=1 ; TITLE; TITLE1 "Bar Chart"; FOOTNOTE; FOOTNOTE1 "Generated by the SAS System (&_SASSERVERNAME, &SYSSCPL) on %TRIM(%QSYSFUNC(DATE(), NLDATE20.)) at %TRIM(%SYSFUNC(TIME(), TIMEAMPM12.))"; PROC GCHART DATA=WORK.SORTTempTableSorted ;  VBAR   days  /  SUMVAR=amount  CLIPREF FRAME MIDPOINTS=30 TO 60 BY 30  TYPE=SUM  COUTLINE=BLACK  RAXIS=AXIS1  MAXIS=AXIS2 ; /* -------------------------------------------------------------------    End of task code.    ------------------------------------------------------------------- */ RUN; QUIT; %_eg_conditional_dropds(WORK.SORTTempTableSorted); TITLE; FOOTNOTE; ... View more

Bar Plot With Specified Bar Values

by Calcite | Level 5 in SAS Enterprise Guide
‎11-20-2015 05:36 AM
‎11-20-2015 05:36 AM
Hi ,   One of my colleagues has the following question regarding to the Bar plot in SAS Enterprise guide.   "See the following table: days    amount 1          10 31        20 60         5   When I generate the bar plot to sum up the amount based on different days, with bar values specified to be 30 and 60. The bar plot has two bars, one is at value 30 which has an amount of 10+20=30, the other bar is at value 60, and has value 5. Why is the first bar value (i.e., 30) also includes the second row? Shouldn't the bar chart value be 10 and 25 in this case?   How is the categorization done? Isn't it days<=30, and days between 30 and 60? " Thanks in advance     ... View more

Clustering with Too Many Variables

by Calcite | Level 5 in SAS Data Science
‎11-20-2015 05:05 AM
‎11-20-2015 05:05 AM
Hi, I have 230 variables and 15.000 observations in my dataset. 30 of the variables are categorical. My goal is to find meaningful clusters out of this population by using SAS EM Clustering Node. These are the steps that I apply before clustering. - Outlier elimination - Missing value imputation - Encoding categorical variables ( by creating dummy binary variables ) I have 4 questions: 1. Do you recommend any other analyses in order to obtain better results ?   2. "Incorporating the categorical variables in clustering  by binarizing them" is the best way to use them? 3. As far as I researched, the number of my variables is too many for clustering. So as a next step,  I need to reduce the number of input variables. I tried applying 'Principal Components' and 'Variable Clustering' before the 'Clustering'.  I ended up with 2 different clusters but I'm having troubles to interpret these clusters. When I check the output of 'Segment Profile' node, I see the distributions of either variable clusters or principal components as. How can I know which components are related to which variables? 4. How do I asses the results of clustering ? Thanks in advance Regards, Gorkem   ... View more

Correlation Matrix for Categorical Variables

by Calcite | Level 5 in SAS Enterprise Guide
‎11-18-2015 09:53 AM
‎11-18-2015 09:53 AM
Hi,   I'd like to see the correlations among the variables in my dataset. I created a correlation matrix for continuous variables by using Analyze/Multivariate/Correlations function but I don't know how to create a correlation matrix for the categorical variables. Could you help me with this issue? Thanks ... View more
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