EPIB 698C lecture 7

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EPIB 698C lecture 7

• Raul Cruz-Cano

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Sorting, Printing and Summarizing Your Data

• SAS Procedures (or PROC) perform specific
  analysis or function, produce results or reports
• Eg Proc Print data new run
• All procedures have required statements, and most
  have optional statements
• All procedures start with the key word PROC,
  followed by the name of the procedure, such as
  PRINT, or contents
• Options, if there are any, follow the procedure
  name
• Datadata_name options tells SAS which dataset to
  use as an input for this procedure. NOTE if you
  skip it, SAS will use the most recently created
  dataset, which is not necessary the same as the
  mostly recently used data.

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BY statement

• The BY statement is required for only one
  procedure, Proc sort
• PROC Sort data new
• By gender
• Run
• For all the other procedures, BY is an optional
  statement, and tells SAS to perform analysis for
  each level of the variable after the BY
  statement, instead of treating all subjects as
  one group
• Proc Print data new
• By gender
• Run
• All procedures, except Proc sort, assumes you
  data are already sorted by the variables in your
  BY statement

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PROC Sort

• Syntax
• Proc Sort data input_data_name out
  out_data_name
• By variable-1 variable-n
• The variables in the by statement are called by
  variables.
• With one by variable, SAS sorts the data based on
  the values of that variable
• With more than one variable, SAS sorts
  observations by the first variable, then by the
  second variable within the categories of the
  first variable, and so on
• The DATA and OUT options specify the input and
  output data sets. Without the DATA option, SAS
  will use the most recently created data set.
  Without the OUT statement, SAS will replace the
  original data set with the newly sorted version

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PROC Sort

• By default, SAS sorts data in ascending order,
  from the lowest to the highest value or from A to
  Z. To have the the ordered reversed, you can add
  the keyword DESCENDING before the variable you
  want to use the highest to the lowest order or Z
  to A order
• The NODUPKEY option tells SAS to eliminate any
  duplicate observations that have the same values
  for the BY variables

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PROC Sort

• Example The sealife.txt contains information on
  the average length in feet of selected whales and
  sharks. We want to sort the data by the family
  and length
• Name Family Length
• beluga whale 15
• whale shark 40
• basking shark 30
• gray whale 50
• mako shark 12
• sperm whale 60
• dwarf shark .5
• whale shark 40
• humpback . 50
• blue whale 100
• killer whale 30

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PROC Sort

• Example The sealife.txt contains information on
  the average length in feet of selected whales and
  sharks. We want to sort the data by the family
  and length
• Name Family Length
• beluga whale 15
• whale shark 40
• basking shark 30
• gray whale 50
• mako shark 12
• sperm whale 60
• dwarf shark .5
• whale shark 40
• humpback . 50
• blue whale 100
• killer whale 30

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PROC Sort

• DATA marine
• INFILE 'F\sealife.txt'
• INPUT Name Family Length
• run
• Sort the data
• PROC SORT DATA marine OUT seasort
• NODUPKEY
• BY Family DESCENDING Length
• run

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Title and Footnote statement

• Title and Footnote statements are global
  statements, and are not technically part of any
  step.
• You can put them anywhere in your program but
  since they apply to the procedure output, it is
  usually make sense to put them with the procedure
• Syntax
• Title This is a title for this procedure
• Footnote This is the footnote for this
  procedure
• To cancel the current title or footnote, use the
  following null statement
• Title
• Footnote

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Label Statement

• The label statement can create descriptive
  labels, up to 256 characters long, for each
  variable
• Eg
• Label Shipdate Date merchandise was
  shipped
• ID Identification number of subject
• When a label statement is used in a data step,
  the labels become part of the data set but when
  used in a PROC step, the labels stay in effect
  only for the duration of that step

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PROC Format statement

• The PROC FORMAT procedure allows you to create
  your own formats. It is useful when you use coded
  data.
• The Proc format procedure creates formats what
  will later be associated with variables in a
  FORMAT statement
• Syntax of the PROC FORMAT
• PROC FORMAT
• Value name range-1 formated-text-1
• range-2 formated-text-2
• range-n
  formated-text-n
• Name is the name of the format you are creating
  if the format is for character data, the you need
  to use name instead of name. In addition the
  name can not be the name of an existing format

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PROC Format statement

• Each range is the value of the variable that is
  assigned to the text given in the quotation marks
• The text can be up to 32,767 characters long, but
  some procedures print only the first 8 to 16
  characters
• The following are some examples of valid range
  specifications
• AAsian character values must be put
  in quotation marks
• 1,3,5,7,9ODD with more than one value in the
  range, separate
• them with comma or
  hyphen (-)
• 5000-highhigh price the key word high and low
  can be used in
• ranges
  to indicate the lowest and highest
• 
  non-missing values for the variable

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PROC Format statement

• Here is a survey about subjects preference of
  car colors. The data contains subjects age, sex
  (coded as 1 for male and 2 for female), annual
  income, and preferred car color (yellow, green,
  blue, and white). Here are the data
• age sex income color
• 19 1 14000 Y
• 45 1 65000 G
• 72 2 35000 B
• 31 1 44000 Y
• 58 2 83000 W

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• DATA carsurvey
• INFILE C\car.txt'
• INPUT Age Sex Income Color
• run
• PROC FORMAT
• VALUE gender 1 'Male
• 2 'Female'
• VALUE agegroup 13 -lt 20 'Teen'
• 20 -lt 65 'Adult'
• 65 - HIGH 'Senior'
• VALUE col 'W' 'Moon White'
• 'B' 'Sky Blue'
• 'Y' 'Sunburst Yellow'
• 'G' Green'
• PROC PRINT DATA carsurvey
• FORMAT Sex gender. Age agegroup.
• Color col. Income DOLLAR8.
• RUN

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Subsetting in procedures with a where statement

• The WHERE statement tells a procedure to use a
  subset of data
• It is an optional statement for any PROC step
• Unlike subsetting in the DATA step, using a WHERE
  statement in a procedure does not create a new
  data set
• The basic form is
• Where condition (eg where gender female)

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Subsetting in procedures with a where statement

• A data set contains information about well-known
  painters
• Name Style Nation of origin
• Mary Cassatt Impressionism
  U
• Paul Cezanne Post-impressionism F
• Edgar Degas Impressionism
  F
• Paul Gauguin Post-impressionism F
• Claude Monet Impressionism
  F
• Pierre Auguste Renoir Impressionism F
• Vincent van Gogh Post-impressionism N
• Goal we want a list of impressionist painters

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• DATA style
• INFILE C\style.txt'
• INPUT Name 1-21 style 23-40 Origin 42
• RUN
• PROC PRINT DATA style
• WHERE style 'Impressionism'
• TITLE 'Major Impressionist Painters'
• FOOTNOTE 'F France N Netherlands U US'
  
• RUN

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Summarizing you data with PROC MEANS

• The proc means procedure provide simple
  statistics on numeric variables. Syntax Proc
  means options
• List of simple statistics can be produced by proc
  means
• MAX the maximum value
• MIN the minimum value
• MEAN the mean
• N number of non-missing values
• STDDEV the standard deviation
• NMISS number of missing values
• RANGE the range of the data
• SUM the sum
• MEDIAN the median

DEFAULT
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Proc means

• Options of Proc means
• By variable-list perform analysis for each
  level of the variables in the list. Data needs to
  be sorted first
• Var variable list specifies which variables to
  use in the analysis

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Proc means

• A wholesale nursery is selling garden flowers,
  they want to summarize their sales figures by
  month. The data is as follows
• ID Date Lily SnapDragon Marigold
• 756-01 05/04/2001 120 80 110
• 756-01 05/14/2001 130 90 120
• 834-01 05/12/2001 90 160 60
• 834-01 05/14/2001 80 60 70
• 901-02 05/18/2001 50 100 75
• 834-01 06/01/2001 80 60 100
• 756-01 06/11/2001 100 160 75
• 901-02 06/19/2001 60 60 60
• 756-01 06/25/2001 85 110 100

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• DATA sales
• INFILE 'C\Flowers.txt'
• INPUT CustomerID _at_9 SaleDate MMDDYY10. Lily
  SnapDragon Marigold
• Month MONTH(SaleDate)
• PROC SORT DATA sales
• BY Month
• Calculate means by Month for flower sales
• PROC MEANS DATA sales OUTPUT OUT values
• BY Month
• VAR Lily SnapDragon Marigold
• TITLE 'Summary of Flower Sales by Month'
• RUN

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OUTPUT statement

• We can use the OUTPUT statement to write summary
  statistics in a SAS data set
• Syntax
• OUTPUT out data_name output-statistic-list
• Eg
• Proc means data new
• Var age BMI
• Output out new1 mean (age BMI)mean_age
  mean_BMI
• Run
• In the output data set new1, we have two means
  for age and BMI respectively. The variable names
  are mean_age mean_BMI respectively.

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Proc means

• A wholesale nursery is selling garden flowers,
  they want to summarize their sales figures by
  month. The data is as follows
• ID Date Lily SnapDragon Marigold
• 756-01 05/04/2001 120 80 110
• 756-01 05/14/2001 130 90 120
• 834-01 05/12/2001 90 160 60
• 834-01 05/14/2001 80 60 70
• 901-02 05/18/2001 50 100 75
• 834-01 06/01/2001 80 60 100
• 756-01 06/11/2001 100 160 75
• 901-02 06/19/2001 60 60 60
• 756-01 06/25/2001 85 110 100

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• PROC MEANS DATA sales
• BY Month
• VAR Lily SnapDragon Marigold
• output outnew1
• mean(Lily SnapDragon
  Marigold)mean_lily
• mean_SnapDragon
  mean_Marigold
• sum (lily SnapDragon
  Marigold)sum_lily
• sum_SnapDragon
  sum_Marigold
• TITLE 'Summary of Flower Sales by Month'
• RUN

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OUTPUT statement

• The SAS data set created by the output statement
  will contain all the variables defined in the
  output statistic list any variables in a BY or
  CLASS statement, plus two new variables _TYPE_
  and _FREQ_
• Without BY or CLASS statement, the data will have
  just one observation
• If there is a BY statement, the data will have
  one observation for each level of the BY group
• CLASS statements produce one observation for each
  level of interaction of the class variables
• The value _TYPE_depends on the level of
  interactions of the CLASS statement.
• _TYPE_ 0 is the grand total