✅ All About PROC SUMMARY in SAS: A Comprehensive Guide with Practical Examples

📘 Introduction

PROC SUMMARY in SAS is a powerful procedure used to generate summary statistics for numeric variables. It is often considered functionally equivalent to PROC MEANS but with more flexibility in generating customized outputs and silent summaries.

In this guide, you'll learn:

• Complete syntax of PROC SUMMARY
• All available options and statements
• Grouped examples
• How it differs from PROC MEANS
• Output datasets and tips

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🛠 Syntax of PROC SUMMARY

PROC SUMMARY <options>;
  VAR variable(s);
  CLASS variable(s);
  BY variable(s);
  OUTPUT OUT=dataset <stat-options>;
RUN;

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⚙️ Common Options in PROC SUMMARY

Option	Description
DATA=	Specifies the input dataset
N	Count of non-missing values
MEAN	Mean or average value
STD	Standard deviation
MIN	Minimum value
MAX	Maximum value
SUM	Total sum
MAXDEC=	Maximum number of decimals
NWAY	Outputs only rows with all CLASS variables present
CHARTYPE	Adds a TYPE variable to output

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📄 Statements in PROC SUMMARY

Statement	Purpose
VAR	Specifies numeric variables to analyze
CLASS	Group summary statistics by categorical variables
BY	BY-group processing; data must be sorted
OUTPUT	Outputs summary statistics to a dataset

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✅ PROC SUMMARY vs PROC MEANS

Feature	PROC MEANS	PROC SUMMARY
Displays output	Yes (default)	No (unless PRINT)
Flexibility	Moderate	High
Use in production	For display/review	For data pipelines
Output dataset	Optional	Common

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🧪 Examples of PROC SUMMARY

Example 1: Basic Summary Statistics

proc summary data=sashelp.class print;
run;

Note: Use PRINT to display output.

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Example 2: Specifying Variables

proc summary data=sashelp.class print;
  var height weight;
run;

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Example 3: Using CLASS Statement

proc summary data=sashelp.class print;
  class sex;
  var height weight;
run;

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Example 4: Creating Output Dataset

proc summary data=sashelp.class n mean maxdec=1;
  class sex;
  var height weight;
  output out=summary_stats;
run;

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Example 5: Custom Output Variable Names

proc summary data=sashelp.class;
  class sex;
  var weight;
  output out=summary_data
    mean=mean_weight
    max=max_weight
    min=min_weight;
run;

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Example 6: Using BY Statement (sorted data)

proc sort data=sashelp.class out=sorted;
  by sex;
run;

proc summary data=sorted print;
  by sex;
  var height;
run;

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🔄 Output Options in PROC SUMMARY

You can customize the summary stats by combining the following keywords in the OUTPUT statement:

Keyword	Description
N=	Assigns name to N (count)
MEAN=	Assigns name to mean
STD=	Standard deviation
SUM=	Assigns name to sum
MIN=	Assigns name to minimum
MAX=	Assigns name to maximum

Example:

output out=myout n=n_obs mean=avg std=stdev;

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🧠 Tips for PROC SUMMARY

• Always use PRINT if you want to display results.
• Use NWAY if you need only fully classified combinations.
• Use meaningful output variable names with =.
• Great for creating reusable summary datasets.

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📦 Summary Table

Feature	Description
Primary Use	Summary statistics
Shows Output	No (by default)
Supports Groups	Yes (CLASS or BY)
Custom Output	Yes (OUTPUT statement)
Output Dataset	Yes
Flexible Output	Highly customizable

 

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📆 SAS Date Interval Functions Explained: INTNX vs INTCK with Examples

Date manipulation is a core part of data analysis in SAS. When working with time series, financial models, or scheduling, calculating intervals and moving dates is essential. That’s where SAS functions like INTNX and INTCK come in.

In this blog post, we will explore:

• What are INTNX and INTCK functions?
• Complete syntax and arguments
• Important options
• Practical real-life examples
• Comparison and use-cases

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🔍 What is INTNX in SAS?

The INTNX (Interval Next) function adds a specified number of intervals to a date or datetime and returns a new date.

📌 Syntax:

INTNX(interval, start-from, increment <, 'alignment' <, method>>)

✅ Arguments:

Parameter	Description
interval	The type of interval to add (e.g., day, week, month, year).
start-from	The base SAS date or datetime value.
increment	Number of intervals to move forward or backward.
'alignment' (optional)	'BEGINNING', 'MIDDLE', 'END', 'SAME' (default is 'BEGINNING').
method (optional)	'S' (simple), 'C' (concurrent), or 'E' (end of period alignment).

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🧪 INTNX Examples

Example 1: Add 3 months to a date

data result;
  new_date = intnx('month', '01JAN2024'd, 3);
  format new_date date9.;
run;

Output: 01APR2024

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Example 2: Move 2 years back and align to end of year

data result;
  year_end = intnx('year', '15JUL2024'd, -2, 'END');
  format year_end date9.;
run;

Output: 31DEC2022

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Example 3: Use 'SAME' alignment

data result;
  same_date = intnx('month', '10JAN2024'd, 1, 'SAME');
  format same_date date9.;
run;

Output: 10FEB2024

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🧠 Pro Tip:

You can use INTNX with time intervals too, like 'hour', 'minute', 'qtr', 'dtday', etc.

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⏳ What is INTCK in SAS?

The INTCK (Interval Check) function calculates the number of intervals between two dates or datetimes.

📌 Syntax:

INTCK(interval, start, end <, 'method'>)

✅ Arguments:

Parameter	Description
interval	Type of interval (e.g., day, week, month, year).
start	Starting SAS date or datetime.
end	Ending SAS date or datetime.
'method' (optional)	'C' (continuous), 'D' (discrete), or 'S' (simple)

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🧪 INTCK Examples

Example 1: Count number of months between two dates

data result;
  month_diff = intck('month', '01JAN2023'd, '01JUL2023'd);
run;

Output: 6

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Example 2: Days between two dates

data result;
  day_diff = intck('day', '15MAR2023'd, '20APR2023'd);
run;

Output: 36

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Example 3: Count number of years using 'CONTINUOUS' method

data result;
  year_cont = intck('year', '31DEC2019'd, '01JAN2021'd, 'C');
run;

Output: 2

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🔄 INTNX vs INTCK in SAS

Feature	INTNX	INTCK
Purpose	Move a date forward/backward	Calculate number of intervals
Returns	Date or datetime value	Integer (count of intervals)
Optional Arg	Alignment ('BEGINNING', etc.)	Method ('C', 'D', 'S')
Use Case	Scheduling future/past events	Analyzing gaps/durations

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📘 Common Intervals in SAS

Interval Type	Example	Description
day	'day'	Daily interval
week	'week'	Weekly interval
month	'month'	Monthly interval
qtr	'qtr'	Quarterly interval
year	'year'	Yearly interval
dtday	'dtday'	Datetime day interval
hour	'hour'	Hour interval

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🛠 Real-World Use Cases

🧾 1. Loan Payment Schedules

due_date = intnx('month', start_date, 12, 'END');

📊 2. Monthly Sales Comparison

month_diff = intck('month', previous_sale, current_sale);

🧑‍💼 3. Employee Tenure Calculation

years_worked = intck('year', hire_date, today());

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🎯 Tips for Using INTNX and INTCK

• Always format the date with FORMAT datevar DATE9. or DATETIME20..
• Use 'SAME' alignment when you want the exact day repeated.
• Prefer 'C' method in INTCK for financial year or continuous interval calculations.

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🧾 Summary

Function	Purpose	Returns	Key Argument
INTNX	Add intervals to a date	Date	'alignment'
INTCK	Count intervals between two dates	Integer	'method'

Both INTNX and INTCK are indispensable tools in time-based analysis in SAS. Whether you’re calculating tenure, creating forecasts, or aligning schedules, mastering these functions will significantly enhance your date handling capabilities.

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Mastering the INPUT and INFILE Statements in SAS: A Beginner's Guide with Examples

Introduction

If you're just starting with SAS programming, one of the most essential skills you'll need is the ability to read raw data files into SAS datasets. This is where the INPUT and INFILE statements come into play. These two statements are fundamental when you're working with external data sources like .txt, .csv, or .dat files.

In this post, we'll explore:

• What the INFILE and INPUT statements do
• Syntax and options
• Step-by-step examples
• Common errors and best practices

Whether you're preparing for the Base SAS Certification or learning SAS for data analytics, this guide will help you understand how to efficiently read data into SAS.

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What is the INFILE Statement in SAS?

The INFILE statement is used to tell SAS where to find your external data file. It defines the file path and other important file-reading options such as delimiters and record length.

Syntax:

INFILE 'file-path' <options>;

Example:

INFILE 'C:\Data\students.txt' DLM=',' FIRSTOBS=2;

• DLM=',' — Specifies the delimiter as a comma.
• FIRSTOBS=2 — Tells SAS to start reading from the second row (often used to skip headers).

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What is the INPUT Statement in SAS?

The INPUT statement tells SAS how to read the data — the structure, variable names, types, and formats. It works hand-in-hand with the INFILE statement to read external files into a SAS dataset.

Syntax:

INPUT var1 $ var2 var3;

• Use $ for character variables.
• No $ is needed for numeric variables.

Example:

INPUT Name $ Age Height;

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Example: Reading a CSV File Using INFILE and INPUT

Let's say you have a file named students.csv with the following data:

Name,Age,Score
Alice,22,88
Bob,23,91
Charlie,21,85

SAS Code:

DATA student_data;
    INFILE 'C:\Users\YourName\Documents\students.csv' DLM=',' FIRSTOBS=2;
    INPUT Name $ Age Score;
RUN;

PROC PRINT DATA=student_data;
RUN;

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More on Input and Infile Statement - 

1. 

Data <Dataset Name>

Infile 'Location\Filename' DLM=<delimiter> Firstobs=<Starting Position>;

Input <Variable Name and formats>;

run;

2. 

FileName <Name/Alias for File> 'Location/FileName';

Data <Dataset Name>

Infile above defined Name/Alias for File  DLM=<delimiter> Firstobs=<Starting Position>;;

Input <Variable Name and formats>;

run;

Here FileName is a Global Statement

For Example - I have a Text file on my location - /home/../New Folder/New Text Document.txt with Credit Card Number and Spend information, to import that

1.

Data datahark;

infile  '/home/../New Folder/New Text Document.txt' Firstobs=2;

INput cc Spend;

run;

2.

Filename CC '/home/../New Folder/New Text Document.txt';

Data datahark;

infile  cc Firstobs=2;

INput cc Spend;

run;

Both of above code will import the File and Give the same output - 

Important Options in INFILE

Option	Description
DLM=','	Sets the delimiter (comma, space, tab, etc.)
FIRSTOBS=n	Reads from the nth record (skip headers)
DSD	Handles missing values and quotes in CSV
MISSOVER	Prevents reading the next line if data is missing
TRUNCOVER	Avoids errors when fewer columns exist than expected

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Reading Space-Delimited Data

DATA test_scores;
    INFILE 'C:\Data\testdata.txt';
    INPUT StudentID $ Subject $ Score;
RUN;

This reads a space-separated file without needing DLM.

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Common Mistakes to Avoid

1. File Not Found: Always use the full path or set the correct working directory.
2. Wrong Delimiter: Use the correct delimiter option in INFILE.
3. Incorrect Data Types: Forgetting to use $ for character variables.
4. Header Row Issues: Use FIRSTOBS=2 if your data has a header.

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Best Practices

• Use DSD and FIRSTOBS=2 for clean CSV handling.
• Always validate data using PROC PRINT after loading.
• Modularize your code: Keep data import in a separate step.

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