This script is designed to help understand and validate data by analyzing column attributes and their values. It uses several SAS© procedures for quick and easy data exploration: PROC PRINT to visualize observations, PROC MEANS for summary descriptive statistics, PROC UNIVARIATE for more in-depth statistics, and PROC FREQ to generate frequency tables, which is ideal for identifying unexpected or inconsistent values and validating data quality.
Data Analysis
Type : SASHELP
The data used comes from the internal SASHELP library, specifically the `sashelp.class` and `sashelp.cars` datasets.
1 Code Block
PROC PRINT
Explanation :
Displays the entire `sashelp.class` dataset, listing all columns and all observations by default. Useful for an initial overview of the data.
Displays the entire `sashelp.class` dataset, listing all columns and all observations by default. Useful for an initial overview of the data.
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| 1 | PROC PRINT DATA=sashelp.class; |
| 2 | RUN; |
2 Code Block
PROC PRINT
Explanation :
Displays the first 10 observations (rows) of the `sashelp.class` dataset, using the `obs=10` option to limit the output. This provides a quick overview without displaying all data.
Displays the first 10 observations (rows) of the `sashelp.class` dataset, using the `obs=10` option to limit the output. This provides a quick overview without displaying all data.
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| 1 | PROC PRINT DATA=sashelp.class (obs=10); |
| 2 | RUN; |
3 Code Block
PROC PRINT
Explanation :
Displays the first 10 observations of the `sashelp.cars` dataset, but limits the displayed columns to the 'Make', 'Model', 'Type', and 'MSRP' variables specified in the `VAR` statement.
Displays the first 10 observations of the `sashelp.cars` dataset, but limits the displayed columns to the 'Make', 'Model', 'Type', and 'MSRP' variables specified in the `VAR` statement.
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| 1 | |
| 2 | PROC PRINT |
| 3 | DATA=sashelp.cars (obs=10); |
| 4 | var make model type msrp; |
| 5 | RUN; |
| 6 |
4 Code Block
PROC MEANS
Explanation :
Calculates summary descriptive statistics (by default: N, mean, standard deviation, min, max) for the numeric variables 'enginesize', 'horsepower', 'mpg_city', and 'mpg_highway' from the `sashelp.cars` dataset. Allows for quick identification of central tendencies and value ranges.
Calculates summary descriptive statistics (by default: N, mean, standard deviation, min, max) for the numeric variables 'enginesize', 'horsepower', 'mpg_city', and 'mpg_highway' from the `sashelp.cars` dataset. Allows for quick identification of central tendencies and value ranges.
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| 1 | |
| 2 | PROC MEANS |
| 3 | DATA=sashelp.cars; |
| 4 | var enginesize horsepower mpg_city mpg_highway; |
| 5 | RUN; |
| 6 |
5 Code Block
PROC UNIVARIATE
Explanation :
Generates more detailed descriptive statistics for the numeric variable 'mpg_highway' from the `sashelp.cars` dataset. This includes quantiles, normality tests, moments, information on extreme values, and graphs (if outputted).
Generates more detailed descriptive statistics for the numeric variable 'mpg_highway' from the `sashelp.cars` dataset. This includes quantiles, normality tests, moments, information on extreme values, and graphs (if outputted).
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| 1 | |
| 2 | PROC UNIVARIATE |
| 3 | DATA=sashelp.cars; |
| 4 | var mpg_highway; |
| 5 | RUN; |
| 6 |
6 Code Block
PROC FREQ
Explanation :
Creates frequency tables for the categorical variables 'origin', 'type', and 'drivetrain' from the `sashelp.cars` dataset. Each table presents distinct values, their frequency, their percentage, and their cumulative frequencies/percentages. Very useful for data validation and anomaly detection.
Creates frequency tables for the categorical variables 'origin', 'type', and 'drivetrain' from the `sashelp.cars` dataset. Each table presents distinct values, their frequency, their percentage, and their cumulative frequencies/percentages. Very useful for data validation and anomaly detection.
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| 1 | |
| 2 | PROC FREQ |
| 3 | DATA=sashelp.cars; |
| 4 | tables origin type drivetrain; |
| 5 | RUN; |
| 6 |
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