sas infile csv pass through comma in quote

Lussy04

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23-01-2025

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This article tackles a common challenge in SAS data import: correctly handling commas embedded within quoted fields in CSV files. The INFILE statement, with its various options, provides the tools to manage this effectively. We'll explore several approaches, demonstrating how to seamlessly import data even when commas are part of the quoted text. This is crucial for accurately importing data containing addresses, names with commas, or any text fields where commas naturally occur.

Understanding the Problem

CSV (Comma Separated Values) files use commas to delimit fields. However, when a field itself contains a comma, it needs to be enclosed in quotes to avoid misinterpretation. For example:

"John Doe, Jr.", 123 Main St, Anytown, CA

Without proper handling, SAS might interpret this as four fields instead of three. This article provides solutions to this common data import challenge.

The INFILE Statement and Key Options

The core of the solution lies within SAS's INFILE statement. Several options are key to handling commas within quotes:

• DSD (Delimiter Separated Data): This option tells SAS that the data is delimited (separated) by commas. It's crucial for CSV files.

• MISSOVER: This option instructs SAS to proceed to the next input line if an invalid data record is encountered. It helps to skip flawed rows instead of stopping the entire process. Useful when dealing with potentially problematic data.

• QUOTE="": This explicitly defines the quote character as a double quote ("). While often the default, specifying it explicitly ensures clarity.

Method 1: Direct INFILE Statement with Options

This straightforward method incorporates the options discussed above directly into the INFILE statement. Here's how you would structure your SAS code:

proc import datafile="your_file.csv" 
	out=work.your_dataset
	dbms=csv
	replace;
	getnames=yes;
	datarow=2; /* Adjust if header row exists */
run;

Remember to replace "your_file.csv" with the actual path to your CSV file and work.your_dataset with your desired SAS dataset name. The datarow=2 option skips the header row if present; adjust accordingly. This method directly utilizes SAS's built-in CSV handling capabilities.

Method 2: Using the QUOTE= Option for More Control

For more complex scenarios or specific quote character requirements, you have more explicit control using the QUOTE= option within the INFILE statement:

data your_dataset;
  infile "your_file.csv" dsd missover quote="""" firstobs=2;  /* firstobs skips header if needed*/
  input variable1 $ variable2 $ variable3 $;
run;

This approach explicitly defines the quote character and handles potential errors with MISSOVER. You would replace placeholders for variable names with the actual names from your CSV file.

Handling Different Quote Characters

While double quotes are standard, some CSV files might use single quotes. Adapting the code is simple: just change the QUOTE= option accordingly:

data your_dataset;
  infile "your_file.csv" dsd missover quote="'" firstobs=2;
  input variable1 $ variable2 $ variable3 $;
run;

This shows flexibility for diverse data formats.

Advanced Scenarios and Troubleshooting

• Escaped Quotes: If your CSV data contains double quotes within quoted fields, you might need more sophisticated techniques involving regular expressions or other string manipulation functions within SAS to correctly handle such escaped quotes.

• Inconsistent Quoting: Inconsistent use of quotes in your CSV file will likely lead to errors. Data cleansing or pre-processing might be necessary before importing the data into SAS. Checking your data source for inconsistencies beforehand is highly recommended.

• Error Handling: For robust error handling, consider adding checks within your SAS code to identify and flag potentially problematic rows or values during the import process. This allows for manual review or more advanced error correction methods.

Conclusion

Successfully importing CSV files with commas in quoted fields using SAS's INFILE statement requires understanding and applying the appropriate options. By using DSD, MISSOVER, and explicitly defining QUOTE=, you can effectively handle most common scenarios. Remember to always inspect your data for inconsistencies to ensure accurate and reliable results. The methods and explanations above should equip you to manage these data import challenges efficiently.