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Extract Rows from CSV Where Severity is Blank Using Awk

Learn how to efficiently parse a CSV file to extract rows with a blank `Severity` column and save them to a new file using a simple Bash script with AWK. --- This video is based on the question https://stackoverflow.com/q/76211585/ asked by the user 'MarkoftheKanes' ( https://stackoverflow.com/u/8792221/ ) and on the answer https://stackoverflow.com/a/76215255/ provided by the user 'Renaud Pacalet' ( https://stackoverflow.com/u/1773798/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: parse a csv file and redirect the full row to another file when a specific column is blank Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- Extract Rows from CSV Where Severity is Blank Using Awk In today's data-driven world, working with CSV files is a common task for developers and data analysts. Often, you may find yourself needing to extract specific rows from a CSV file based on certain conditions. A typical scenario is identifying rows where a specific column, such as Severity, is left blank. In this guide, we'll explore how to achieve this using the awk command in Bash. The Problem Suppose you have a CSV file containing multiple columns, and you want to extract rows where the Severity column is blank. This can be crucial for data cleaning processes or when analyzing logs generated from applications. The initial challenge presents itself when you struggle to properly parse the CSV file and retrieve the needed rows. Example of a CSV File Consider the following CSV structure: [[See Video to Reveal this Text or Code Snippet]] In this example, you need to filter out rows like col1txt7 and col1txt15 where the Severity column is blank. Expected Output After processing, your output CSV file should look like this: [[See Video to Reveal this Text or Code Snippet]] The Solution To address this problem, let's break down the solution step-by-step. We will correct any issues in the initial command to make it functional. Step 1: Understanding the AWK Command The awk command is powerful for text processing. Here's how we can modify your initial command to work correctly. Step 2: Modifications Needed Upon reviewing your command, three key issues were found: Field Separator Definition: The original command used -F without specifying a separator. Correction: Use -F, to define the field separator as a comma. Variable Assignment: The command defines a variable as -vpos_sev, but your awk script refers to vpos_sev. Correction: Use the variable pos_sev consistently. Referencing Fields: awk field references need to use $n instead of ${n}. Correction: Refer to the field with $pos_sev. Final Command Taking all the corrections into account, here’s the refined command: [[See Video to Reveal this Text or Code Snippet]] Explanation of the Command awk -F,: This sets the comma as the field separator, allowing awk to properly parse the CSV file. -v pos_sev="$severity_column": This assigns the variable pos_sev to the column number for Severity. !length($pos_sev): This condition checks for rows where Severity is blank (length of the field is zero). "$source_log_file": The source CSV file to be processed. tee -a "$no_severity_logs_file": Appends the output to the specified results file. Conclusion In scenarios where you need to extract rows based on specific conditions in a CSV file, utilizing awk in a Bash script can save you time and enhance your data analysis efforts. By correctly modifying the command to account for field separation and variable usage, you can easily obtain the desired results. Feel free to reach out if you have any questions or need further assistance with CSV processing using Bash!