<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Csv on Ghafoor's Personal Blog</title><link>http://ghafoorsblog.com/tags/csv/</link><description>Recent content in Csv on Ghafoor's Personal Blog</description><generator>Hugo</generator><language>en</language><managingEditor>noreply@example.com (AG Sayyed)</managingEditor><webMaster>noreply@example.com (AG Sayyed)</webMaster><copyright>Copyright © 2024-2026 AG Sayyed. All Rights Reserved.</copyright><lastBuildDate>Fri, 15 May 2026 13:20:20 +0100</lastBuildDate><atom:link href="http://ghafoorsblog.com/tags/csv/index.xml" rel="self" type="application/rss+xml"/><item><title>Python Crash Debugging</title><link>http://ghafoorsblog.com/courses/google/it-automation-content/it-automation-python-pcert/04-troubleshooting-debugging/04-module/001-python-crash/</link><pubDate>Thu, 13 Nov 2025 12:40:27 +0000</pubDate><author>noreply@example.com (AG Sayyed)</author><guid>http://ghafoorsblog.com/courses/google/it-automation-content/it-automation-python-pcert/04-troubleshooting-debugging/04-module/001-python-crash/</guid><description>&lt;p class="lead text-primary"&gt;
This document provides a practical walkthrough of debugging Python exceptions using the PDB debugger, demonstrating how to analyze KeyError exceptions, investigate variable contents, identify UTF-8 Byte Order Mark (BOM) encoding issues, and implement fixes for CSV file processing.
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&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;While C and C++ programs commonly crash with segmentation faults, Python applications typically fail with unexpected exceptions. Understanding how to debug these exceptions using Python&amp;rsquo;s PDB debugger is essential for diagnosing and fixing runtime errors in Python code.&lt;/p&gt;</description></item><item><title>File Formats</title><link>http://ghafoorsblog.com/courses/ibm/fullstack-content/fullstack-pcert/07-python-datascience/05-module/005-file-formats/</link><pubDate>Fri, 25 Jul 2025 06:51:38 +0000</pubDate><author>noreply@example.com (AG Sayyed)</author><guid>http://ghafoorsblog.com/courses/ibm/fullstack-content/fullstack-pcert/07-python-datascience/05-module/005-file-formats/</guid><description>&lt;p class="lead text-primary"&gt;
This document covers the essential file formats used in data science, such as CSV, JSON, and Excel. It explains their structure, how to read and write them in Python, and the advantages and limitations of each format for data storage and exchange.
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&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;File formats are fundamental to data science, enabling the storage, exchange, and analysis of data. Understanding the structure and use cases of different file formats is crucial for efficient data handling.&lt;/p&gt;</description></item></channel></rss>