Converting text files to Excel format is a crucial task for many users, especially when working with automation, data analysis, and reporting. The methods outlined in this article cover various approaches, including manual copying-pasting, using Excel's built-in tools like 'Get Data', online converters, VBA macros, Python libraries, and Large Language Models (LLMs). Each method has its pros and cons, making it essential to choose the best approach for specific needs. For instance, manual methods are suitable for small files with simple structures, while batch processing using VBA macros or Python libraries is ideal for large volumes of complex data. LLMs, like ChatGPT, can efficiently extract structured data from unstructured text but require careful prompt crafting and may generate inaccurate output. Intelligent Document Processing (IDP) tools, such as Nanonets, offer advanced capabilities for extracting structured data from complex documents, ensuring high accuracy and consistency. Ultimately, selecting the right tool or method depends on the size, complexity, and structure of the text data, as well as the desired level of automation and customization.