csv may not always be the best with which to work. Even though many editing features are out there, not all offer a simple solution. We developed DocHub to make editing easy, no matter the document format. With DocHub, you can quickly and easily cut off frame in csv. In addition to that, DocHub gives a variety of other functionality such as form generation, automation and management, sector-compliant eSignature tools, and integrations.
DocHub also enables you to save time by producing form templates from documents that you utilize regularly. In addition to that, you can take advantage of our numerous integrations that allow you to connect our editor to your most used apps easily. Such a solution makes it quick and easy to deal with your documents without any delays.
DocHub is a handy feature for personal and corporate use. Not only does it offer a extensive suite of capabilities for form creation and editing, and eSignature implementation, but it also has a variety of features that come in handy for producing multi-level and straightforward workflows. Anything imported to our editor is saved safe according to major field requirements that safeguard users' data.
Make DocHub your go-to option and simplify your form-based workflows easily!
DB in 60 seconds I wanted to ingest a bunch of CSV files directly from Jeff sackmanamp;#39;s awesome tennis data set on GitHub now duck DB supports Wild Card matching files but we canamp;#39;t use that here as itamp;#39;s not a file system so we just get back at 404. instead we need to create a list of all the file names and pass those to the read CSV function lucky for us the names are all in the format ADP underscore matches underscore yeah so if we can create a list of years then weamp;#39;ll be golden the generate series function lets us do this so you can see here we can pass in 1968 to 2023 and we get back a list of all those years we can then use the list transform function pass in the generate series and then we get a Lambda where we can map over that and construct some file names finally letamp;#39;s put all that together and create a table using the read CSV Auto function and then if we give it a few seconds we are done