You are a life saver. I was having trouble completing an assignment for my engineering course and I was stuck for hours. But this video literally fixed my problem. Thank you so much!!!
very helpful! thank you! with the help of this video I was able to decompose a txt file containing radar data sampled from a rocket. It had 1662 rows of datapoints across 16 columns of different datatypes. was able to make some nice plots. Hopefully I can impress the lecturer tomorrow :D
It depends on what you want to store it as and how it was stored to begin with. Usually images have a type like uint8 for each color channel, with 3 or 4 channels. How that was translated in your table changes the way to do this.
Oh, I think you previously asked about converting a matrix to a table. Checkout my other tutorial here to see a table made manually: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-SbR5_i4UY0w.html The short answer is that you probably want to just make it column by column like I show in that tutorial. That said, if you want to directly do what you asked about below, array2table() will do the job.
Haha, I've got bad news for you about python - huge portions of its internal treatment of objects is similar to matlab's. Actually, numpy in particular uses almost identical methodology to matlab as far as I can tell. Not surprising, they're optimizing for the same things. To really find a language that doesn't do the same things under the hood, I think you need to go to something god-awful like javascript. If you want the same typeless behavior as python lists, you can use cell-arrays. You pay a huge speed penalty for them though. Tables are really an attempt to bring in relational databases into matlab - it borrows techniques from SQL for it. In python, you will find identical functionality and limitations in pandas in my experience, except pandas like to break for fun periodically. Those python libraries are not so list like in my experience, but I guess it's in the eye of the beholder. Happy coding :)
