I loved it and it was very detailed.

(I've learned to be a purchaser of my money, not a book-in-a-bend) 60%. We've talked about deeper than any Python data analysis book, but the sentence is not smoother, so we feel it's harder. Actually. I bought it from a book that was written about the philosophy and experience of the author. Just. I think it's better to have a translation of the one that we're going to use in the next video. The "max" of the "mix" homeline is described in detail. We're looking at the number of times it's

It was good to understand the interest in Big Data, the technology that was involved in the growing industry, through the theories and applications of data analysis in the fourth Industrial Revolution. I'd like to recommend you to readers who are interested in analyzing data.

I was studying Python and then I bought an AI book and I gave up on it. It's overlooked the importance of all of artificial intelligence. And then I went to the ssns and I bought it, and it's nice to learn from the character. And the explanation is neat, and the coding example is now being heated.

I picked a book that looked like it was a pretty easy book to look at during the course of the video, but it was hard to deal with the changing data processing process. And then it looked like it was very organized, and I bought it at the end of my mind, and we read it all the way to Gumpi, Pandane, MattPlip. I like the easy way to describe the difficult ones, the per-pebe library, and it's a good place to be able to learn naturally by doing examples. I liked the middle-class applications. Data

I couldn't find a proper Python data analysis, but it seems to be a very easy and faithful book. And I particularly like how we explained the difficult different types of functions, and I like having them code right away. If you have any questions for him, if you have time for some real-life practice, please give him a follow-up.