Python for the .NET developer Transcripts
Chapter: Computational notebooks
Lecture: Notebook intro

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0:00 In this chapter, we're going to talk
0:01 about computational notebooks, and there are a variety
0:05 of options here, but by far the most popular
0:07 are things call Jupyter Notebooks.
0:10 Originally they were called iPython Notebooks
0:12 and that got broadened out, so Jupyter.
0:15 The environment where we run these notebooks
0:17 these days is a place called the Jupyter Lab
0:19 and you'll see that right here.
0:21 We're going to look at two demos
0:23 one that's a simple getting started one
0:26 and one that's more mathematically involved
0:28 this Lawrence differential equations
0:30 that we're looking at here.
0:32 Working with notebooks is incredibly powerful
0:35 for visualizing data and telling stories
0:38 but it turns out that it's a different
0:40 way of programming than a lot of folks
0:42 who are used to working in Visual Studio
0:45 putting together a well factored application
0:47 with different tiers, and all that kind of stuff.
0:50 In order to appreciate these, you really need
0:52 to kind of take a step back and realize
0:55 different people are solving problems
0:57 different problems, with different experiences
1:00 in different styles in Python.
1:02 When I first saw notebooks I thought
1:03 Well, okay, that's cool and all
1:05 but I just don't get it.
1:06 Just write a file, come on, just write a program.
1:09 And as I saw more folks working with it
1:11 I realized for the way they work with Python
1:15 for what Python means to them
1:17 notebooks are perfect.
1:18 And the way that I would like them to do it
1:20 the way I thought that it should be done
1:22 was totally wrong for them.
1:24 There's a really interesting presentation
1:25 it was a keynote, one of the keynote speeches
1:27 at PyCon 2017 by this guy named Jake Vanderplas.
1:31 Jake is an astrophysicist who has become
1:35 a data scientist, there's actually a lot of overlap
1:37 between those things.
1:38 He was at University of Washington in Seattle
1:40 and now he's at Google actually.
1:43 He talked about how Python is a mosaic
1:45 and all the different things that's happening for Python
1:49 not just in the web development space
1:51 but in science, and in many other things.
1:53 And if you watch this talk, I think it'll give you
1:55 a deep appreciation for the different styles of programming
1:59 and problem solving, and a lot of the stuff
2:01 from his world, from Python in science
2:04 these notebooks are perfect for exploring data
2:06 when you don't really even know where you're going
2:08 but you need a great visual aspect to them.
2:11 That's what notebooks are about
2:12 and we're going to see how to work with them
2:14 in Python in this chapter.