#100DaysOfCode in Python Transcripts
Chapter: Days 82-84: Data visualization with Plotly
Lecture: Other data visualization libraries

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0:01 And, a quick video on some extra pointers
0:04 Plotly is cool but there are others.
0:07 Matplotlib probably the best known.
0:09 You can do awesome stuff with that as well
0:12 and we have a notebook here integrated on our blog
0:15 as showing some more examples.
0:23 We like Bokeh, and we even had a code challenge
0:27 and there were some submissions
0:30 historical exchange rates for BitCoin
0:32 using Bokeh, integrated in Flask.
0:35 By the way that was the challenge,
0:36 to integrate it into Flask.
0:38 Weather data, look at how nice that looks.
0:42 Life expectancies in countries, very cool.
0:45 Versus Australia, so that's Bokeh.
0:48 And actually the Bokeh side is very well,
0:51 I mean look at this, this is awesome, simple
0:54 text is up high.
0:56 Look at these visualizations that's amazing.
0:59 Bokeh has really great documentation
1:02 and user guide so definitely check it out.
1:05 Then we have Seaborn as well, and we had
1:07 a guest post here looking at Marvel data
1:10 which was a code challenge we did
1:12 and this uses Panda in combination with Seaborn
1:16 and again this is a very nice library.
1:20 Look at these visualizations, very nice.
1:25 And one other example, this was one I did.
1:28 Analyzing Brexit data with pandas uses matplotlib
1:32 it integrates very nicely with pandas
1:34 so it's a very powerful combination.
1:38 One cool thing is scatter plots on demographics.
1:47 And that hopefully gives you some extra inspiration
1:50 to start using data visualizations yourself.