#100DaysOfCode in Python Transcripts
Chapter: Days 58-60: Twitter data analysis with Python
Lecture: Identify the most popular tweets
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And let's see, in particular,
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what tweets were most popular.
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And I'm going to first use a list comprehension,
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which I showed you on Day 16,
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to exclude the retweets.
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And a retweet is easy to see
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because it always starts with a RT.
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Next, let's get the top 10.
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And for that I need to do some sorting.
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Okay, so how does sorted work?
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You give it a sequence, which is the list of tweets
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and we use the key argument that can take a function
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or callable and we give it a lambda,
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which is basically a just a simple function in a one-liner.
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And we give it a tweet,
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and then it will average
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of the number of likes and retweets.
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That's sorts the list of tweets by highest average.
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And if you then do it reversed=True,
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you get the highest at the top.
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Alright?
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Got already with this format.
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So, let's try the for loop to make it nicer.
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First, I'll do a specify a format,
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which I will then use for every row.
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I got a column of five.
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Separator...
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Another column of five...
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And the text.
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You can use f-strings.
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When I was preparing this notebook,
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I will still using the older formats,
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so I'm going with that for now.
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Besides, if you're not on 3.6, you might still need it.
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I use some nice icons.
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Then I do a dashed line
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which I can just say
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dash times 100
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and then the loop.
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For tweet in top 10,
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I'm going to print, format, format,
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and then I can just fit in those keyboard arguments
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likes...
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and just for the fun of it,
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let's use a return icon instead of the new line.
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Oops.
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And I have to close this.
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Look at that.
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Our first tweet was the launch of our co-tennis platform.
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And the second one was our Flash course, etc, etc.
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So we have the likes, number of retweets
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and the text of the tweets.
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So here you already see the benefits
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of doing a bit of data analysis to explore your data set.
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And it's not taking that much of code.
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Once we have the data loaded in, it's fairly easy.