#100DaysOfCode in Python Transcripts
Chapter: Days 58-60: Twitter data analysis with Python
Lecture: Identify the most popular tweets
Login or
purchase this course
to watch this video and the rest of the course contents.
0:00
And let's see, in particular,
0:03
what tweets were most popular.
0:05
And I'm going to first use a list comprehension,
0:08
which I showed you on Day 16,
0:10
to exclude the retweets.
0:15
And a retweet is easy to see
0:18
because it always starts with a RT.
0:21
Next, let's get the top 10.
0:25
And for that I need to do some sorting.
0:33
Okay, so how does sorted work?
0:35
You give it a sequence, which is the list of tweets
0:38
and we use the key argument that can take a function
0:41
or callable and we give it a lambda,
0:43
which is basically a just a simple function in a one-liner.
0:46
And we give it a tweet,
0:47
and then it will average
0:49
of the number of likes and retweets.
0:51
That's sorts the list of tweets by highest average.
0:55
And if you then do it reversed=True,
0:57
you get the highest at the top.
0:59
Alright?
1:00
Got already with this format.
1:02
So, let's try the for loop to make it nicer.
1:05
First, I'll do a specify a format,
1:09
which I will then use for every row.
1:15
I got a column of five.
1:19
Separator...
1:23
Another column of five...
1:26
And the text.
1:28
You can use f-strings.
1:30
When I was preparing this notebook,
1:31
I will still using the older formats,
1:33
so I'm going with that for now.
1:36
Besides, if you're not on 3.6, you might still need it.
1:40
I use some nice icons.
1:44
Then I do a dashed line
1:48
which I can just say
1:50
dash times 100
1:52
and then the loop.
1:53
For tweet in top 10,
1:57
I'm going to print, format, format,
2:01
and then I can just fit in those keyboard arguments
2:04
likes...
2:08
and just for the fun of it,
2:09
let's use a return icon instead of the new line.
2:14
Oops.
2:19
And I have to close this.
2:21
Look at that.
2:22
Our first tweet was the launch of our co-tennis platform.
2:25
And the second one was our Flash course, etc, etc.
2:30
So we have the likes, number of retweets
2:33
and the text of the tweets.
2:35
So here you already see the benefits
2:37
of doing a bit of data analysis to explore your data set.
2:40
And it's not taking that much of code.
2:43
Once we have the data loaded in, it's fairly easy.
