July 2017
Beginner to intermediate
312 pages
7h 27m
English
Content preview from Python Social Media Analytics
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Sentiment by weekday
We use a similar approach for sentiment to keep the results comparable:
dx = df[df.index > '2013-11-18']ax = dx.groupby(dx.index.weekday)['sentiment'].mean().plot(kind = 'bar', title = 'Average sentiment by day of week')ax.set_xticklabels(['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'])plt.show()
The analysis by the day of the week shows an interesting trend. While the maximum number of comments is on Friday, the most positive sentiment is on Thursday. Based on these two extreme days, we notice a correlation between the number of comments and its sentiment saying that the lesser number ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.