Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.
Hi,
I'm currently looking for a way to figure out which #s and which @s are most commonly tweeted by a single user, (ideally using PowerQuery).
Two examples below, most @s and #s will be followed by a blank space or a form of punctuation, perhaps this will help with seperating them out?
"Opening remarks at this afternoons @Cabinet meeting @WhiteHouse.https://www.pscp.tv/w/bMikWjFvTlFsTFJub1dwUXd8MXZBR1JNallOUVlLbPB_wB7ULYiT7F9_1VC4rG8Q-NHPcbdGlhYzet...''
"Check out @SecondLady Karen's new initiative! #ArtTherapyhttps://twitter.com/secondlady/status/921089107341688833''
Some help would be greatly appreciated!
@Anonymous ,
Are you trying to scrapy the twitter home page data and then split something in the data? I'm afraid your requirement is not so clear, could you clarify more details about the requirement?
Regards,
Jimmy Tao
Hi Jimmy,
Thanks for picking this up!
I have a CSV file containing a single twitter users tweets from 2017. All the text from the tweets is in a single column in this file. I've already created a word cloud with this info to show the most frequently used words in the user's tweets, but I'd like to be able to show who they @ the most, and the same for hashtags.
An example of a tweet in the text column is below.
"Great news @SecretaryAcosta!https://twitter.com/secretaryacosta/status/925044690864476160"
I'd need to duplicate the text column, then split everything before and after the @SecretaryAcosta in the above example, to leave me with a column just with:
@example
@example
@example2
@example3
@example3
@example3
I'd then duplicate the original column a second time to do the same with hashtags. How would I achieve this?
Kind regards,
Jordan
Covering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City
Check out the April 2024 Power BI update to learn about new features.
User | Count |
---|---|
111 | |
100 | |
80 | |
64 | |
58 |
User | Count |
---|---|
146 | |
110 | |
93 | |
84 | |
67 |