Weekly Challenges

Solve the challenge, share your solution and summit the ranks of our Community!

Also available in | Français | Português | Español | 日本語
IDEAS WANTED

Want to get involved? We're always looking for ideas and content for Weekly Challenges.

SUBMIT YOUR IDEA

Challenge #36: Data Cleansing Extract Authors

grazitti_sapna
17 - Castor

Hi ,Please find my solution for the given challenge.

Sapna Gupta
terry10
11 - Bolide

This exercise is very familiar; I know I've done this it before, perhaps as part of a training.

 

Spoiler
ss 36.PNG
Sylvana
8 - Asteroid

My solution.

cc000072
8 - Asteroid

Here is my solution

Spoiler
WeeklyChallenge_Ryohei_36.JPG
NaiLo
8 - Asteroid

It took me a while to figure out why I wasn't getting the same number of records as the solution; The "official" solution uses a method that filters out articles that don't have any authors listed 🙂

izamryan
8 - Asteroid

I seem to be doing these challenges in more steps than some of the other solutions ... still need to work on my optimising!

 

 

Spoiler
asdf
izamryan_0-1590162707465.png

I used 2 RegEx tools to slice out the PMID's and then the FAU's.
(PMID).*(\d{8}).*
(FAU - )(.*)

I then used Multi-Row formula tools to "fill" the rows - you need to do this step otherwise you can't associate the PMID's to the FAU's.

Using the Unique tool I then extracted out which are the unique combos of PMID/FAU.
A little Filter tool to clean up the data.

I then build out the column header for the Cross Tab so it can pivot the data

deviseetharaman
11 - Bolide
Spoiler
 
jarrod
ACE Emeritus
ACE Emeritus

was thinking about it too hard. came up with a simpler solution

Spoiler
jarrod_0-1590766117221.png

 

ALexAn
8 - Asteroid
Spoiler
Spoiler
Capture.PNG

I know I have used way too many tools! and the guess, for number of columns needed is burdening my workflow. Will work on optimizing .

vaishabhinav_iitm
6 - Meteoroid
Spoiler
vaishabhinav_iitm_1-1591044645881.png