Get Inspire insights from former attendees in our AMA discussion thread on Inspire Buzz. ACEs and other community members are on call all week to answer!

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 #16: Parsing Out the New-line Character

Emil_Kos
17 - Castor
17 - Castor

Hi,

 

Sharing my solution.

 

Very quick and fun challenge. 

 

Spoiler
Challenge_16_Emil_Kos.PNG
DavidLane
8 - Asteroid

I have found the standard formula tool to be significantly faster than the data cleansing tool when you only need to do one task like remove a specific character, though clearly it is not quite as user friendly.

Not a big deal with this small dataset, but might be useful to bear in mind when dealing with GBs of data in a workflow.

DMContente
8 - Asteroid

Here's my solution

SideSweep7
7 - Meteor

This problem seemed oddly familiar...

 

Spoiler
SideSweep7_0-1589917159979.png

 

edavilac
8 - Asteroid

My solution attached.

 

Spoiler
Challenge_16_edavilac.PNG
powell
5 - Atom

Here's my solution

jarrod
ACE Emeritus
ACE Emeritus

Nice use case for regex_replace

Spoiler
jarrod_0-1590172446655.png
from ayx import Alteryx
import pandas as pd

poem = Alteryx.read('#1')

poem['Field_1'] = poem['Field_1'].replace('\n',' ',regex=True) 
poem['Field_3'] = pd.to_datetime(poem['Field_3'])
poem = poem.rename(columns={'Field_1':'Poem','Field_2':'Poem_ID','Field_3':'Poem_Read_Date'})


Alteryx.write(poem,1)

#SnakingMyWayThruChallenges 

vorod
5 - Atom

Learned how to use the datetime tool

namrad
5 - Atom

Completed my second weekly challenge 🙂

deviseetharaman
11 - Bolide
Spoiler