17|EXCEL – Cleaning Government Data

[Chase_Tucker]

Challenge17_PPP_Loans_To_Utah_Businesses (1).xlsx (998.9 KB)
This was an awesome challenge. It was a good refresher on pivot tables!

[Kevin_Garrett]

Challenge17_PPP_Loans_To_Utah_Businesses.csv (1.4 MB)

[Brandon_Rice]

Challenge17_PPP_Loans_To_Utah_Businesses.csv (7.2 KB)

[Kaleb_Ashdown]

[britbraatz]

That was awesome! I’ve never used Pivot Tables. There were definitely different ways I cleaned up the data but I felt so powerful organizing the data to answer the questions. It makes me picture I get to do that for a boss and watch as their jaws drop!
Challenge17_PPP_Loans_To_Utah_Businesses.csv (11.7 KB)

[Allison_Richardson]

1. To replace variations of Salt Lake to Salt Lake City, I used CTRL+H to FIND and REPLACE Salt Lake with Salt Lake City.

2.To removed data without NAICS code, I filtered the NAICS column to only show the “Blank” fields. Then I selected all and deleted them.

3. finally, to get the answers in the pivot table, I summed the count of LoanRange and then alternatively added business type and NAICS description to find the answers
   
   

[Logan_Doles]

This was a nice challenge! It taught me a few new things I could do with excel!
Here is my file with solutions, it may not work as the file was throwing all sorts of errors at me.