Data Sets

I was able to successfully import and manipulate a data set from the internet. I decided to do ice hockey goalie stats, which I found on Kaggle (thank you for the connection during class!). I kept the original data set and used new workbooks as I manipulated them. I decided to sort the data using time on ice, as that is an important fact in the relevance of the stats. The data set was quite large and I think my computer at times had a hard time handling/processing it because it operated quite slowly. 

I feel confident with sorting and filtering data. I was able to use pivot tables and graphs well. I still think I could review and play around with formulas more, but those just take memorizing I think. I think the data sets were quite large so the charts weren't as effective at delivering a point using the data. I tried to compare time on ice and save percentage, which is a key parallel in hockey, with all the data, but it overworked my computer. I decided to do less of the data for a comparison and that worked better. (Hint: manageable amount of data points for charts makes more sense that all  the data anyways).

I was able to find that the average save was 25.203....while the average shot was 27.684...

I did at times feel overwhelmed by the data so trying to locate and fix missing data did not happen for me. 

Otherwise, I found this a very helpful exercise and look forward to continuing to grow in using excel to my advantage! Here is the link to my spreadsheet. I originally was working directly in excel and then uploaded to Google Sheets in order to be able to share it. I am very grateful that I was able to choose my data set because numbers and I normally do not get along, so this helped me engage with the material better. 

1. Locating and downloading data from public sources
2. Being able to import that data into a spreadsheet program (Excel, LibreOffice Calc, Google Sheets)
3. Cleaning up data in the spreadsheet -- reorganizing columns, locating and fixing missing data, making
sense of the various fields in the data
4. Sorting and filtering data
5. Using formulas to manipulate data.
6. Using pivot tables to aggregate and summarize data
7. Creating graphs or other charts to visualize some aspects/trends of the data.