My Data Analysis and Machine Learning Portfolio

 I analyzed my collection of books on the site goodreads.com. I did this using Excel. I used functions and Power Query to clean the data. I used Pivot Tables, Pivot Charts, and Splicers to visualize the data. The data was downloaded from goodreads.com as a csv file. I first checked for, and removed, any duplicate books.  You can expand the pics below by clicking on them.  Power Query At the site goodreads.com, books are placed into categories called "Bookshelves". Each book is placed by default into a "read" Bookshelf or a "to-read" Bookshelf. Each book can also be placed into additional Bookshelves created by the user. Below is an example (screenshot), for one book, from the Bookshelves column: I used Power Query to separate that cell into 4 columns: I  did the same to split the Author column (not shown) into 2 columns: Last Name and First Name. Functions The Default GR Shelf and the Main Shelf columns (seen above) were used for the visualizations. I use...

This is a project that looks at the data from a company called Citi Bike. It is a bike rental company in New York City that allows clients to pick-up a bike at one of its several locations and leave the bike at another location. The data can be found at Kaggle.com.  I determined the following using Excel's Pivot Tables:  1) the start locations frequented most and least 2) the end locations frequented most and least 3) use of service by age group 4) average duration of trip by age group This info may help Citi Bike determine if some stations should be shut down or determine if more bikes should be placed at certain stations. Citi Bike may also use this information to target certain age groups and neighborhoods in its advertising.  The Excel spreadsheet was imported into Google Docs so that a link to the worksheet could be published here: https://docs.google.com/spreadsheets/d/e/2PACX-1vRhSnt-5l2kQL1gwgSrsDpCU9AYOkjDa9VA-X53IuSnk5gasNFq3wiKzzZE3TnTYA/pubhtml As a Google wor...