## Parallel Coordinates Plot using Plotly

Over the holiday season I heard several discussions on which charities are best to donate to and why some are better than others. With this in mind, I thought it would be interesting to examine the stats which set one charity over another and find a way to visualize these in an effective manner. With some help from Charity Navigator, I was able to source and collect the appropriate information and thought it a great time to finally give Plotly a go.

## Multiple Linear Regression to Predict Consumer Spending

As in the last post, here's some more work in excel with economic variables. This time I use value forecasts of 30y mortgage, unemployment, and personal income rates, figured in a similar manner as before (annual growth/change rates - 10y moving averages) to predict future levels of personal consumption expenditures. I run a multilinear regression analysis to forecast PCE based upon the three independent variables and end up with some pretty strong results and an adjusted R-squared of .974.

## Forecasting Economic Time-Series Variables in Excel

I grabbed some economic data from FRED and attempt to forecast future values for each variable using Excel. Econ variables of focus for this project include GDP, CPI, and the unemployment rate for the U.S. This was originally done for my Macro-econometrics class and provided me some nice time with Excel which I admittedly use too little.

## Character Co-occurrence Network Diagram w/ NetworkX in Python

Being a big fan of fantasy novels, I've always had an interest in how characters within books with massive character lists all interweave and connect together. I've also had interest for awhile now in visualizing some type of complex network with networkX in Python. Oathbringer is the most recent book from Brandon Sanderson's Stormlight Archive series and it was a perfect option for me to combine both of these interests. The following is the code I used to parse through the etext of the novel and create a character co-occurence network diagram. Although certain decisions made throughout the process may not be perfect for representing direct 'co-occurrences', I found the resulting visual to be an interesting look at relationships seen throughout the book.

## Nightingale Rose in R

Summary: I recently tracked my daily coffee consumption and thought it would be interesting to find a fun way to visual it. After some exploration of options in R, I decided to give a Nightingale Rose Diagram a try.

## Lyric Analysis

An assortment of word clouds I made from lyrics I scraped for a school project. Size of each word is relative to frequency of usage by the artist in (up to) 150 of their most recent songs. Mount Eerie references nature a lot while Aesop Rock just references A LOT of things. Harry and the Potters, well... .