Scott Numamoto
2 min readNov 3, 2016

RubyEdge came about because I had some issues with Ledgers.

I wanted to be able to interact with my data also on my computer. My initial solution to this was exporting through the .csv format. This method did work, but involved jumping through a lot different hoops, such as copy and pasting, exporting to the computer through Pushbullet, and creating a .csv, and finally opening with excel. In other words, this was a pain. I wanted a way to be able to interface on both mobile and desktop and iterate more quickly outside the Android environment. With a desire to delve beyond front-end web development, I set out to port Ledgers to web through Ruby on Rails.

First though, I had to learn a whole new language and framework. The resource I found most useful was Daniel Kehoe’s 2 free books. They gave a very in-depth and detailed explanation of not just what to do to build a rails application, but why. His commentary on the philosophy behind rails and the general development process were super helpful. After going through other tutorial and guides, I was able to create their finished product, but didn’t understand enough to deviate and combine their building blocks in my own way.

One of the particular challenges I found with using Ruby on Rails was the database system. I had trouble with debugging as I didn’t correctly understand the encapsulation. Examining some different examples and brushing up more with Kehoe’s database specific questions got me over the hump. With the transition to hosting on Heroku rather than locally on the device, I aded Google account authentication for multiple users.

RubyEdge, as it currently stands, is a working proof-of-concept. The UI is in its initial stages and has a long way to go. I’m most excited about the possibilities with data analysis. Initial steps would be replicating and automating the analysis I used excel to do — graphing the balance against time, comparing monthly spendings, etc. Looking deeper, it’d be interesting to see a breakdown of my spendings. What proportion goes where? What’s the frequency of my spendings? How does this change during midterm season or my location (particularly outside of Berkeley)?

Though not directly applicable to this Ruby on Rails site, one of my inspirations for data analysis is this data visualization of machine learning through R3. I love how interactive the data is and changes very specifically with the focus of the text. With result of my statistical computing class, hopefully I can a report leveraging the same frameworks.

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