chloemar10/marten-assignment2-methodology.md

## marten-assignment2-methodology.md

      
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              marten-assignment2-methodology.md
            
          
    CHLOE MARTEN 

QUANT HUMANISTS 

SPRING 2018 

05 02 2018
Assignment 2: Document Your Methodology, link to assignment

Introduction

This past week, I further developed the questions I seek to answer as part of my final self-tracking project. Overall, I aim to interpret what my financial data says about me by exploring the following questions:

What do I spend my money on?

Categorical Spends


Where do I spend money?

Geographic Location
Places/Vendors


How has my spending shifted over time?

Increased/Decreased Spending in Certain Categories


How have my financial habits changed over time?

Ratio of Money Spent
Ratio of Money Saved/Invested


Below outlines my methodology to go about answering these questions.
Phase 1 - Data Gathering

In order to answer the above questions, I will need to track my financial transactions. I have decided to take an automated approach in gathering my data since I have limited time on a daily basis. To source my financial transaction data I will be using Plaid (https://plaid.com/products/transactions/), from which I can export JSON files. I am currently waiting on Plaid to grant me development access in order to link to my banking and credit card accounts. In the meantime, I was able to use their sandbox data to get a feel for how it works and setup my workflow. One concern I have about using Plaid is that it may not be able to source all my historical transactions. Once I am able to link my accounts, I need to figure out how far back I can go.
Phase 2 - Data Manipulation

Using the sandbox data Plaid provides, I went through the process of cleaning up the raw JSON data to isolate needed data points. In order to answer my questions, I will need to track the following transaction data:

Date
Amount/Balance
Name
Location
Category

 {
      "amount": -500, 
      "category": [
        "Travel", 
        "Airlines and Aviation Services"
      ], 
      "date": "2018-01-24", 
      "location": {
        "address": null, 
        "city": null, 
        "lat": null, 
        "lon": null, 
        "state": null, 
        "store_number": null, 
        "zip": null
      }, 
      "name": "United Airlines", 
      }, 
    }
This week, I worked on importing a JSON file from Plaid, and then using Jupyter Notebook (http://jupyter.org/) to clean up and identify the needed data points. I got so far as pulling out “amounts” and “date” with the intention to plot them in a line graph.
import json
with open('transactions.json') as f:
    data = json.load(f)

transactions = data["transactions"]
amounts = [t["amount"] for t in transactions]
mydates = [datetime.datetime.strptime(t["date"], "%Y-%m-%d") for t in transactions]
Phase 3 - Data Visualization

I also plan on using Jupyter to organize and plot my data but did not get to it this week. Before plotting, I need to first design the graphs/charts I intend on using to analyze my financial data.
Phase 4 - Data Analysis

The fourth phase is the actual analysis of my data for reflective insights. I imagine there will a bit of trial and error getting the right charts for visualization, which will probably bring me to tweaking phase 2 and 3.