Austin Median Home Prices and Growth Rates from 2010–2019 by Neighborhood

A question popped into my head this weekend regarding which would be the best neighborhood in which to own property for the next few years. Granted, markets are pretty unstable as of late, so the predictive value of this analysis is less meaningful.

*Data pulled from zillow.

ANALYSIS

This analysis looks into the growth rates YoY broken down by neighborhood. I also further break down the dataframe by only using the December median home price each year.

• My thought behind this was I wanted a time of the year where the market was relatively stable; as you know, buyers tend to buy during the summer months, for multiple reasons such as schools and relocation. December, in my head, was more of a stable month. Less fluctuation, people who bought and sold during December are valuing the house at a true cost, given the reduction in demand.
• I also didn’t want to do the analysis on identifying which month would be the most descriptive.
• And mostly because December is my favorite month and this is my analysis and I’ll do whatever I want with it thank you.

PRO TIPS:

You’ll likely need to install/upgrade plotly, as most of these charts use the plotly library in python

Zillow has zip code data, but it doesn’t seem to work.. the same spreadsheet downloads even when selecting the zip code link. weird

The jupyterthemes package seems to mess up the jupyter toggle bar. More of a side note

PLOTS

Plot 1: I started out just using a seaborn pointplot, but quickly realized there was too many neighborhoods defined as hues for it to be very easy to read. I also wanted something interactive.

Plot 2: I wanted to use the scatter plot by plotly because it’s super cool. If you configure it just right, you can ‘play’ the animation of the plot. However, there is definitely a bug with this package — i kept getting a domain error — something regarding the datatype of the column i was passing into the ```size``` parameter. I tried both ```int``` and ```float``` datatypes but was unsuccessful. So I settled for a standalone plot.

Plot 3: I kind of wanted to see the prices over time/the changes yoy. So I created an interactive line plot.

Plot 4: All of this is fine and dandy but if you want to just see the high level, I figured it’d be best to add in a bar chart in descending order — based on the sum of percent changes.

Plot 5: One more attempt at the animated scatter plot — it’s animated, but the bubbles don’t stay in place, nor do they ‘travel’ smoothly. could be because there are only a few ticks on the x-axis.

Plot 6: A scatter plot with a heat map based on the frequency of annual growth rates. Said differently: how many times was there a 10% growth rate, regardless of year and neighborhood. Also interactive because… I can.

Social Media:

Instagram: @maxbade

Github: @supercoolgetsallthegirlsmax