Comp 151 Makeup Project

This project can replace any project grade other than project 8

Due: Friday May 3rd at 11:59pm


Summary: Several people have approached me because the underestimated or procrastinated on an assignment earlier in the semester. In this project you you can make up for an assignment *except* project 8 which is larger than this one. In this project you will examine home affordability in each state using the most recently available data (2016.

Because this is a Makeup project, Project 8 will run concurrently with this project

Description:

 
Grab the Median Income by State data that we've used previously.
Then get Housing and property tax data spreadsheet.



Houses are considered affordable if they cost no more than 3 times household income. Lets use the data in these two spreadsheets to see what the housing affordability is across the states. 

For each state, divide the Average home price by the median income. Then use plotly to show the relative affordability on a Choropleth map.


For this project you *must use the spreadsheets without editing them.* The Median Income as you know is ordered alphabetically by state. The housing data is ordered by property tax rate. You will need to use multiple loops and/or dictionaries to match up the data to do this analysis.



data = [dict(
    type='choropleth',
    colorscale="BlueRed",
    autocolorscale=False,
    locations=state_names_Pandas,
    z=change_in_income_Pandas,
    locationmode='USA-states',
     colorbar=dict(
         title="Median Income Change in Dollars")
)]

layout = dict(
    title='Change in median income for each state',
    geo=dict(
        scope='usa',
        projection=dict(type='albers usa'),
        showlakes=True,)
)
fig = dict(data=data, layout=layout)
plotly.offline.plot(fig, filename='comp151-map.html')




Submission:

Starting this project you need to submit the whole project folder. So name the project itself with your name in the project (jsantoreMakeup for me) and then you can name your python files whatever you want so long as I can tell which python file to run. Remove any old stuff that you don't want me to run.

explain in a readme.txt: