Continuing from my last post, I wanted to see how the distribution of donations looked across the US states.

Data is from the FEC

import pandas as pd
import plotly.plotly as py
import plotly.offline as offline
import cufflinks as cf

Preparing The Data

url = 'contributors.csv'
df = pd.read_csv(url, index_col=False)

Matching Candidates To Their Parties

parties = {'Rubio, Marco': 'Republican',
           'Santorum, Richard J.': 'Republican',
           'Perry, James R. (Rick)': 'Republican',
           'Carson, Benjamin S.': 'Republican',
           "Cruz, Rafael Edward 'Ted'": 'Republican',
           'Paul, Rand': 'Republican',
           'Clinton, Hillary Rodham': 'Democrat',
           'Sanders, Bernard': 'Democrat',
           'Fiorina, Carly': 'Republican',
           'Huckabee, Mike': 'Republican',
           'Pataki, George E: .': 'Republican',
           "O'Malley, Martin Joseph": 'Democrat',
           'Graham, Lindsey O.': 'Republican',
           'Bush, Jeb': 'Republican',
           'Trump, Donald J.': 'Republican',
           'Jindal, Bobby': 'Republican',
           'Christie, Christopher J.': 'Republican',
           'Walker, Scott': 'Republican',
           'Stein, Jill': "Green Party",
           'Webb, James Henry Jr.': 'Democrat',
           'Kasich, John R.': 'Republican',
           'Gilmore, James S III': 'Republican',
           'Lessig, Lawrence': 'Democrat',
           'Johnson, Gary': 'Libertarian',
           'McMullin, Evan': 'Independent'}
df['party'] = df.cand_nm.map(parties)

Filtering Out Refunds

df = df[df.contb_receipt_amt > 0]

Split By Party

democrats = df[df['party'] == 'Democrat']
democrats = democrats.groupby('contbr_st').contb_receipt_amt.sum()
democrats = democrats.to_frame().reset_index()

republicans = df[df['party'] == 'Republican']
republicans = republicans.groupby('contbr_st').contb_receipt_amt.sum()
republicans = republicans.to_frame().reset_index()

Filter To Valid States

states = ['AL','AK','AZ','AR','CA','CO','CT','DE','FL','GA','HI','ID','IL','IN','IA','KS',
          'KY','LA','ME','MD','MA','MI','MN','MS','MO','MT','NE','NV','NH','NJ','NM','NY',
          'NC','ND','OH','OK','OR','PA','RI','SC','SD','TN','TX','UT','VT','VA','WA','WV','WI','WY']
democrats = democrats[democrats.contbr_st.isin(states)]
republicans = republicans[republicans.contbr_st.isin(states)]

Contribution Map For Democrats

scl = [[0.0, 'rgb(239,243,255)'],[0.2, 'rgb(198,219,239)'],[0.4, 'rgb(158,202,225)'],\
            [0.6, 'rgb(107,174,214)'],[0.8, 'rgb(49,130,189)'],[1.0, 'rgb(8,81,156)']]

data = [ dict(
        type='choropleth',
        colorscale = scl,
        autocolorscale = False,
        locations = democrats['contbr_st'],
        z = democrats['contb_receipt_amt'].astype(float),
        locationmode = 'USA-states',
        marker = dict(
            line = dict (
                color = 'rgb(255,255,255)',
                width = 2
            ) ),
        colorbar = dict(
            title = "Millions USD")
        ) ]

layout = dict(
        title = '2016 US Election Contributions(Democrats)',
        geo = dict(
            scope='usa',
            projection=dict( type='albers usa' ),
            showlakes = True,
            lakecolor = 'rgb(255, 255, 255)'),
             )
    
fig = dict( data=data, layout=layout )
py.iplot( fig, filename='2016-election-democrat-ammount-map' )

Contribution Map For Republicans

scl = [[0.0, 'rgb(254,229,217)'],[0.2, 'rgb(252,187,161)'],[0.4, 'rgb(252,146,114)'],\
            [0.6, 'rgb(251,106,74)'],[0.8, 'rgb(222,45,38)'],[1.0, 'rgb(165,15,21)']]

data = [ dict(
        type='choropleth',
        colorscale = scl,
        autocolorscale = False,
        locations = republicans['contbr_st'],
        z = republicans['contb_receipt_amt'].astype(float),
        locationmode = 'USA-states',
        marker = dict(
            line = dict (
                color = 'rgb(255,255,255)',
                width = 2
            ) ),
        colorbar = dict(
            title = "Millions USD")
        ) ]

layout = dict(
        title = '2016 US Election Contributions(Republican)',
        geo = dict(
            scope='usa',
            projection=dict( type='albers usa' ),
            showlakes = True,
            lakecolor = 'rgb(255, 255, 255)'),
             )
    
fig = dict( data=data, layout=layout )
py.iplot( fig, filename='2016-election-republican-map' )

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The Jupyter Notebook for this work can be found on GitHub.