Two Scoreboards for Republican Presidential Candidates in Python/v3

Plot Scoreboard Using Python and Plotly

Note: this page is part of the documentation for version 3 of Plotly.py, which is not the most recent version.
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Plot Scoreboard Using Python and Plotly¶

ABOUT THE AUTHOR:¶

This notebook was contributed by Plotly user Emilia Petrisor. You can follow Emilia on Twitter @mathinpython or GitHub.

Two Scoreboards for Republican Presidential Candidates¶

Starting with August 6, 2015, The New York Times updates from time to time a scoreboard for the republican presidential candidates.

In this IPython (Jupyter) Notebook we generate the scoreboard published on August 14, respectively August 17, as Heatmap(s) objects in Python Plotly.

Inspecting the web page source code we found out that the scoreboard heatmap in The New York Times is generated with http://colorzilla.com/gradient-editor/.

To identify the color code of each of the 16 colors defining the color gradient in The New York Times dashboard we install ColorZilla Chrome extension.

When the newtimes page is opened, we choose the Web page color analyzer in the ColorZilla menu and read succesively the color codes.

The corresponding Plotly colorscale is defined as follows:

In [13]:

newyorktimes_cs=[[0.0, '#8B0000'],
 [0.06666666666666667, '#9E051B'],
 [0.13333333333333333, '#B0122C'],
 [0.2, '#C0223B'],
 [0.26666666666666666, '#CF3447'],
 [0.3333333333333333, '#DB4551'],
 [0.4, '#E75758'],
 [0.4666666666666667, '#F06A5E'],
 [0.5333333333333333, '#F87D64'],
 [0.6, '#FE906A'],
 [0.6666666666666666, '#FFA474'],
 [0.7333333333333333, '#FFB880'],
 [0.8, '#FFCB91'],
 [0.8666666666666667, '#FFDEA7'],
 [0.9333333333333333, '#FFEEC1'],
 [1.0, '#FFFFE0']]

Below we give the table of rankings as for 14 August, by the factors in the list with the same name.

In [26]:

tab_vals14=[[1,2,3,4,5,6,6,8,9,9,9,12,13,13,13,13],
          [1,7,5,12,5,4,12,7,2,3,12,7,7,12,7,12],
          [4,7,2,1,10,5,6,7,9,12,3,14,12,11,15,16],
          [2,9,4,1,3,8,10,11,6,5,6,14,14,12,14,13],
          [1,3,4,14,8,2,13,12,7,6,9,16,5,10,12,15]]

candidates=['Bush', 'Rubio', 'Walker', 'Trump', 'Kasich', 'Cruz', 'Fiorina', 'Huckabee', 'Paul']+\
 ['Christie', 'Carson', 'Santorum', 'Perry', 'Jindal', 'Graham', 'Pataki']

factors=['Prediction Market', 'NationalEndorsements', 'Iowa Polls']+\
['New Hampshire Polls', 'Money Raised']

First we define a simple Plotly Heatmap:

In [27]:

import plotly.plotly as py
from plotly.graph_objs import *

In [28]:

data14=Data([Heatmap(z=tab_vals14,
                   y=factors,
                   x=candidates,
                   colorscale=newyorktimes_cs,
                   showscale=False
                   )])

In [29]:

width = 900
height =450

anno_text="Data source:\
<a href='http://www.nytimes.com/interactive/2015/08/06/upshot/\
2016-republican-presidential-candidates-dashboard.html'> [1]</a>"

title = "A scoreboard for republican candidates as of August 14, 2015"

layout = Layout(
    title=' ',
    font=Font(
        family='Balto, sans-serif',
        size=12,
        color='rgb(68,68,68)'
    ),
    showlegend=False,
    xaxis=XAxis(
        title='',
        showgrid=True,
        side='top'
    ),
    yaxis=YAxis(
        title='',
        autorange='reversed',
        showgrid=True,
        autotick=False,
        dtick=1
    ),
    autosize=False,
    height=height,
    width=width,
    margin=Margin(
        l=135,
        r=40,
        b=85,
        t=170
    )
)

annotations = Annotations([
    Annotation(
            showarrow=False,
            text=anno_text,
            xref='paper',
            yref='paper',
            x=0,
            y=-0.1,
            xanchor='left',
            yanchor='bottom',
            font=Font(
            size=11 )
            )])

fig=Figure(data=data14, layout=layout)
fig['layout'].update(
title=title,
annotations=annotations
)

py.sign_in('empet', 'my_api_key')
py.iplot(fig,filename='Heatmap-republican-candidates-14')

Out[29]:

Now we go further and update the above Figure with data available on August 17, and moreover we annotate the Heatmap, displaying the candidate ranking on each cell.

In [30]:

tab_vals17=[[1,2,3,4,5,6,7,7,9,9,11,11,13,13,13,13],
  [1,7,5,12,5,4,7,12,2,12,3, 7,7,12,7,12],
   [4,7,2,1,10,5,7, 6, 9,3, 12, 14,12,11,15,16],
  [2,9,4,1,3,8,11, 10, 6,6, 5, 14,14,12,14,13],
  [1,3,4,14,8,2,12, 13, 7,9, 6,16,5,10,11,15]]

candidates17=['Bush', 'Rubio', 'Walker', 'Trump', 'Kasich', 'Cruz',  'Huckabee', 'Fiorina','Paul']+\
  ['Carson',  'Christie', 'Santorum', 'Perry', 'Jindal', 'Graham', 'Pataki']

The first row in tab_vals17 changed relative to the same row in tab_vals14, by swapping their positions the candidates (Fiorina, Huckabee) and (Christie, Carson), and correspondingly the other rows.

In [31]:

fig['data'].update(Data([Heatmap(z=tab_vals17,
                   y=factors,
                   x=candidates17,
                   colorscale=newyorktimes_cs,
                   showscale=False
                   )]))

In [32]:

for i, row in enumerate(tab_vals17):
    for j, val in enumerate(row):
        annotations.append(
            Annotation(
                text=str(val),
                x=candidates[j], y=factors[i],
                xref='x1', yref='y1',
                font=dict(color='white' if tab_vals17[i][j]<12 else 'rgb(150,150,150)'),
                showarrow=False))

In [33]:

fig['layout'].update(
title="A scoreboard for republican candidates as of August 17, 2015 <br> Annotated heatmap",
annotations=annotations
)

py.iplot(fig,filename='Annotated heatmap-republican-candidates-17')

Out[33]:

In [35]:

from IPython.core.display import HTML
def  css_styling():
    styles = open("./custom.css", "r").read()
    return HTML(styles)
css_styling()

Out[35]: