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Peter Norvig
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ipynb/Electoral Votes.ipynb
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ipynb/Electoral Votes.ipynb
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Tracking Trump: Electoral Votes\n",
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"\n",
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"[Morning Consult](https://morningconsult.com) has a page called [Tracking Trump](https://morningconsult.com/tracking-trump/) that summarizes the presidential approval polls on a state-by-state basis, and tells you how many states Trump has a net positive or net negative approval rating. But I don't care about the number of *states*; I care about the number of *electoral votes*. This notebook computes that for me:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import urllib.request\n",
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"import re\n",
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"import collections \n",
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"\n",
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"Row = collections.namedtuple('Row', 'state delta jan17app jan17dis jan17err app dis err')\n",
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"\n",
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"def read_data(url='https://morningconsult.com/tracking-trump/'):\n",
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" \"Fetch data from the website and return a list of `Row` objects.\"\n",
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" with urllib.request.urlopen(url) as response:\n",
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" html = response.read().decode('utf-8')\n",
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" rows = re.findall(r'<tr(.*?)</tr>', html, re.S)\n",
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" return [parse_row(row) for row in rows[1:]]\n",
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" \n",
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"def parse_row(row):\n",
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" \"Parse an html string into a `Row` object.\"\n",
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" state, *nums = re.findall('>([^>]*?)</td', row.replace('%', ''))\n",
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" return Row(state, *map(int, nums))\n",
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"\n",
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"def net(row): \"Approval minus disapproval.\"; return row.app - row.dis \n",
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"\n",
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"votes = dict(AL=9, AK=3, AZ=11, AR=6, CA=55, CO=9, CT=7, DE=3, DC=3, FL=29, GA=16, HI=4, ID=4,\n",
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" IL=20, IN=11, IA=6, KS=6, KY=8, LA=8, ME=4, MD=10, MA=11, MI=16, MN=10, MS=6, MO=10, \n",
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" MT=3, NE=5, NV=6, NH=4, NJ=14, NM=5, NY=29, NC=15, ND=3, OH=18, OK=7, OR=7, PA=20, \n",
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" RI=4, SC=9, SD=3, TN=11, TX=38, UT=6, VT=3, VA=13, WA=12, WV=5, WI=10, WY=3)\n",
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"\n",
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"rows = read_data()\n",
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"\n",
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"def EV(swing=0, rows=rows):\n",
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" \"How many electoral votes would Trump win today, given a swing.\"\n",
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" return sum(votes[row.state] for row in rows if net(row) + swing > 0)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"164"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"EV()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"What that says is that if an election were held today, January 23, 2019, and if Trump won those states in which he has a net positive approval (i.e. more approval than disapproval), **he would get 164 electoral votes** (that's 9 worse than McCain in 2008). You need **270** to win.\n",
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"\n",
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"But things can change. The election is a long ways away, and we don't know who's running. In the table below, I list the number of electoral votes Trump would get assuming he gets an increase of net approval of 0 to 9 percentage points across the board in every state. We see he would need a **7** percent upswing in order to win."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{0: 164,\n",
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" 1: 164,\n",
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" 2: 164,\n",
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" 3: 164,\n",
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" 4: 255,\n",
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" 5: 255,\n",
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" 6: 255,\n",
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" 7: 279,\n",
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" 8: 279,\n",
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" 9: 294}"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"{m: EV(m) for m in range(10)}"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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