Add files via upload

ipynb/Electoral Votes.ipynb

@@ -0,0 +1,130 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tracking Trump: Electoral Votes\n",
+    "\n",
+    "[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:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import urllib.request\n",
+    "import re\n",
+    "import collections \n",
+    "\n",
+    "Row = collections.namedtuple('Row', 'state delta jan17app jan17dis jan17err app dis err')\n",
+    "\n",
+    "def read_data(url='https://morningconsult.com/tracking-trump/'):\n",
+    "    \"Fetch data from the website and return a list of `Row` objects.\"\n",
+    "    with urllib.request.urlopen(url) as response:\n",
+    "        html = response.read().decode('utf-8')\n",
+    "        rows = re.findall(r'<tr(.*?)</tr>', html, re.S)\n",
+    "        return [parse_row(row) for row in rows[1:]]\n",
+    "    \n",
+    "def parse_row(row):\n",
+    "    \"Parse an html string into a `Row` object.\"\n",
+    "    state, *nums =  re.findall('>([^>]*?)</td', row.replace('%', ''))\n",
+    "    return Row(state, *map(int, nums))\n",
+    "\n",
+    "def net(row): \"Approval minus disapproval.\"; return row.app - row.dis \n",
+    "\n",
+    "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",
+    "             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",
+    "             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",
+    "             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",
+    "\n",
+    "rows = read_data()\n",
+    "\n",
+    "def EV(swing=0, rows=rows):\n",
+    "    \"How many electoral votes would Trump win today, given a swing.\"\n",
+    "    return sum(votes[row.state] for row in rows if net(row) + swing > 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "164"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "EV()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "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",
+    "\n",
+    "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."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{0: 164,\n",
+       " 1: 164,\n",
+       " 2: 164,\n",
+       " 3: 164,\n",
+       " 4: 255,\n",
+       " 5: 255,\n",
+       " 6: 255,\n",
+       " 7: 279,\n",
+       " 8: 279,\n",
+       " 9: 294}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "{m: EV(m) for m in range(10)}"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}