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Peter Norvig
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<div align=\"right\"><i>Peter Norvig<br>12 August 2019</i></div>\n",
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"<div align=\"right\"><i>Peter Norvig<br>12 August 2019<br>Update Oct 2020</i></div>\n",
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"\n",
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"# Data and Code for [Tracking Trump: Electoral Votes Edition](Electoral%20Votes.ipynb)\n",
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"\n",
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@ -12,7 +12,7 @@
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" gives state-by-state, month-by-month presidential approval poll data. Within the web page there is some Javascript from which\n",
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" we can extract the data we need. It looks like this:\n",
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"\n",
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" var mc_state_trend = [[\"Demographic\",\"Jan-17\",\"\",\"Feb-17\",\"\", ...]\n",
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" var mc_state_trend = [[\"Demographic\",\"January '17\",\"\",\"February '17\",\"\", ...]\n",
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" [\"Alabama\",\"62\",\"26\",\"65\",\"29\", ...], \n",
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" ... ]\n",
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" \n",
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@ -28,7 +28,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"! curl -s -o evs.html https://morningconsult.com/tracking-trump-2/"
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"! [ -e evs.html ] || curl -s -o evs.html https://morningconsult.com/tracking-trump-2/"
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]
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},
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{
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@ -94,8 +94,8 @@
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"net_usa = {\n",
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" 'Jan-17': 10, 'Jan-18': -18, 'Jan-19': -12, 'Jan-20': -11,\n",
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" 'Feb-17': 0, 'Feb-18': -15, 'Feb-19': -16, 'Feb-20': -10,\n",
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" 'Mar-17': -6, 'Mar-18': -14, 'Mar-19': -11, \n",
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" 'Apr-17': -13, 'Apr-18': -13, 'Apr-19': -11, \n",
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" 'Mar-17': -6, 'Mar-18': -14, 'Mar-19': -11, \n",
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" 'Apr-17': -13, 'Apr-18': -13, 'Apr-19': -11, \n",
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" 'May-17': -11, 'May-18': -12, 'May-19': -12, \n",
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" 'Jun-17': -16, 'Jun-18': -11, 'Jun-19': -12, \n",
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" 'Jul-17': -15, 'Jul-18': -10, 'Jul-19': -11, \n",
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@ -128,13 +128,17 @@
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" \"Read data from the file and return tuple: (list of `State`s, list of dates).\"\n",
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" text = re.findall(r'\\[\\[.*?\\]\\]', open(filename).read())[0]\n",
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" header, *table = ast.literal_eval(text)\n",
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" dates = header[1::2]\n",
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" dates = [date32(d) for d in header[1::2]]\n",
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" states = [State(name, *state_data[name],\n",
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" approvals=dict(zip(dates, map(int, numbers[0::2]))),\n",
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" disapprovals=dict(zip(dates, map(int, numbers[1::2]))))\n",
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" for (name, *numbers) in table]\n",
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" return states, dates\n",
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"\n",
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"def date32(date) -> str: \n",
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" \"\"\"Convert a date to 3-2 format: date32(\"June '17\") => 'Jun-17'.\"\"\"\n",
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" return date[:3] + '-' + date[-2:]\n",
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"\n",
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"states, dates = parse_page('evs.html')\n",
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"now = dates[-1]\n",
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"\n",
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@ -178,7 +182,7 @@
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"\n",
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"def grid(dates, xlab, ylab): \n",
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" plt.minorticks_on(); plt.grid(which='minor', axis='y', ls=':', alpha=0.7)\n",
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" plt.xticks(range(len(dates)), dates, rotation=90)\n",
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" plt.xticks(range(len(dates)), dates, rotation=90, fontfamily='monospace')\n",
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" plt.xlabel(xlab); plt.ylabel(ylab); plt.legend()"
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]
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},
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" plt.plot(range(N), [270] * N, color='darkorange', label=\"270 EVs\", lw=2)\n",
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" plt.errorbar(range(N), [EV(states, date) for date in dates], fmt='D-',\n",
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" yerr=err, ecolor='grey', capsize=7, label='Trump EVs ±3% swing', lw=2)\n",
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" grid(dates, 'Date', 'Electoral Vptes')\n",
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" grid(dates, 'Date', 'Electoral Votes')\n",
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" #labels('Date', 'Electoral Votes')"
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]
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},
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" yield f'|{swing_name(s)}|{s.lean:+d}|{s.ev}|{\"|\".join(fields)}|'"
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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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"Show how to make all Electoral Vote totals:"
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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": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"def all_totals(states) -> dict:\n",
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" \"\"\"Return a dict of {ev_total: [state, ...]}\"\"\"\n",
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" totals = {0: []}\n",
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" for s in sorted(states, key=lambda s: s.ev):\n",
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" new = {}\n",
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" for t in totals:\n",
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" new[t + s.ev] = shorter(totals.get(t + s.ev), totals[t] + [s.name])\n",
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" totals = {**totals, **new}\n",
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" return totals\n",
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" \n",
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"def shorter(A, B):\n",
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" \"\"\"Return the sequence that is shorter, but always return B if A is None.\"\"\"\n",
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" return B if A is None or len(A) > len(B) else A\n",
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"\n",
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"def show_totals():\n",
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" districts = [State('Maine-1', 1, 0, 0, 0), State('Maine-2', 1, 0, 0, 0)]\n",
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" totals = all_totals(states + districts)\n",
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" for i in range(270):\n",
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" print(f\"{i:3} [{' + '.join(totals[i])}]\")"
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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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@ -280,7 +318,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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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": "3.7.2"
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"version": "3.7.6"
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}
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},
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"nbformat": 4,
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