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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Simple process: let's say you have two populations. Non-Republican split-ticket voters, and Republican voters who vote using the straight ticket.\n", | |
"\n", | |
"We assume Republican straight-ticket voters always vote for Trump.\n", | |
"\n", | |
"Non-Republican voters instead have some small chance of voting for Trump, $p({NR})$." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"correlation = 0.6\n", | |
"p_NR = lambda percent_r: correlation*percent_r" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Great now let's simulate a bunch of precincts with different fractions of R voters.\n", | |
"\n", | |
"We'll assume that all R-voters voted Trump." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"import numpy as np\n", | |
"num_precincts = 1000 # let's deal with 1000 precincts.\n", | |
"r_percentages = np.random.rand(num_precincts) # modeling the fraction of R voters in a precint, randomly from [0-1]" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Now let's simulate some per-precinct votes and collect % of Trump votes from non-Republican candidates.\n", | |
"\n", | |
"This can be sampled a a bunch of weighted coinflips with the probability $p({NR})$--i.e, sampling from a binomial distribution." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"# let's say we're dealing with a fixed size of non-republican voters in each precinct\n", | |
"non_r_pop_size = 100 \n", | |
"split_trump_percentages = np.zeros(num_precincts)\n", | |
"# simulating\n", | |
"for i, percent in enumerate(r_percentages):\n", | |
" split_votes = np.random.binomial(non_r_pop_size, p_NR(percent)) \n", | |
" split_trump_percentages[i] = split_votes / non_r_pop_size\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"import seaborn as sns\n", | |
"sns.set()\n", | |
"\n", | |
"diffs = split_trump_percentages - r_percentages\n", | |
"plt.scatter(r_percentages*100, diffs*100) \n", | |
"plt.xlabel('% republican straight-ticket votes')\n", | |
"plt.ylabel('% individual trump votes - % straight ticket votes')\n", | |
"plt.savefig('corr-diff')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"import seaborn as sns\n", | |
"sns.set()\n", | |
"\n", | |
"diffs = split_trump_percentages - r_percentages\n", | |
"plt.scatter(r_percentages*100, split_trump_percentages*100) \n", | |
"plt.ylim([0,100])\n", | |
"plt.xlabel('% republican straight-ticket votes')\n", | |
"plt.ylabel('% individual trump votes')\n", | |
"plt.savefig('corr-split')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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Dww1ZIxE1AFV6LsbHJUsOhm4dHRkMFkhry+HNN9/EkSNHAAC9evX63wbW1vD399d/ZUTUYOTcicQpMCyb1nBYs2YNAGDOnDl4//33DVYQETWs8KUHUFpeJWkbBgPpvJW1ZjAsX778vh3URGR8wubuQXFZ3W9PvYOdzgTUYW6lmpKTpS8eru1zQkNDERAQgIULFwIAUlJSEBISgv79+yMxMbFB9kNkqcbFJUsOBr8n22JtVB8GAwGoQ8uhpoaYNiM7OxuxsbHYunUrnJyc8Oqrr+LgwYOIjY3F+vXr0aZNG0yePBkHDx6Er69vvfdHZGnClx6Q9H6OW6D7kdRy6NOn/rMtfv/99wgMDETr1q1hY2ODxMRE2Nvbo2PHjmjfvj2sra0REhKCpKSkeu+LyJKs35eJcXHJkvoXbJRgMNB96QyHmtNzz5gxAwDq1e+QlZUFtVqN8ePHY9CgQdi0aRPy8/Ph7OyseY+Liwvy8vJk74PI0sxafkjy3Ug2SmDlbE6vTfen9bJSbGws8vLykJqaihs3bmier6ysxMWLF2XvUK1W4/jx41i/fj2aNm2KadOmwd7evtb7FAqFpM91cnKQXZOzc3PZ25oqHrP5mLb4B8ljFzwedcLCqd56qqhxmet5fhB9HLPWcBg+fDjOnz+Ps2fPYsCAAZrnlUolnnzySdk7bNmyJby8vNCiRQsAQN++fZGUlASlUql5T35+PlxcXCR9bmHhLVRJWK3qDmfn5igo+FvydqaMx2we5Nyi2q2jI2aPfAoAzO77AMzzPOsi95itrBQP/KNaazj06NEDPXr0wPPPP19r+oz68PPzQ2RkJP766y80a9YMhw4dQkBAAFatWoWsrCy0a9cOe/bswbBhwxpsn0TmZsLiZEj5W0gBYAJvUSUJdN6tdPXqVcyZMweFhYV33a20e/duWTv08PDAhAkTMGrUKFRUVKB3794YOXIkOnXqhOnTp6OsrAy+vr4ICAiQ9flE5kzOhHltneyxcKKXnioic6UQOu5PDQwMxIsvvohu3brd1Q/g6emp9+Kk4GWluuMxmyaOdNbNHM6zVAa/rHSHra0txo4dK3nHRNQw5LQWFABmjXoKj3Vw1E9RZPZ03sraqVMnnD592hC1ENE9Zi0/JDkYunV0xJqoPnjh6fZ6qoosgdaWQ0hICACguLgYI0eO1AxQu0NunwMR6SZnFlXg7ruRiOpDazjExMQYsg4i+v/kLMYDcMI8alhaw+FOh/OxY8fuel6hUKBJkya4desWHBzkDzwjotqiV6u4ShsZhTpN2Z2ZmQl3d3dYWVnh3LlzcHZ2RmlpKRYtWsSFf4gayLg46bMeW9rdSGQ4OsOhbdu2iIyM1KwGd+rUKaxbtw5vv/02pk6dynAgqic5/QvsWyB90xkO2dnZdy0T+sQTT+Dy5csNOmqayFJJ7V/ggDYyFJ3hYG1tjcOHD8Pbu3qSrsOHD8PGxgY3btxAZWWl3gskMkdyOp3ZWiBD0hkOsbGxmDFjBhQKBaqqqmBnZ4dly5bh888/R1hYmCFqJDIrnBeJTIHOcHjiiSfw448/4ty5c1AqlXBzc4NSqUTXruwEI5JClZ6L1bvPSN5uTRTXXCDD0xoOq1evxsSJE/Huu+/ed22F6OhovRZGZE7kTIEBAGsZDNRItIZD8+bVi0c8/PDDBiuGyNxwpDOZKq3hcKc/4fXXX6/1WklJif4qIjITcjqdeTcSGQudfQ4//PADli1bhpKSEgghUFVVhaKiIpw4ccIQ9RGZHLl9CxzQRsZEZzjEx8fjjTfewObNmzFx4kT88MMPaNasmSFqIzI5k5cko0ItfTvOi0TGRmc42NvbIzAwEBkZGbCzs8P8+fO5hCfRfciZ/oKXkchY1Wmxn/LycnTo0AEZGRno1asXysvLDVEbkcmYvERaMCgUwIRgthbIeOkMh759+2LSpEmIi4tDWFgYUlNT4ejI1aWIAHn9C04P2SHU143BQEZNZzgMHz4cgwYNQuvWrfHJJ5/g2LFjCA4ONkRtREZNztgFjlsgU6EzHF555RUkJSUBALp3747u3bvrvSgiYyZ37AKDgUyJzjWkXV1dkZaWhqqqKkPUQ2TUolerZE2vzWAgU6Oz5fD7779j1KhRsLa2hq2tLYQQUCgUSEtLM0R9REZBlZ6LtXvOQC1hwjyAt6iS6dIZDps2bar1nBAS/4UQmbDo1SpcKyyVtI2VAvg8kq0FMl06LyvFxsbC1dX1rv9mzZpliNqIGt2s5YckB4NjMxsGA5k8rS2HGTNm4NKlS8jOzkZISIjm+crKSlhZ6cwUIpMmt9OZl5HIXGgNh7fffhtXr15FTEwMYmJiNM8rlUq4u7sbpDiixiBnCgwbJbByNlsLZD60hkO7du3Qrl07JCUlaVoK2dnZyM3NxUMPPWSwAokMSeoUGEoFMI4jnckM6eyQ/vrrr3H8+HHMmzcPYWFhcHBwQP/+/fHmm28aoj4ig5m1/JCk93PNBTJnOjsPtm7dijlz5iApKQl9+/bFt99+iyNHjhiiNiKDWLI5DePikiWtveD3ZFsGA5k1nS0HhUKBli1bQqVSYeDAgbC2tuaAODILcjqd7W2tsGLWC/opiMiI6Gw52NraYvXq1fjll1/Qu3dvbNq0Cfb29oaojUhvZi0/JDkYbJRgMJDF0NlyWLRoEdasWYPFixfjH//4B1JTU7Fo0SJD1EbU4LimM1HdKISZDHcuLLyFqirph+Ls3BwFBX/roSLjZanHPPm972QNaFs6/V96qkq/LPU885jrxspKAScnB62v62w5EJmD6E8PSw4GDmgjS9Zo4bB48WL8+eefiIuLQ0ZGBqKjo3Hr1i0888wzWLBgAaytmVtUf6r0XHz53wyUV0prVTIYyNI1yjwYKpUKO3bs0DyePXs2YmJisG/fPgghsGXLlsYoi8xM9GoVVu8+IykY2jrZY21UHwYDWTydf54XFBTg66+/RlHR3SteRUdHy9phUVEREhMTMWXKFGRmZuLq1au4ffs2evbsCQAIDQ3FsmXLMGrUKFmfTwTImwLD78m2GD2gq34KIjIxOsMhIiICzZs3R/fu3aFQKOq9w3//+9+IiIhATk4OACA/Px/Ozs6a152dnZGXlyf5cx/UsaKLs3Nz2duaKnM95uhPD+PX3wslb/fmqKfwwtPt9VBR4zLX8/wgPOaGoTMcCgsLsWHDhgbZ2datW9GmTRt4eXlh+/btAO6/NoScEOLdSnVnrsccvvQASsulDdCseYuquX0n5nqeH4THXHf1vlupbdu2KCkpQdOmTSXv/F579+5FQUEBBg8ejJs3b6KkpAQKhQLXr1/XvKegoAAuLi713hdZDlV6LlbvPiNpG15CInowneHg4uKCIUOGwNPTE02aNNE8L6fP4YsvvtD8//bt2/HLL7/g/fffR3BwMFJTU/H0009j586d8PHxkfzZZJlmLT8kaU4koLq1wGAgejCd4XBn9Td9SkhIQHR0NIqLi9G9e3eMGTNGr/sj8yB1em2ALQaiupI1QrqhLjM1JPY51J2pH7OcNZ1bNLdFQri3nioyTqZ+nuXgMdddvfscfvjhByxbtgwlJSUQQqCqqgpFRUU4ceKE5GKI6kvqLaoKABNCumPQC+4W90uDqD50hkN8fDzeeOMNbN68GRMnTsQPP/yAZs2aGaI2Ig05fQucXptIPp0jpO3t7REYGIiePXvCzs4O8+fPx9GjRw1RGxGA6taC1GBo62TPYCCqB50tB1tbW5SXl6NDhw7IyMhAr169UF5ebojayMLJnV6b8yIR1Z/OcOjbty8mTZqEuLg4hIWFITU1FY6OjoaojSyYnAFtNkpg5ew+eqqIyLLoDIcpU6Zg0KBBaN26NT755BMcP34cQUFBhqiNLJCcAW0AF+Mhamg6+xwyMzMxf/58AIBSqcS2bdtw8+ZNfddFFmj9vkxZwTAxpDuDgaiB6QyH+fPnY8SIEQCALl26YPr06YiNjdV7YWRZolerJPcvdOvoyOm1ifRE52Wl0tJS9OvXT/PY398fK1as0GtRZDnY6UxknHSGg0KhwNmzZ9GlSxcAwIULF2Bl1ShrBJGZWbI5DRlZRbrfWIMpr+lMZEp0hsPMmTPxyiuvoHPnzgCAixcvIiEhQe+FkXmTM6iN8yIRGY7OcPDz80NSUhLS0tKgVCrh4eEBJycnQ9RGZkju3UgMBiLD0hoOKpUKXl5e+O677zTPVVZWIjU1FQDQv39//VdHZkVO/wJvUSVqHFrD4dtvv4WXlxfWr19f6zWFQsFwIEl4GYnItGgNh4ULFwLAfcOBqK7kdDpzpDNR49MaDlOmTHnghp999lmDF0PmRer02kD1hHkLJ3rppyAiqjOt4TBgwABD1kFmhK0FItOnNRyGDh2q+f8///wTJ0+ehLW1NTw8PPDQQw8ZpDgyPXJaCxy7QGR8dN7KeuDAAURGRsLd3R1VVVW4cuUKEhMT8eyzzxqiPjIRckc6s9OZyDjpDIePPvoIGzZsgLu7OwAgPT0dMTEx2L59u96LI9MgZ01n9i0QGbc6TZ9xJxgA4LHHHoMQQq9FkWmQM6CNfQtEpkHrJElFRUUoKirC448/jjVr1qC4uBilpaXYuHEjnnvuOUPWSEZIzvTajs1sGAxEJkJry+G5556DQqHQtBKWLFmieU2hUCAyMlL/1ZFR4oA2IvOnNRwyMzMNWQeZAE6vTWQ5dPY51JxbqSZOn2FZ5HQ6s3+ByHTpDIea02dUVFTg7Nmz8PT0ZDhYkPClB1BaXiVpG06YR2TaJIUDAFy5cgUffPCB3goi48HWApHl0hkO9+rQoQMuXryoj1rIiHCkM5Flk9TnIITAb7/9BmtryZlCJkJOawFgpzORuZF0WUmhUKBFixaIi4vTa1HUOMbFJUvehiOdicyT5D4HMj9yl+5ka4HIfOkMh4KCAixcuBCHDx+GUqlEnz59MGfOHPzjH/8wRH2kZ3Km1waAtVHsdCYyZ1qnz7gjKioKHTp0wM6dO7FlyxY8/PDDiImJMURtpGfhSw9IDgZ7WysGA5EF0NlyyM3NxZo1azSPIyMjERgYqNeiSL8OpGbjg01pkrbhLapElkVny6FVq1a4cuWK5nF+fj5cXFzqtdOPP/4YQUFBCAoKQnx8PAAgJSUFISEh6N+/PxITE+v1+aTdks1pkoPBSsFgILI0dZqye8iQIfD29oZSqYRKpULr1q01a0xLXUs6JSUFhw8fxo4dO6BQKDBhwgTs2bMHCQkJWL9+Pdq0aYPJkyfj4MGD8PX1lXdUVIvcTmfejURkmXSGQ3BwMIKDgzWPfXx86rVDZ2dnREVFwdbWFgDg5uaGy5cvo2PHjmjfvj0AICQkBElJSQyHBiJnQBunvyCybDrDYejQocjNzcXZs2fh7e2N/Px8tGnTRvYOay4cdPnyZezduxejR4+Gs7Oz5nkXFxfk5eXJ3gf9j9yxCwwGIsumMxwOHjyI2NhYWFlZ4auvvkJgYCCWLFkCf3//eu34/PnzmDx5MiIjI2FtbY1Lly7d9bpCoZD0eU5ODrJrcXZuLntbYxU2dw+KyyQ2FwC8OeopvPB0ez1U1PjM8TzrwmO2DPo4Zp3hsHz5cmzZsgWTJk2Ci4sLNm3ahMjIyHqFQ2pqKmbMmIG5c+ciKCgIv/zyC65fv655XU6nd2HhLVRVSV++1Nm5OQoK/pa8nTGT01qoOS+SuX0fgHmeZ114zJZB7jFbWSke+Ee1zruVqqqq7vpF3a1bN8l/1deUk5OD8PBwJCQkICgoCADg4eGBS5cuISsrC2q1Gnv27Kl334almrxE3mUkTphHRDXpbDnY29vj2rVrmkA4fvw47OzsZO9wzZo1KCsru2t+prCwMMTFxWH69OkoKyuDr68vAgICZO/DEqnSc/H5njMQEhtPnAKDiO5HIcSDf52kpaVh7ty5KCgowKOPPorLly9j+fLl8PT0NFSNdWKpl5VU6bnY9P1ZFN+W1r9gadNrm/p5loPHbBn0dVlJZ8uhQ4cO2LJlC06cOIGqqip4eHigRYsWkguhhqdKz8XaPWeglpCJbZ3ssXJuf4v7B0RE0ugMh1deeYVjDozQ+n2Z2H/imqRt/J5si9EDuuqpIiIyJ0XWnXQAABOfSURBVDo7pF1dXZGWloaqKmlrCJP+hC89wGAgIr3S2XK4cOECRo0aBWtra9ja2kIIAYVCgbQ0afPzUP3JmV7b0voWiKhh6AyHjRs3GqIO0kHOFBicF4mI5NIZDq6uroaog7SQ07fgYG+Nkf6deYsqEcmmMxyo8ci5jMQJ84ioITAcjJAqPRf/ScpAWYW0cRvsdCaihsJwMDJy+hbsba2wYtYLeqmHiCyTzltZ70hJSUFwcDD8/f2xfft2fdZkscbFSQ8GvyfbMhiIqMFpbTlUVFTAxsZG83jDhg2aUBg2bBhCQ0P1X50FmbX8kORt1kZx6U4i0g+t4TB69GhMnTpVMzK6SZMmSEpK0ox3oIYh524kgMFARPql9bLSqlWr8NNPPyE8PBzZ2dmIjo7GhQsXcPr0aXzwwQeGrNFsyRnp7NjMhsFARHqnteXw0EMPISYmBpmZmYiNjUWPHj0wdepUNGnSxJD1mSU5rQWFApgQzOm1icgwtLYc1Go1Dh48iBs3bmDNmjXo1KkTXn31VSQlJRmyPrOiSs/F+MXJkoOhW0dHrInsw2AgIoPR2nKYOXMmnJycUFpaiu+++w7z589H3759sWLFCnzzzTf4/PPPDVmnyYtercK1wlJJ23BeJCJqLFrDITs7Gx9//DEAYMiQIQAABwcHREZG4sKFC4apzkzIWdPZ3taKwUBEjUZrOHTv3h0TJ05EWVkZXnjhhbtec3Nz03ddZkHunUgc1EZEjU1rOLz//vs4e/YsbG1t8cgjjxiyJrMgZ14kgFNgEJFxeOD0GV26dDFUHWZFTjCwtUBExoRzKzUgVXouPt9zBkLafHmcSZWIjA7DoYFwlTYiMicMhwYg5zZVrtJGRMaM4VAPckLB1lqBVwd244A2IjJqDAcZVOm5WL37jOTtJoZw+gsiMg0MB4lmLT+EouIKSdtwXiQiMjUMBwnkjHRmpzMRmSKGQx3JCQbeokpEporhUAdSg4ED2ojI1DEcHkDO3Ei8RZWIzAHD4T5U6bn4fPcZSBnozFAgInPCcLiHnLELvEWViMwNw6GG8KUHUFpeJWkbrudMROaI4QBgwuJkVEmcLA9gMBCR+bL4cAh5c5fkbdi/QETmzqjCYffu3fj0009RUVGBsWPH4uWXX9bbvu5Mry0FQ4GILIXRhENeXh4SExOxfft22NraIiwsDL169cKjjz7a4PtSpefiy/9mSlp3wUYJBgMRWQyjCYeUlBQ899xzcHR0BAAMGDAASUlJeP311+u0vZWVos77+unkNTg2t6vz+x9qaoPoV5+t8/tNgZTvy1zwmC0Dj7lhtjGacMjPz4ezs7PmsYuLC06dOlXn7R9+uFmd35vwhq+k2syRk5NDY5dgcDxmy8BjbhhWDf6JMon7XONRKCzvLwAiImNgNOHQqlUrXL9+XfM4Pz8fLi4ujVgREZHlMppweP7556FSqXDjxg2Ulpbiu+++g4+PT2OXRURkkYymz6FVq1aIiIjAmDFjUFFRgeHDh+OJJ55o7LKIiCySQtzvYj8REVk0o7msRERExoPhQEREtTAciIioFoYDERHVYtHhsHv3bgQGBqJfv37YuHFjY5ejFx9//DGCgoIQFBSE+Ph4ANVTlYSEhKB///5ITExs5Ar1Z/HixYiKigIAZGRkYNiwYRgwYADmzZuHysrKRq6u4SUnJyM0NBQBAQFYuHAhAPM/17t27dL8fC9evBiAeZ7rW7duITg4GH/88QcA7ee1QY9dWKjc3Fzh5+cn/vzzT1FcXCxCQkLE+fPnG7usBnXkyBHx0ksvibKyMlFeXi7GjBkjdu/eLXx9fcWVK1dERUWFGDdunDhw4EBjl9rgUlJSRK9evURkZKQQQoigoCBx4sQJIYQQc+bMERs3bmzM8hrclStXhLe3t8jJyRHl5eVi5MiR4sCBA2Z9rktKSsSzzz4rCgsLRUVFhRg+fLg4cuSI2Z3rkydPiuDgYPHYY4+J7OxsUVpaqvW8NuSxW2zLoeZEf02bNtVM9GdOnJ2dERUVBVtbW9jY2MDNzQ2XL19Gx44d0b59e1hbWyMkJMTsjruoqAiJiYmYMmUKAODq1au4ffs2evbsCQAIDQ01u2P+/vvvERgYiNatW8PGxgaJiYmwt7c363OtVqtRVVWF0tJSVFZWorKyEtbW1mZ3rrds2YLY2FjNjBGnTp2673lt6J9zoxkEZ2j1nejPFLi7u2v+//Lly9i7dy9Gjx5d67jz8vIaozy9+fe//42IiAjk5OQAqH2unZ2dze6Ys7KyYGNjg/Hjx6OgoAB+fn5wd3c363Pt4OCAmTNnYuDAgWjSpAk8PT1hY2Njdud60aJFdz2+3++uvLy8Bv85t9iWg7Cgif7Onz+PcePGITIyEh06dKj1ujkd99atW9GmTRt4ef1v7Q1LONdqtRoqlQpLlizBli1bcPr0ac316ZrM6bgzMzOxbds27N+/H4cPH4aVlRWOHDlS633mdMyA9p/nhv45t9iWQ6tWrXD8+HHNY3Od6C81NRUzZszA3LlzERQUhF9++cWsJzjcu3cvCgoKMHjwYNy8eRMlJSVQKBR3HXNBQYFZHTMAtGzZEl5eXmjRogUAoG/fvkhKSoJSqdS8x9zO9eHDh+Hl5QUnJycA1ZdR1qxZY/bnWtskpfc+X99jt9iWgyVM9JeTk4Pw8HAkJCQgKCgIAODh4YFLly4hKysLarUae/bsMavj/uKLL7Bnzx7s2rULM2bMQJ8+ffD+++/Dzs4OqampAICdO3ea1TEDgJ+fHw4fPoy//voLarUahw4dQkBAgFmf665duyIlJQUlJSUQQiA5ORmenp5mf661/Rt2dXVt0GO36JaDuU/0t2bNGpSVlSEuLk7zXFhYGOLi4jB9+nSUlZXB19cXAQEBjVilYSQkJCA6OhrFxcXo3r07xowZ09glNSgPDw9MmDABo0aNQkVFBXr37o2RI0eiU6dOZnuuvb29cebMGYSGhsLGxgY9evTApEmT0K9fP7M+13Z2dlr/DTfkzzkn3iMiolos9rISERFpx3AgIqJaGA5ERFQLw4GIiGphOBARUS0MB8KcOXMwaNAgTJs2DRUVFQCAmzdv4qWXXkJ5eXmj1dWlSxfcuHGj1vPbt2/H5MmTAQDz5s1DSkqKoUsDAGRnZ2P69OmSt9u8eTNWrVr1wPf8/PPPCA4Ovu9rp06dwr///W+t244bN07zvU2cOBG///67rP1oI/e4tYmOjsZvv/3WYJ9HDYPhYOEyMzORn5+P//u//0PLli1x+PBhAMBHH32EKVOmwNbWtpErfLBFixbh+eefb5R9X7t2DZcuXZK83ciRIzFp0iTZ+/39998fOGdOzSkkVq9ejUcffVT2vu5H7nFrk5KSct+pH6hxMRwsnK2tLcrLyyGEQGlpKWxsbJCZmYmcnBz4+flp3e6PP/6Ar68vxo0bhwEDBiA/Px9paWkYNWoUhg4ditDQUOzfvx9A9V/648ePx2uvvYbAwEC89tprml9uo0ePvmvmyHsff/jhhxg6dCgGDx6s+byaar5///79GDx4MEJCQvDSSy8hMzMTAPDZZ59h+PDhCAkJgb+/P77//nsAwPLlyxEVFYXx48cjICAAo0aNuu8v3QsXLiAsLAyhoaEYOnQoNm7cCLVajejoaFy5cgXjx4+/7/fxoP2+8847AKpbAaGhoQgJCUF4eDiGDh2Kn3/+GQBQUlKCiIgIDB48GAEBATh+/DhycnKwbNkyHD9+HHPmzKlV653nXn31VeTk5KBPnz44ffo0AOCbb75BUFAQQkJCMGbMGM3EhHccP34cfn5+SEtLA1C9PsSIESMwZMgQhIWF4cSJE7WOu6ZLly6hV69emtamWq2Gj48Pfv/9d+Tm5mLKlCkICQlBcHAwPv/8cwBAYmIi8vPz8dZbb+HXX3/F33//jaioKM138t5772nWJFi2bBlCQkIQGhqK8ePHIz8/v9bxUwOqzzzjZB6WLl0qBg0aJGJiYoRarRZjx44Vly9ffuA22dnZonPnzuLYsWNCCCGKiopE//79RXZ2thCier0MHx8fcfXqVbFt2zbRs2dPcfHiRSGEEEuWLBHTp08XQgjxyiuviP/+97+az635uHPnzmLlypVCCCHOnj0rPD09RWFhodi2bZuYNGnSXe8vKCgQTz/9tDhz5owQQoh9+/aJ8ePHiz/++EOMHj1alJaWCiGE2LNnjwgODhZCCLFs2TLRt29f8ffffwshhJg8ebL46KOPah3rnDlzNHXk5+eLN954Q6jVanH06FERFBR03+9D134XLFggKioqhI+Pj2YufpVKJbp06SKOHj0qjh49Krp16yZOnjwphBDiiy++EGPGjBFCiLuO/346d+4sCgsLhRBC+Pn5iVOnTomMjAzRq1cvce3aNc3nxcTEaI5BpVIJf39/kZGRIYQQ4tKlSyI4OFjcuHFDCCHEuXPnRO/evUVxcfFdx32vl19+WXP+Dhw4IMLCwjTPr127VgghxF9//SVCQkLEnj177qpRCCGioqLEf/7zHyGEEJWVleKtt94Sq1atEteuXRNPPfWUKCsrE0IIsWbNGvH9999r/Q6o/ix2+gz6n4iICERERACoXlmrR48ecHBwQEREBEpLSzF69Gj07t271nbW1taaueNPnjyJgoIChIeHa15XKBQ4e/YsAKB379545JFHAAAvvvgiBg8eXKfaRo4cCQDo3Lkz3NzccOLEifu+Ly0tDe7u7ujWrRsAoH///ujfvz+A6hXhdu/ejaysLPz6668oLi7WbOfp6QkHBwcAQPfu3XHz5s1an92vXz9ERkbi1KlT8PLyQnR0NKysaje6a34frq6uD9wvAJw7dw4A4OvrCwB47rnn7ppmvX379vDw8ABQPY/Qtm3bdH1dWqlUKnh7e6NNmzYAgLFjxwKo7nO481f9yJEj0bVrVwDVl6by8/M17wOqz+eVK1ceuJ8RI0Zgx44dCAgIwPbt2zFixAiUlJQgLS0Na9euBQA0b94coaGh+OmnnzRzft1x4MABnD59Gt988w0A4Pbt2wCqp7vp2rUrhg4dCh8fH/j4+Nw18y41PIYDady6dQsbNmzAl19+ic8++0wzZ8uwYcPw7bff1nq/ra0trK2rf4TUajXc3NywdetWzet5eXlo0aIFdu/efdfsoFVVVXc9FjWuN9/pEL+j5i9hIYRmf/dSKpV3TU8shMDZs2ehVqsxbdo0jB07Fr1798azzz6LBQsWaN7XpEkTzf9rm/bYz88P+/btQ0pKClQqFVasWIGvvvrqgd9Henr6A/d7p+Z791fze7GxsdFZ20cffYTk5GQAQJ8+fTBz5sw6fT+3b9/G1atXNa+tWrUK06ZNw8CBA/HEE0+gqqoKXl5e+PDDDzXb5OTkwMXF5a7ZjO8VEBCA999/HxcuXMCxY8cQFxcHtVpdq/aqqqr7LmFZVVWFjz76CG5ubgCAv/76CwqFAlZWVtiwYQNOnz4NlUqF9957D7169UJ0dLTWWqh+2OdAGitWrMBrr72Gpk2bory8HDY2NrCyskJpaanObXv27ImsrCwcO3YMQPVatneuvQPA0aNHNdfzv/rqK01/RosWLTR3qly5ckXT0rhjx44dAKp/2WZlZWn+kr6Xh4cHLly4gPPnzwMAfvzxR8yePRvHjh3D448/jtdeew2enp748ccfoVarJX0vb775Jvbu3YugoCDExsbCwcEBOTk5UCqVtcLsjrrs183NDba2tvjpp58AVPc/nDt3Tucc/EqlUvOLdebMmdi1axd27dqlCYaar9/Rq1cvqFQqzfn46quvsGTJEgDVi8I89dRTiIyMxOzZs1FaWornnnsOR44cwYULFwAABw8exKBBg1BWVvbA47azs0NQUBCioqLQv39/2Nvbw8HBAR4eHpp12v/++2/s3LlTcyNBzXq9vb2xbt06CCFQXl6OqVOnYsOGDcjMzERwcDDc3NwwefJkjB07ttbPCjUsthwIQHWn67lz5xAZGQkAeOmll/Dmm2/i008/xdSpU3Vu36JFCyxbtgzx8fEoKyuDEALx8fFwdXUFUH1ZYPbs2SgoKMCjjz6q6ZCdOnUqoqKicPDgQXTq1AnPPPPMXZ+bnZ2NIUOGQKFQYOnSpXB0dLzv/lu2bImEhARERkZCrVbDwcEBiYmJcHR0xHfffYfAwEDY2NjAy8sLN2/exK1bt+r83UybNg3z5s3D119/DaVSCX9/f3h6euKvv/6CUqnE8OHD71rkHQCCg4N17tfa2hrLly9HbGwsli5din/+859o2bIlmjRp8sBAfvLJJ/Hhhx8iPDwcK1asqPV6v379MGrUKHzyySea57p06YLZs2djwoQJAKoD4b333sPly5c17xk6dCj27duHuLg4LFiwAO+88w5mzZqlabF9+umnaNq0Kdzd3TXHvXXr1lphNmLECGzYsAHz58/XPJeQkIB33nkH27dvR3l5uaZjGQD8/f0RERGBhQsXYt68eVi0aBFCQkJQUVGB559/HhMmTICNjQ0GDhyIYcOGoWnTpmjSpAlbDXrGWVlJ77Zv3459+/Zh5cqVjV2K0Vm8eDHGjx+Pli1bIicnB4MHD8YPP/yAhx56qLFLIwvHlgNRI3J1dcXYsWNhbW0NIQQWLlzIYCCjwJYDERHVwg5pIiKqheFARES1MByIiKgWhgMREdXCcCAioloYDkREVMv/A8dYZ4zrK6w5AAAAAElFTkSuQmCC\n", | |
"text/plain": [ | |
"<Figure size 432x288 with 1 Axes>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"import matplotlib.pyplot as plt\n", | |
"import seaborn as sns\n", | |
"sns.set()\n", | |
"\n", | |
"diffs = split_trump_percentages - r_percentages\n", | |
"plt.scatter(r_percentages*100, r_percentages*100) \n", | |
"plt.ylim([0,100])\n", | |
"plt.xlabel('% republican straight-ticket votes')\n", | |
"plt.ylabel('% republican straight-ticket votes')\n", | |
"plt.savefig('corr-straight')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"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": "3.7.7" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 4 | |
} |
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