{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'retina'\n",
"\n",
"import numpy as np\n",
"import matplotlib\n",
"from matplotlib import pyplot as plt\n",
"import pandas as pd\n",
"from datetime import date, datetime\n",
"from lifelines import KaplanMeierFitter, CoxPHFitter, NelsonAalenFitter\n",
"\n",
"matplotlib.rcParams['figure.figsize'] = (12.0, 6.0)\n",
"plt.style.use('seaborn-deep')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Definition of censoring and death\n",
"\n",
"Quitting is death, all else is censoring. This is different than the [original article](https://fivethirtyeight.com/features/two-years-in-turnover-in-trumps-cabinet-is-still-historically-high/)'s author's rules, who stated that switching roles _within_ a cabinent is an \"event\". "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
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" 0 | \n",
" Trump | \n",
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"text/plain": [
" president president_start_date president_end_date\n",
"0 Trump 2017-01-20 2019-03-05\n",
"1 Obama 2009-01-20 2017-01-20\n",
"2 Bush 43 2001-01-20 2009-01-20\n",
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},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_df = pd.read_csv(\"https://raw.githubusercontent.com/fivethirtyeight/data/master/cabinet-turnover/cabinet-turnover.csv\",\n",
" na_values=['Still in office', '#VALUE!']\n",
" )\n",
"TODAY = datetime.today().date()\n",
"\n",
"INAUG_DATES = {\n",
" 'Trump': date(2017, 1, 20),\n",
" 'Obama': date(2009, 1, 20),\n",
" 'Bush 43': date(2001, 1, 20),\n",
" 'Clinton': date(1993, 1, 20),\n",
" 'Bush 41': date(1989, 1, 20),\n",
" 'Reagan': date(1981, 1, 20),\n",
" 'Carter': date(1977, 1, 20)\n",
"}\n",
"\n",
"presidential_terms = pd.DataFrame(list(INAUG_DATES.items()))\n",
"presidential_terms.columns = ['president', 'president_start_date']\n",
"presidential_terms['president_end_date'] = presidential_terms['president_start_date'].shift(1).fillna(TODAY)\n",
"presidential_terms"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def fill_end(series):\n",
" end, president = series\n",
" if pd.notnull(end) and end.endswith('admin'):\n",
" next_pres ,_ = end.split(' ')\n",
" if next_pres == 'Bush':\n",
" next_pres = next_pres + ' 43' if president == 'Clinton' else next_pres + ' 41'\n",
" return INAUG_DATES[next_pres].strftime('%m/%d/%y')\n",
" else:\n",
" return end\n",
" \n",
"def fill_start(series):\n",
" end, president = series\n",
" if pd.notnull(end) and end.endswith('admin'):\n",
" prev_pres ,_ = end.split(' ')\n",
" if prev_pres == 'Bush':\n",
" prev_pres = prev_pres + ' 43' if president == 'Obama' else prev_pres + ' 41'\n",
" return INAUG_DATES[president].strftime('%m/%d/%y')\n",
" else:\n",
" return end\n",
" \n",
" \n",
"raw_df['end'] = raw_df[['end', 'president']].apply(fill_end, axis=1)\n",
"raw_df['start'] = raw_df[['start', 'president']].apply(fill_start, axis=1)\n",
"\n",
"raw_df['end'] = pd.to_datetime(raw_df['end']).dt.date\n",
"raw_df['end'] = raw_df['end'].fillna(TODAY)\n",
"raw_df['start'] = pd.to_datetime(raw_df['start']).dt.date"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"raw_df = raw_df.merge(presidential_terms, left_on='president', right_on='president')\n",
"raw_df['event'] = (raw_df['end'] < raw_df['president_end_date']) & pd.notnull(raw_df['end'])\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# we need to \"collapse\" individuals into rows, because they may change positions, but that's not quitting...\n",
"def collapse(df):\n",
" return df.groupby('appointee', as_index=False).aggregate({\n",
" 'start': 'min', 'end': 'max', 'event': 'all', 'president': 'last', 'president_end_date': 'last'\n",
" })\n",
"\n",
"raw_df = raw_df.groupby('president', as_index=False).apply(collapse).reset_index(drop=True)\n",
"raw_df['T'] = (raw_df['end'] - raw_df['start']).dt.days\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
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\n",
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\n",
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\n",
" \n",
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" 672 | \n",
"
\n",
" \n",
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\n",
" \n",
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\n",
" \n",
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\n",
" \n",
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" Tom Price | \n",
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\n",
" \n",
" 286 | \n",
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"
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"text/plain": [
" appointee start end event president \\\n",
"267 Jeff Sessions 2017-02-09 2018-11-07 True Trump \n",
"268 Jim Mattis 2017-01-20 2018-12-31 True Trump \n",
"269 John Kelly 2017-01-20 2018-12-31 True Trump \n",
"270 Kirstjen Nielsen 2017-12-06 2019-03-05 False Trump \n",
"271 Linda McMahon 2017-02-14 2019-03-05 False Trump \n",
"272 Mick Mulvaney 2017-02-16 2019-03-05 False Trump \n",
"273 Mike Pence 2017-01-20 2019-03-05 False Trump \n",
"274 Mike Pompeo 2017-01-23 2019-03-05 False Trump \n",
"275 Nikki Haley 2017-01-27 2018-12-31 True Trump \n",
"276 Reince Priebus 2017-01-20 2017-07-28 True Trump \n",
"277 Rex Tillerson 2017-02-01 2018-03-31 True Trump \n",
"278 Rick Perry 2017-03-02 2019-03-05 False Trump \n",
"279 Robert Lighthizer 2017-05-15 2019-03-05 False Trump \n",
"280 Robert Wilkie 2018-07-30 2019-03-05 False Trump \n",
"281 Ryan Zinke 2017-03-01 2019-01-02 True Trump \n",
"282 Scott Pruitt 2017-02-17 2018-07-06 True Trump \n",
"283 Sonny Perdue 2017-04-25 2019-03-05 False Trump \n",
"284 Steve Mnuchin 2017-02-13 2019-03-05 False Trump \n",
"285 Tom Price 2017-02-10 2017-09-29 True Trump \n",
"286 Wilbur Ross 2017-02-28 2019-03-05 False Trump \n",
"\n",
" president_end_date T \n",
"267 2019-03-05 636 \n",
"268 2019-03-05 710 \n",
"269 2019-03-05 710 \n",
"270 2019-03-05 454 \n",
"271 2019-03-05 749 \n",
"272 2019-03-05 747 \n",
"273 2019-03-05 774 \n",
"274 2019-03-05 771 \n",
"275 2019-03-05 703 \n",
"276 2019-03-05 189 \n",
"277 2019-03-05 423 \n",
"278 2019-03-05 733 \n",
"279 2019-03-05 659 \n",
"280 2019-03-05 218 \n",
"281 2019-03-05 672 \n",
"282 2019-03-05 504 \n",
"283 2019-03-05 679 \n",
"284 2019-03-05 750 \n",
"285 2019-03-05 231 \n",
"286 2019-03-05 735 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_df.tail(20)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"number of subjects = 287\n",
" number of events = 158\n",
" log-likelihood = -1310.480\n",
" hypothesis = lambda_0_ != 1, lambda_1_ != 1, lambda_2_ != 1\n",
"\n",
"---\n",
" coef se(coef) lower 0.95 upper 0.95 p -log2(p)\n",
"lambda_0_ 2872.6704 280.8217 2322.2701 3423.0708 <5e-05 79.1248\n",
"lambda_1_ 154.6505 30.4338 95.0013 214.2998 <5e-05 21.1000\n",
"lambda_2_ 1101.0836 189.0864 730.4810 1471.6862 <5e-05 27.3221\n"
]
},
{
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