{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 可视化新特征" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "def getData():\n", " data = {}\n", " data[\"METTS MARK\"]={'salary': 365788, 'to_messages': 807, 'deferral_payments': 'NaN', 'total_payments': 1061827, 'loan_advances': 'NaN', 'bonus': 600000, 'email_address': 'mark.metts@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 585062, 'expenses': 94299, 'from_poi_to_this_person': 38, 'exercised_stock_options': 'NaN', 'from_messages': 29, 'other': 1740, 'from_this_person_to_poi': 1, 'poi': False, 'long_term_incentive': 'NaN', 'shared_receipt_with_poi': 702, 'restricted_stock': 585062, 'director_fees': 'NaN'}\n", " data[\"BAXTER JOHN C\"]={'salary': 267102, 'to_messages': 'NaN', 'deferral_payments': 1295738, 'total_payments': 5634343, 'loan_advances': 'NaN', 'bonus': 1200000, 'email_address': 'NaN', 'restricted_stock_deferred': 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J\"]={'salary': 'NaN', 'to_messages': 1433, 'deferral_payments': 'NaN', 'total_payments': 'NaN', 'loan_advances': 'NaN', 'bonus': 'NaN', 'email_address': 'danny.mccarty@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 758931, 'expenses': 'NaN', 'from_poi_to_this_person': 25, 'exercised_stock_options': 664375, 'from_messages': 215, 'other': 'NaN', 'from_this_person_to_poi': 2, 'poi': False, 'long_term_incentive': 'NaN', 'shared_receipt_with_poi': 508, 'restricted_stock': 94556, 'director_fees': 'NaN'}\n", " data[\"FUGH JOHN L\"]={'salary': 'NaN', 'to_messages': 'NaN', 'deferral_payments': 50591, 'total_payments': 50591, 'loan_advances': 'NaN', 'bonus': 'NaN', 'email_address': 'NaN', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 176378, 'expenses': 'NaN', 'from_poi_to_this_person': 'NaN', 'exercised_stock_options': 176378, 'from_messages': 'NaN', 'other': 'NaN', 'from_this_person_to_poi': 'NaN', 'poi': False, 'long_term_incentive': 'NaN', 'shared_receipt_with_poi': 'NaN', 'restricted_stock': 'NaN', 'director_fees': 'NaN'}\n", " data[\"SCRIMSHAW MATTHEW\"]={'salary': 'NaN', 'to_messages': 'NaN', 'deferral_payments': 'NaN', 'total_payments': 'NaN', 'loan_advances': 'NaN', 'bonus': 'NaN', 'email_address': 'matthew.scrimshaw@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 759557, 'expenses': 'NaN', 'from_poi_to_this_person': 'NaN', 'exercised_stock_options': 759557, 'from_messages': 'NaN', 'other': 'NaN', 'from_this_person_to_poi': 'NaN', 'poi': False, 'long_term_incentive': 'NaN', 'shared_receipt_with_poi': 'NaN', 'restricted_stock': 'NaN', 'director_fees': 'NaN'}\n", " data[\"KOENIG MARK E\"]={'salary': 309946, 'to_messages': 2374, 'deferral_payments': 'NaN', 'total_payments': 1587421, 'loan_advances': 'NaN', 'bonus': 700000, 'email_address': 'mark.koenig@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 1920055, 'expenses': 127017, 'from_poi_to_this_person': 53, 'exercised_stock_options': 671737, 'from_messages': 61, 'other': 150458, 'from_this_person_to_poi': 15, 'poi': True, 'long_term_incentive': 300000, 'shared_receipt_with_poi': 2271, 'restricted_stock': 1248318, 'director_fees': 'NaN'}\n", " data[\"SAVAGE FRANK\"]={'salary': 'NaN', 'to_messages': 'NaN', 'deferral_payments': 'NaN', 'total_payments': 3750, 'loan_advances': 'NaN', 'bonus': 'NaN', 'email_address': 'NaN', 'restricted_stock_deferred': 'NaN', 'deferred_income': -121284, 'total_stock_value': 'NaN', 'expenses': 'NaN', 'from_poi_to_this_person': 'NaN', 'exercised_stock_options': 'NaN', 'from_messages': 'NaN', 'other': 'NaN', 'from_this_person_to_poi': 'NaN', 'poi': False, 'long_term_incentive': 'NaN', 'shared_receipt_with_poi': 'NaN', 'restricted_stock': 'NaN', 'director_fees': 125034}\n", " data[\"IZZO LAWRENCE L\"]={'salary': 85274, 'to_messages': 496, 'deferral_payments': 'NaN', 'total_payments': 1979596, 'loan_advances': 'NaN', 'bonus': 'NaN', 'email_address': 'larry.izzo@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 5819980, 'expenses': 28093, 'from_poi_to_this_person': 28, 'exercised_stock_options': 2165172, 'from_messages': 19, 'other': 1553729, 'from_this_person_to_poi': 5, 'poi': False, 'long_term_incentive': 312500, 'shared_receipt_with_poi': 437, 'restricted_stock': 3654808, 'director_fees': 'NaN'}\n", " data[\"TILNEY ELIZABETH A\"]={'salary': 247338, 'to_messages': 460, 'deferral_payments': 'NaN', 'total_payments': 399393, 'loan_advances': 'NaN', 'bonus': 300000, 'email_address': 'elizabeth.tilney@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': -575000, 'total_stock_value': 1168042, 'expenses': 'NaN', 'from_poi_to_this_person': 10, 'exercised_stock_options': 591250, 'from_messages': 19, 'other': 152055, 'from_this_person_to_poi': 11, 'poi': False, 'long_term_incentive': 275000, 'shared_receipt_with_poi': 379, 'restricted_stock': 576792, 'director_fees': 'NaN'}\n", " data[\"MARTIN AMANDA K\"]={'salary': 349487, 'to_messages': 1522, 'deferral_payments': 85430, 'total_payments': 8407016, 'loan_advances': 'NaN', 'bonus': 'NaN', 'email_address': 'a..martin@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 2070306, 'expenses': 8211, 'from_poi_to_this_person': 8, 'exercised_stock_options': 2070306, 'from_messages': 230, 'other': 2818454, 'from_this_person_to_poi': 0, 'poi': False, 'long_term_incentive': 5145434, 'shared_receipt_with_poi': 477, 'restricted_stock': 'NaN', 'director_fees': 'NaN'}\n", " data[\"BUY RICHARD B\"]={'salary': 330546, 'to_messages': 3523, 'deferral_payments': 649584, 'total_payments': 2355702, 'loan_advances': 'NaN', 'bonus': 900000, 'email_address': 'rick.buy@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': -694862, 'total_stock_value': 3444470, 'expenses': 'NaN', 'from_poi_to_this_person': 156, 'exercised_stock_options': 2542813, 'from_messages': 1053, 'other': 400572, 'from_this_person_to_poi': 71, 'poi': False, 'long_term_incentive': 769862, 'shared_receipt_with_poi': 2333, 'restricted_stock': 901657, 'director_fees': 'NaN'}\n", " data[\"GRAMM WENDY L\"]={'salary': 'NaN', 'to_messages': 'NaN', 'deferral_payments': 'NaN', 'total_payments': 119292, 'loan_advances': 'NaN', 'bonus': 'NaN', 'email_address': 'NaN', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 'NaN', 'expenses': 'NaN', 'from_poi_to_this_person': 'NaN', 'exercised_stock_options': 'NaN', 'from_messages': 'NaN', 'other': 'NaN', 'from_this_person_to_poi': 'NaN', 'poi': False, 'long_term_incentive': 'NaN', 'shared_receipt_with_poi': 'NaN', 'restricted_stock': 'NaN', 'director_fees': 119292}\n", " data[\"CAUSEY RICHARD A\"]={'salary': 415189, 'to_messages': 1892, 'deferral_payments': 'NaN', 'total_payments': 1868758, 'loan_advances': 'NaN', 'bonus': 1000000, 'email_address': 'richard.causey@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': -235000, 'total_stock_value': 2502063, 'expenses': 30674, 'from_poi_to_this_person': 58, 'exercised_stock_options': 'NaN', 'from_messages': 49, 'other': 307895, 'from_this_person_to_poi': 12, 'poi': True, 'long_term_incentive': 350000, 'shared_receipt_with_poi': 1585, 'restricted_stock': 2502063, 'director_fees': 'NaN'}\n", " data[\"TAYLOR MITCHELL S\"]={'salary': 265214, 'to_messages': 533, 'deferral_payments': 227449, 'total_payments': 1092663, 'loan_advances': 'NaN', 'bonus': 600000, 'email_address': 'mitchell.taylor@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 3745048, 'expenses': 'NaN', 'from_poi_to_this_person': 0, 'exercised_stock_options': 3181250, 'from_messages': 29, 'other': 'NaN', 'from_this_person_to_poi': 0, 'poi': False, 'long_term_incentive': 'NaN', 'shared_receipt_with_poi': 300, 'restricted_stock': 563798, 'director_fees': 'NaN'}\n", " data[\"DONAHUE JR JEFFREY M\"]={'salary': 278601, 'to_messages': 865, 'deferral_payments': 'NaN', 'total_payments': 875760, 'loan_advances': 'NaN', 'bonus': 800000, 'email_address': 'jeff.donahue@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': -300000, 'total_stock_value': 1080988, 'expenses': 96268, 'from_poi_to_this_person': 188, 'exercised_stock_options': 765920, 'from_messages': 22, 'other': 891, 'from_this_person_to_poi': 11, 'poi': False, 'long_term_incentive': 'NaN', 'shared_receipt_with_poi': 772, 'restricted_stock': 315068, 'director_fees': 'NaN'}\n", " data[\"GLISAN JR BEN F\"]={'salary': 274975, 'to_messages': 873, 'deferral_payments': 'NaN', 'total_payments': 1272284, 'loan_advances': 'NaN', 'bonus': 600000, 'email_address': 'ben.glisan@enron.com', 'restricted_stock_deferred': 'NaN', 'deferred_income': 'NaN', 'total_stock_value': 778546, 'expenses': 125978, 'from_poi_to_this_person': 52, 'exercised_stock_options': 384728, 'from_messages': 16, 'other': 200308, 'from_this_person_to_poi': 6, 'poi': True, 'long_term_incentive': 71023, 'shared_receipt_with_poi': 874, 'restricted_stock': 393818, 'director_fees': 'NaN'}\n", "\n", " return data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "以下的代码计算了所有邮件中,每个人发给或收到 POIs 的邮件所占全部收发邮件的比例" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "import pickle\n", "\n", "def computeFraction( poi_messages, all_messages ):\n", " \"\"\" given a number messages to/from POI (numerator) \n", " and number of all messages to/from a person (denominator),\n", " return the fraction of messages to/from that person\n", " that are from/to a POI\n", " \"\"\"\n", "\n", "\n", " ### you fill in this code, so that it returns either\n", " ### the fraction of all messages to this person that come from POIs\n", " ### or\n", " ### the fraction of all messages from this person that are sent to POIs\n", " ### the same code can be used to compute either quantity\n", "\n", " ### beware of \"NaN\" when there is no known email address (and so\n", " ### no filled email features), and integer division!\n", " ### in case of poi_messages or all_messages having \"NaN\" value, return 0.\n", " fraction = 0.\n", " if poi_messages != \"NaN\" and all_messages != \"NaN\":\n", " fraction = poi_messages / all_messages\n", " else: fraction = 0.\n", "\n", "\n", " return fraction\n", "\n", "\n", "data_dict = getData() \n", "\n", "submit_dict = {}\n", "for name in data_dict:\n", "\n", " data_point = data_dict[name]\n", "\n", " print\n", " from_poi_to_this_person = data_point[\"from_poi_to_this_person\"]\n", " to_messages = data_point[\"to_messages\"]\n", " fraction_from_poi = computeFraction( from_poi_to_this_person, to_messages )\n", " #print (\"The fraction of mails from POIs\",fraction_from_poi)\n", " data_point[\"fraction_from_poi\"] = fraction_from_poi\n", "\n", "\n", " from_this_person_to_poi = data_point[\"from_this_person_to_poi\"]\n", " from_messages = data_point[\"from_messages\"]\n", " fraction_to_poi = computeFraction( from_this_person_to_poi, from_messages )\n", " #print (\"The fraction of mails to POIs\", fraction_to_poi, \"\\n\")\n", " submit_dict[name]={\"from_poi_to_this_person\":fraction_from_poi,\n", " \"from_this_person_to_poi\":fraction_to_poi}\n", " data_point[\"fraction_to_poi\"] = fraction_to_poi\n", " \n", " \n", "#####################\n", "\n", "def submitDict():\n", " return submit_dict\n" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "image/png": 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VAADp6mS1BJCO5OUMKyjXHVTMlVLNOlYtgeAjwH9I+qCkDwL/QTIBrCvVs5xhrpLKm6tcEQ0MwOio8wNmHaqWWkPXA2cCPwceA86IiBuyblirDC0fYvTkUQb6BhBioG+A0ZNHpyWKC0nliR0TBLEvqdy1waBSt09hKc0ODgK5CuhmZdS8VKWkZ1E0fyAiWtJp3i5LVeYuqVwuR7BwYcdfCZSOEoPkCrBc8DfrZNWSxTNeEUg6RdJPgIeBbwObgK81tIUdKHdJ5aGh5Ed/YCAZHdQl3UHDa4anBAGAyV2TDK8ZblGLzJqvlhzBB0lm/T4YEUuBlcB3Mm1VB8hlUnloKOkG2ru347uDCnIX0M3KqCUQ7IqIbSSjh3rStQiOzbhdba+epLK1r1wGdLMStQSCxyUdANwJjEn6KLA722a1v1qTytbeHNDNaptZ/DvATpKgMQT0AWPpVULTtUuy2LrH2LoxhtcMs3nHZvr7+hlZOeKAbl2nWrK4aiBIVxm7PSJelVXj6uVAYGZWv1mPGoqIPcCkpL5MWmZmZi1XS47gN8A6SZ+S9LHCLeuGdSJPTDKzTlRLzaCvpjerwuWrZ8999GatVW2Fsn6AiPhMuVvzmtgZ6pqY5NW99sldqQ6zNlSta+jLhTuSyq1bbEVqnpjk1b2m8MzejPmkw2pQLRAULz5/eNYN6XQ1T0yqtrpXDnlmb4Z80mE1qhYIosJ9K6PmiUmVyjlXK/PcYlkmwT2zN0M+6bAaVQsEx0h6QtKvgKPT+09I+pWkJ5rVwE5R80zjSuWc23R1r6z78D2zN0MdeNJhrVFzGep20fETyjqsnHMzym171FBGBgfLry9dWEPCcmVOZajzruHdIh1WzrkZffhDy4fYdPEm9l62l00Xb+r6INC0+SYjI8lJRjEvKWplOBBU0dBukeLRG8PDyf+M1co5t8loD/fhN1ZTh8t22EmHtY67hqpoWLdIvd1BbdR95BW8Git3K9tZ23DX0Cw1rFuk3tEbbTLao9B3P7lrknmaB+By23Pk4bLWjhwIqmhYt0i9ozfaYLRHcRcGwJ7Ys280j4PA7LmrzdqRA0EVDRvaWGFo6JYDe6b2DRfyApW66xoxxLTG3INn/Gaj3N8UwJNPPcnYujEXLrSWqKXoXG4VznznPLRxZGRan/+ve+Hdr9jDLYXCdPcxPS9QrBGjPUpzDxMT7H7L+VzytYv452Xbp3w/d2Fko/C3c9HXLmLbzqfXdtq2cxvn33I+EcGuvbsAFy605nGyuFnGxtjyznP5b7/cw+Y+eO9KuPHo5KmBvgE2XUn5Md+QjPYYGZl7orjCuPJNfbD0L5L7hUTw8JrhsknNQnvdRTQ3lZLG5TiRbI1QLVnsK4JmGRqif8M5ZWt1bN6xGSqdaEuNm/xTIcfQv+Pp+4Xun5GVI9NGCxX4THXu6rmy8lWYZS3THIGkEyU9IGmDpEvLPH+JpPWS7pO0RtJAlu1ptHr7c6smCptReqLCe20uWX9u847NU0pmlON8wdzUkxx2ItmyllkgSNc7vgp4HXAUcLako0p2uwdYERFHA58HrsiqPY1W18SgNEH78CUTTFwpzr7v6af2JZ+bMQu0zGf8ujfppipW+OEpzPjVlEK0T/OZ6uyVSxovmLeA3p7eKdtcd8maIcsrghOADRGxMSKeAm4CTi3eISK+GRGFvoe7gEMzbE9D1TyqpqgUsAL6Hw8+eav4n/eVjMlvxizQks948tmLuPC03n25Cij/w+Mhj41Xrkjhtadey6dP+/TMhQvNGiyzZLGkM4ETI+It6eNzgBdGxIUV9v9n4GcR8bdlnlsFrALo7+9/wUSlpGoT9XyghyjT4y/E3sv2Pr2hzQt/1VLwzbOLzTpfq5LF5foTykYdSW8EVgAvK/d8RIwCo5CMGmpUA+eiv6+/7KiPaWfJbTA5rJqh5UMz/pg3bBitmbWlLLuGtgCHFT0+FHi0dCdJrwKGgVMi4rcZtqehap5s1mHrD1TS1AqhbVJwzywvsgwEa4FlkpZKWgCcBawu3kHSccAnSILAYxm2peFqXojGpYDr4+UVzZou0wllkk4CrgTmAddGxIiky4HxiFgt6d+A5cBP05dsjohTqr1nR04oGxtLCsZt3pxcCTRicli3avOcilmnqpYj8Mxia6nSZPXDlySjq6aRkvUbzGxWPLPY2lLpaKSJHRM80if6Hy8TCTosp2LWSVx91Fqm3FyMS18ZTPaWDDhzTsUsUw4ENejW0sCt/l7lZibfeDS89eTw8opmTeSuoRmU677ohoJr7fC9Ks3F+M4fDcAXNjWlDWbmK4IZdesCLe3wvRq28I+ZzYkDwQy6dYGWdvheNc/FMLNMuWtoBjWXkugw7fK9ailxYWbZyt0VQb0J0m7tvujW72Vm9ctVIKhrDYFUK7ovmjGax90yZlaQq5nFldaJbac1YV3y2cyyUG1mca6uCNohQTqTdhjNY2b5kqtA0AkrbXVCsDKz7pKrQNAJCdJOCFZm1l1yFQianSCdTdK3E4KVmXWXXCWLm2kuSd9a1hE2M6uH1yNogU4YoTRXDlhmncOjhlqg3qRvqyuB1ms2czLMrD05EGSknqRv1j+qWQQZD3M16x65CwTNOvOuJ+mb5Y9qVkHGw1zNukeuAsFcfxTrCSL1jFDK8kc1qyDjYa5Wj07r+sybXFUfnelHsVriczYLudRaWTPLSqBZBZmRlSNlR0V5mKuVaodFkKy6XI0a6vlAD0H579vb08uuvbue3pceDtr/ILbv3E5/Xz9PPvUk23Zum/a6RowCyrK+UJajlzxqyGqRhxF0ncCjhlKVzrCFpgQBgL3sZdvObfu6kMoFAWhM9025bqRzjzmX4TXDc76UznKC2tDyITZdvIm9l+1l08WbHASsLOeT2l+uAsHIyhF6e3qnbOvt6a14lVCLIBrS51n8o3rSspO4ZvyahiR4S4PMov0Xsf/8/Tnni+e4r9aawvmk9perQAAgqerj2ZjYMcH5t5zP4isWz/kM/oKvXsDHxz8+LTg1IsEbBNt3bp9ypeOx/5Y1l01pf7kKBMNrhnlqz1NTtj215yl6VNth6FEPi/ZfVPa5p/Y8Necf2LF1Y1wzfk3F52dzKV08UgrIJMCYVeNFkNqfk8WpBfMWTAsS5SzsXTht5FEl9SbDKiXVZvt+tbwnJDmSvZftret9zayzOFmcqtQnOdA3wLWnXjvljOXtK97OPM2btu/krsmy28uZ2DFRVzdRtR9soVldStdyFeG+WrN8y1UgqNZXWToC5uo/vpq9Uf4seU/smfY+ldTTTVQtwLxtxdtmdSk904+8+2rNLFeBoN6+yoP3P7js9kX7L5o2Eqd0NFKxWvvh98Seis9d/cdXz/j6csoFP5EkyN1Xa2aQcSCQdKKkByRtkHRpmeefIenm9PnvSRrMsj0A5938RiYenyAimHh8gvNufuO+54qnwS++YnHFuQPbdm7j0/d8et/jAxYcwFuOf0vVM/rSLppyU+4H+gYqvn62I5HKBb8bzriBuCyaPva/WWUGml3OwOUTrNNlliyWNA94EHg1sAVYC5wdEeuL9rkAODoi3ibpLOD0iHhDtfedS7K492/E7vlA8YjRgPm74bo3/N9ps3vrMVMSuTjRW2km8bnHnMun7vlUxaR1o2Ybt0KWs6db8Tmt+jyz2WrJwjSSXgS8PyJemz5+D0BE/H3RPren+3xX0nzgZ8CSqNKouQQCvV9Tg0BBwMCBAzOOrpnJPM0r270jxA1n3LDvh6HalPtKpSyK9+nEafnNKjPQ7HIGLp9gnaJVo4YOAR4perwl3VZ2n4jYDewApg3Ul7RK0rik8a1bt2bS2EZMdy+XRBaaluitNuV++87tmbezFZpVZqDZ5QxcPsG6QZaBoMK5d937EBGjEbEiIlYsWbKkIY0r1YghlIXka2l/fGmit9qU+5na0alDPZtVZqDZ5QxcPsG6QZaBYAtwWNHjQ4FHK+2Tdg31AdVPiedg/m6mh5k0R1BudE09Kg1DLddPXG0Ya7V2dPJQz2aVGWh2OQOXT7BukGUgWAssk7RU0gLgLGB1yT6rgXPT+2cCd1TLD8zVrr+Np4NBepu/O9lerjjbov0X7TuzX7l05b5RQfM0j5VLV856yny1YazFzxU+Czp/qGezygw0u5yByydYN8i0xISkk4ArgXnAtRExIulyYDwiVkvaD7gBOI7kSuCsiNhY7T3nkiw2M8urasniTFcoi4jbgNtKtr2v6P5vgD/Jsg1mZlZdrmYWm5nZdA4EZmY550BgZpZzDgRmZjnnQGBmlnMOBGZmOedAYGaWcx23ZrGkrcDcyoQmFgO/aMD7dBMfk+l8TKbzMZmqU47HQESULdbWcYGgUSSNV5pll1c+JtP5mEznYzJVNxwPdw2ZmeWcA4GZWc7lORCMtroBbcjHZDofk+l8TKbq+OOR2xyBmZkl8nxFYGZmOBCYmeVe1wUCSSdKekDSBkmXlnn+GZJuTp//nqTBoufek25/QNJrm9nuLM32mEgalLRT0r3p7Zpmtz0rNRyTl0r6gaTdks4see5cST9Jb+eWvrZTzfGY7Cn6OyldibBj1XBMLpG0XtJ9ktZIGih6rnP+TiKia24kK6E9BBwOLAB+CBxVss8FwDXp/bOAm9P7R6X7PwNYmr7PvFZ/pxYfk0HgR63+Di06JoPA0cD1wJlF2w8GNqb/HpTeP6jV36mVxyR97slWf4cWHZNXAAvT+28v+n+no/5Ouu2K4ARgQ0RsjIingJuAU0v2ORX4THr/88BKSUq33xQRv42Ih4EN6ft1urkck2414zGJiE0RcR+wt+S1rwW+ERHbI+KXwDeAE5vR6IzN5Zh0q1qOyTcjYjJ9eBdwaHq/o/5Oui0QHAI8UvR4S7qt7D4RsRvYASyq8bWdaC7HBGCppHskfVvSH2Xd2CaZy3/rPP+dVLOfpHFJd0k6rbFNa5l6j8mbga/N8rUtlemaxS1Q7iy2dHxspX1qeW0nmssx+SnQHxHbJL0A+LKk50fEE41uZJPN5b91nv9OqumPiEclHQ7cIWldRDzUoLa1Ss3HRNIbgRXAy+p9bTvotiuCLcBhRY8PBR6ttI+k+UAfsL3G13aiWR+TtJtsG0BE3E3SX3pk5i3O3lz+W+f576SiiHg0/Xcj8C3guEY2rkVqOiaSXgUMA6dExG/reW276LZAsBZYJmmppAUkic/SEQyrgUIG/0zgjkiyO6uBs9IRNEuBZcD3m9TuLM36mEhaImkeQHqmt4wk6dXpajkmldwOvEbSQZIOAl6Tbut0sz4m6bF4Rnp/MfBiYH1mLW2eGY+JpOOAT5AEgceKnuqsv5NWZ6sbfQNOAh4kOXsdTrddTvIfCmA/4HMkyeDvA4cXvXY4fd0DwOta/V1afUyA1wP3k4yW+AFwcqu/SxOPye+TnNX9GtgG3F/02vPTY7UBeFOrv0urjwnwh8C69O9kHfDmVn+XJh6TfwN+Dtyb3lZ34t+JS0yYmeVct3UNmZlZnRwIzMxyzoHAzCznHAjMzHLOgcDMLOccCKxtlFSwvLe4Muwc3vM0SUcVPb48nQCUiSy+wwyfd56krelnrZf01qLnTkurYv5Y0rri0g+SriutIGr51W0lJqyz7YyIYys9KWl+JLWQ6nEa8BXSCU4R8b45tK8WWXyHmdwcERdKehZwf1oG+r8CHwZeHREPp5MkvyFpYySF48z28RWBtbX0jPdzkm4Fvi7pgLTu+w/Ss9xTi/b9s/QM+IeSbpD0h8ApwD+kZ8xHFJ8JS1qZFtRbJ+naotmxmyR9oOgznptuf1nRmf49kp45y+8gSf8g6Ufp+78h3e/laXG/z0p6UNKHJA1J+n663xHVPieSma0PAQPAXwF/F0klXdJ//x54V5n2fUhP19T/cC3fybqLrwisnewv6d70/sMRcXp6/0XA0RGxPa2FdHpEPJGWM7grPQM+imRm+Isj4heSDk73Xw18JSI+D6C0urak/YDrgJUR8aCk60nqyV+ZfuYvIuJ4SReQ/Ki+Jf33HRHxHUkHAL+Z5Xd4PXAscAywGFgr6c50v2OA55HUv9oIfDIiTpB0EfBO4OJKBy8tA3I4yUzW55NcERQbB95R8jX/mkEAAAIMSURBVJqDgdOB50ZESDqw0vtb93IgsHZSqVvlGxGxPb0v4O8kvZSkLv4hwH8BXgl8PiJ+AVC0fyXPIfmhfjB9/BmSH8lCIPhi+u/dwBnp/e8A/yhpDPhiRGyZ5Xd4CXBjROwBfi7p2yTlG54A1kbETwEkPQR8PX3NOpJFUMp5g6SXAL8F/lcabET5KrOl254gCWiflPRVkm40yxl3DVkn+HXR/SFgCfCC9Af35yS1ksr9yFUz08I7hSqSe0hPmCLiQyRXBvuTXIk8t47PK/4O1T77t0X39xY93kvlE7ebI+LYiHhhRHwp3XY/SVnkYsdTUgwuzVecAHyBJJ/y/6q0zbqUA4F1mj7gsYjYJekVJP3hAGuAP5W0CPZ1eQD8CijXl/9jYFDSf08fnwN8u9oHSzoiItZFxP8m6WapJxAUu5PkLH6epCXAS2l8pdsPA+8pjFpK/30v8JHindIurr6IuI2k26liotu6l7uGrNOMAbdKGiep9vhjgIi4X9II8G1Je4B7gPNIlhf8F0l/TlJim3T/30h6E/C5NO+wFrhmhs++OA0+e0jOrL82w/6VfIkkZ/BDkquYd0fEz+q8wqgqIu6V9Nckx6oX2JV+zr0luz4TuCXNmQj4i0a1wTqHq4+ameWcu4bMzHLOgcDMLOccCMzMcs6BwMws5xwIzMxyzoHAzCznHAjMzHLu/wN4aJeuKfx3uAAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import matplotlib\n", "%matplotlib inline\n", "\n", "#print(data_dict[\"METTS MARK\"])\n", "\n", "for name in data_dict:\n", " if data_dict[name][\"poi\"]:\n", " plt.scatter(data_dict[name][\"fraction_from_poi\"], data_dict[name][\"fraction_to_poi\"],c=\"r\")\n", " else:\n", " plt.scatter(data_dict[name][\"fraction_from_poi\"], data_dict[name][\"fraction_to_poi\"],c=\"g\")\n", "plt.xlabel(\"Fractions From POIs\")\n", "plt.ylabel(\"Fractions To POIs\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "根据上边的图片看来,其实还是没有太明显的特征.但是可以看到,**POIs 发送给 POIs 的邮件数量普遍占据所有发送邮件的 17% 及以上**,\n", "所以,如果发送给 POIs 的邮件数量低于总数的 17% 就很有可能此人不是 POIs" ] }, { "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": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 4 }