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@avonmoll
Last active August 29, 2015 14:19
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{
"metadata": {
"name": "",
"signature": "sha256:5de6683faffdfa80db24dabd1315022ea26b0c73271e636b9ba52e1dcea1a7d6"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Flight Frequency"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"%cd 'C:\\Users\\Alexander\\Documents\\School\\CSE 6730\\Project 2\\EbolaSimCode'"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"C:\\Users\\Alexander\\Documents\\School\\CSE 6730\\Project 2\\EbolaSimCode\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.read_csv('ebola_4.csv', index_col = False)\n",
"df_grouped = df.groupby(['Origin','Destination'])\n",
"\n",
"#df_grouped['Seats'].mean()\n",
"\n",
"for (orig,dest),group in df_grouped:\n",
" print orig, dest, len(group)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"ABJ BKO 707\n",
"ABJ CKY 341\n",
"ABJ DKR 851\n",
"ABJ LOS 279\n",
"ABJ ROB 50\n",
"ABV ACC 265\n",
"ABV ADD 203\n",
"ABV CAI 186\n",
"ABV FRA 363\n",
"ABV LHR 625\n",
"ABV NIM 65\n",
"ABV SSG 156\n",
"ACC ABV 263\n",
"ACC DKR 156\n",
"ACC FNA 309\n",
"ACC LOS 2333\n",
"ACC MLW 9\n",
"ACC ROB 640\n",
"ADD ABV 204\n",
"ADD BKO 163\n",
"ADD LOS 442\n",
"ALG BKO 162\n",
"ALG DKR 69\n",
"AMS LOS 365\n",
"ATL LOS 294\n",
"BEY KAN 54\n",
"BEY LOS 158\n",
"BJL DKR 760\n",
"BJL FNA 323\n",
"BKO ABJ 786\n",
"BKO ADD 162\n",
"BKO ALG 110\n",
"BKO CDG 356\n",
"BKO CKY 357\n",
"BKO CMN 398\n",
"BKO COO 354\n",
"BKO DKR 1157\n",
"BKO LFW 222\n",
"BKO NBO 157\n",
"BKO NKC 152\n",
"BKO ORY 123\n",
"BKO OUA 567\n",
"BKO TUN 53\n",
"BRU DKR 362\n",
"CAI ABV 187\n",
"CAI KAN 312\n",
"CAI LOS 261\n",
"CDG BKO 356\n",
"CDG CKY 182\n",
"CDG DKR 365\n",
"CDG LOS 363\n",
"CKY ABJ 327\n",
"CKY BKO 352\n",
"CKY CDG 182\n",
"CKY CMN 279\n",
"CKY DKR 303\n",
"CKY OXB 157\n",
"CMN BKO 398\n",
"CMN CKY 273\n",
"CMN DKR 730\n",
"CMN FNA 77\n",
"CMN ROB 51\n",
"COO BKO 355\n",
"COO DKR 126\n",
"COO LOS 417\n",
"DKR ABJ 812\n",
"DKR ACC 208\n",
"DKR ALG 53\n",
"DKR BJL 726\n",
"DKR BKO 1085\n",
"DKR BRU 362\n",
"DKR CDG 365\n",
"DKR CKY 325\n",
"DKR CMN 730\n",
"DKR COO 126\n",
"DKR DXB 87\n",
"DKR FNA 123\n",
"DKR IAD 345\n",
"DKR IST 156\n",
"DKR JFK 490\n",
"DKR JNB 346\n",
"DKR LIS 366\n",
"DKR LOS 198\n",
"DKR LPA 105\n",
"DKR MAD 437\n",
"DKR MXP 152\n",
"DKR NKC 570\n",
"DKR ORY 63\n",
"DKR OUA 100\n",
"DKR OXB 413\n",
"DKR RAI 342\n",
"DKR TUN 151\n",
"DLA LOS 397\n",
"DOH LOS 365\n",
"DXB DKR 87\n",
"DXB LOS 832\n",
"FCO LOS 157\n",
"FNA ACC 320\n",
"FNA BJL 286\n",
"FNA CMN 62\n",
"FNA DKR 113\n",
"FNA LHR 159\n",
"FNA LOS 221\n",
"FNA MLW 104\n",
"FNA ROB 32\n",
"FRA ABV 363\n",
"FRA LOS 362\n",
"IAD DKR 352\n",
"IST LOS 208\n",
"JED KAN 243\n",
"JFK DKR 166\n",
"JFK LOS 118\n",
"JNB DKR 684\n",
"JNB LOS 746\n",
"KAN BEY 54\n",
"KAN CAI 312\n",
"KAN JED 241\n",
"KAN KRT 31\n",
"LBV LOS 5\n",
"LFW BKO 230\n",
"LFW LOS 58\n",
"LHR ABV 625\n",
"LHR FNA 161\n",
"LHR LOS 1142\n",
"LIS DKR 366\n",
"LOS ABJ 271\n",
"LOS ACC 2448\n",
"LOS ADD 443\n",
"LOS AMS 365\n",
"LOS ATL 295\n",
"LOS BEY 157\n",
"LOS CAI 261\n",
"LOS CDG 363\n",
"LOS CMN 186\n",
"LOS COO 583\n",
"LOS DKR 219\n",
"LOS DLA 410\n",
"LOS DOH 365\n",
"LOS DXB 833\n",
"LOS FNA 220\n",
"LOS FRA 362\n",
"LOS IST 205\n",
"LOS JFK 118\n",
"LOS JNB 730\n",
"LOS LBV 8\n",
"LOS LFW 54\n",
"LOS LHR 1146\n",
"LOS MAD 156\n",
"LOS NBO 332\n",
"LOS SSG 5\n",
"LPA DKR 105\n",
"MAD DKR 436\n",
"MAD LOS 156\n",
"MLW ACC 9\n",
"MLW FNA 104\n",
"MXP DKR 150\n",
"NBO BKO 157\n",
"NBO LOS 488\n",
"NDJ KAN 70\n",
"NIM ABV 65\n",
"NKC BKO 140\n",
"NKC DKR 584\n",
"ORY BKO 123\n",
"ORY DKR 63\n",
"OUA BKO 591\n",
"OUA DKR 99\n",
"OXB CKY 157\n",
"OXB DKR 413\n",
"RAI DKR 339\n",
"ROB ABJ 62\n",
"ROB ACC 650\n",
"ROB BRU 101\n",
"ROB CMN 65\n",
"ROB FNA 17\n",
"SSG ABV 156\n",
"TUN BKO 91\n",
"TUN DKR 151\n"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from dateutil.parser import parse\n",
"\n",
"T_mean = []\n",
"T_std = []\n",
"seats = []\n",
"routes = pd.read_csv('ebola-sim/relevant_routes.csv')\n",
"\n",
"for (orig,dest),group in df_grouped:\n",
" #print orig, dest, len(group)\n",
" dates = list(group['Timeseries'])\n",
" for i in range(len(dates)):\n",
" dates[i] = parse(dates[i])\n",
" dates = numpy.sort(dates)\n",
" delta = numpy.diff(dates)\n",
" for i in range(len(delta)):\n",
" delta[i] = delta[i].days\n",
" h = hist(delta,bins = range(max(delta)+2),normed = True)\n",
" title('%s to %s'%(orig,dest))\n",
" text(0.5, 0.25, 'Mean = %0.4f\\nStd = %0.3f'%(mean(delta), std(delta)))\n",
" show()\n",
" \n",
" T_mean.append(mean(delta))\n",
" T_std.append(std(delta))\n",
" seats.append(int(group['Seats'].mean()))\n",
" \n",
" routes.loc[(routes['SourceAirport'] == orig) & (routes['DestAirport'] == dest), 'MeanPeriod'] = mean(delta)\n",
" routes.loc[(routes['SourceAirport'] == orig) & (routes['DestAirport'] == dest), 'StdPeriod'] = std(delta)\n",
" routes.loc[(routes['SourceAirport'] == orig) & (routes['DestAirport'] == dest), 'Seats'] = int(group['Seats'].mean())"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x7958518>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8ffe9e8>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x8ff90b8>"
]
},
{
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"text": [
"<matplotlib.figure.Figure at 0x9605be0>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x9605c88>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x95f8898>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x98861d0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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FTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x9606c50>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x9010c50>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8d32d68>"
]
},
{
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"text": [
"<matplotlib.figure.Figure at 0x8fee908>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc090080>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc0a5dd8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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5CajL4xkR8Wj+aXIp2fGhfweu6q69L3QyM0uUv7LPzCxRDngzs0Q54M3MEuWA\nNzNLlAPezCxRDngzs0Q54M3MEuWANzNL1P8Hbm3tR03iP+IAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x8f06a58>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc5860f0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc5861d0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xcc90cf8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc89c128>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc8c5b00>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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Nyt6fxdRZCX0qqY+kL2Sf9wL+DWjMaVYJ/VmwznL3Z0T8Z0QMjIg9gBOBByJi\nSk6zTvdloStUO1vkFnHRUzF1AscDp0laB3xIptM3K0m3AKOBPpKWAReRObunYvqyUI1UQD9mHQJ8\nA/iLpA1/3P8J7A6V05/F1Ell9GlfYJakrcgMEudExP2V9rdeTJ1URn+2FgBd7UtfxGRmlkD+mj0z\nswRyuJuZJZDD3cwsgRzuZmYJ5HA3M0sgh7uZWQI53M3MEsjhbmaWQP8fiPxowk6Y9owAAAAASUVO\nRK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0xc898048>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc896588>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8d3deb8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc5728d0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc572b70>"
]
},
{
"metadata": {},
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"text": [
"<matplotlib.figure.Figure at 0x9868eb8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x98689b0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x934a860>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x95f13c8>"
]
},
{
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"png": 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MmQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x95f1278>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8fdc2e8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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StgAbyQz6biXpXmA00FvSKuBaMmf3VMxYFqqRChjHrGOAs4HfS9r+w/1PwMFQ\nOeNZTJ1Uxpj2AWZK6kTmIHFWRDxZaT/rxdRJZYxnrgDY1bH0RUxmZgnkr9kzM0sgh7uZWQI53M3M\nEsjhbmaWQA53M7MEcribmSWQw93MLIEc7mZmCfSffHh6DHjcq5cAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0xc577550>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x9886d68>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x8feea90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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Am5llygFvZpYpB7yZWaYc8GZmmfr/S0Oor4vo7GYAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0xc092b38>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x900a780>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x900ab38>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc564c18>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0xcc78160>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8ee6240>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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pba8+eRHxPyOiPCI+B5wFPBkRE0rdr1KR1FtS3+R5H+BUoN0j8EoW8BGxjewZ\nsI8BrwK/242PlJgOLAD+q6RVkn5Q6j6V0AnAOcCY5BCwJZKqSt2pEhkAPJnMwdcAsyJiTon71BPs\n7tO7nwXm5/xc/DEiHm+vok90MjNLKd+yz8wspRzwZmYp5YA3M0spB7yZWUo54M3MUsoBb2aWUg54\nM7OUcsCbmaXU/wflPS5+YK0RZgAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x8ee6a90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc583cf8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8efef28>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc8b3a20>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8fdb160>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc0bd7b8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x98890b8>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x93219b0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xcb5e390>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xcb5ecf8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8f0a5f8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc0a69e8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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54M3McsoBb2aWUw54M7OccsCbmeWUA97MLKf+Pz1jJXH1RgQiAAAAAElFTkSu\nQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x9878470>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc598c88>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8f05e48>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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bpP1IBolzImJhs/2u11MnzdGfpQJgT/vSNzGZmeWQP2bPzCyHHO5mZjnkcDcz\nyyGHu5lZDjnczcxyyOFuZpZDDnczsxxyuJuZ5dD/ByjPEvdY9UpjAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x9008da0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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ggg==\n",
"text": [
"<matplotlib.figure.Figure at 0xc0a8eb8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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C+Wv2zMwSyOFuZpZADnczswRyuJuZJZDD3cwsgRzuZmYJ5HA3M0sgh7uZWQL9\nf03UfCaavWxkAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0xc8b1358>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc0b5e10>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x93eebe0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x95f27f0>"
]
},
{
"metadata": {},
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"text": [
"<matplotlib.figure.Figure at 0xc8b1978>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc0b35c0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc0b3668>"
]
},
{
"metadata": {},
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677b+9a8XyXzOmZntevkCvg4YmDU/kMyeeK42A5I2vQroC8DWrX8spNZu6bHH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\nQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0xc0b4e10>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc0b4cf8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x9859d30>"
]
},
{
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x93f3550>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x9352e10>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x9879358>"
]
},
{
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"png": 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"text": [
"<matplotlib.figure.Figure at 0xcb42f60>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0xcb42c18>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x98574a8>"
]
},
{
"metadata": {},
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"text": [
"<matplotlib.figure.Figure at 0x9877668>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x900abe0>"
]
},
{
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"text": [
"<matplotlib.figure.Figure at 0x8fef4e0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc5965c0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x985b400>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xcc64048>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8eee4a8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc09db38>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x94006a0>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0x8eee7b8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8eee400>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc0c03c8>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x93efc18>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x8fd6a90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc56df60>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0xc58ab38>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc592b38>"
]
},
{
"metadata": {},
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"png": 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"text": [
"<matplotlib.figure.Figure at 0xc59b588>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc8bfa90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc593f28>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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hdMyzAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x987c358>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0xc8a5358>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAEKCAYAAADpfBXhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAGglJREFUeJzt3XuUVOWd7vHvQ+MlKkbQRKVBmYwdRyMKemy8RQpxkg7x\nFicJYcbExFkjR4KXGG+ZE4dm1jgTjZ4R9ejgDGPQWYJjcBhY3uKg7V1ERLyACLJIuIh3BcW4aPmd\nP2rTFkV3V3V3td31+nzWqkXtvd/a+7d5u5/a9dbeuxURmJlZWvr0dAFmZlZ5DnczswQ53M3MEuRw\nNzNLkMPdzCxBDnczswQ53M3MEuRwtx4jaZWkTZI2SHpX0uOSxkt
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