{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df = pd.read_csv('BPD_Part_1_Victim_Based_Crime_Data.csv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Look at the extreme ends of the data \n", "## Odd things tend to lurk there" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CrimeDateCrimeTimeCrimeCodeLocationDescriptionInside/OutsideWeaponPostDistrictNeighborhoodLocation 1Total Incidents
009/03/201623:52:004C3700 DOLFIELD AVEAGG. ASSAULTOOTHER643.0NORTHWESTERNDolfield(39.3376100000, -76.6773300000)1
109/03/201623041F6100 SHIPVIEW WYHOMICIDEOutsideFIREARM243.0SOUTHEASTERNO'Donnell Heights(39.2765900000, -76.5425400000)1
209/03/201600:00:004D500 MOUNT HOLLY STAGG. ASSAULTIHANDS843.0SOUTHWESTERNAllendale(39.2928100000, -76.6796100000)1
309/03/201600:30:004D200 W BALTIMORE STAGG. ASSAULTOHANDS111.0CENTRALDowntown(39.2893700000, -76.6182500000)1
409/03/201601:00:007A4000 BAREVA RDAUTO THEFTONaN643.0NORTHWESTERNEast Arlington(39.3342000000, -76.6711900000)1
509/03/201601:01:005A4400 MORAVIA RDBURGLARYINaN443.0NORTHEASTERNFrankford(39.3284300000, -76.5579800000)1
609/03/201601:15:007A4200 ERDMAN AVEAUTO THEFTONaN333.0NORTHEASTERNOrangeville Industrial Area(39.3123900000, -76.5668000000)1
709/03/201601:20:004B800 S BROADWAYAGG. ASSAULTOKNIFE213.0SOUTHEASTERNFells Point(39.2824800000, -76.5935200000)1
809/03/201601:40:004E600 N EUTAW STCOMMON ASSAULTIHANDS143.0CENTRALSeton Hill(39.2959700000, -76.6213700000)1
909/03/201601:40:004B600 N EUTAW STAGG. ASSAULTIKNIFE143.0CENTRALSeton Hill(39.2959700000, -76.6213700000)1
1009/03/201602:00:006E2600 GREENMOUNT AVELARCENYONaN513.0NORTHERNHarwood(39.3204400000, -76.6095100000)1
1109/03/201602:07:004E4400 MANORVIEW RDCOMMON ASSAULTIHANDS822.0SOUTHWESTERNUplands(39.2873400000, -76.6907600000)1
1209/03/201602:30:004E1800 WASHINGTON BLVDCOMMON ASSAULTIHANDS941.0SOUTHERNCarroll - Camden Industrial Area(39.2751300000, -76.6423500000)1
1309/03/201602:30:004E1800 WASHINGTON BLVDCOMMON ASSAULTIHANDS941.0SOUTHERNCarroll - Camden Industrial Area(39.2751300000, -76.6423500000)1
1409/03/201602:54:004E600 MCKEWIN AVECOMMON ASSAULTIHANDS543.0NORTHERNWaverly(39.3329500000, -76.6068500000)1
1509/03/201603:00:004D4300 N ROGERS AVEAGG. ASSAULTIHANDS621.0NORTHWESTERNWest Arlington(39.3419200000, -76.6957200000)1
1609/03/201604:25:003CO100 S BROADWAYROBBERY - COMMERCIALIOTHER212.0SOUTHEASTERNWashington Hill(39.2902100000, -76.5937400000)1
1709/03/201605:00:004E2400 SAINT PAUL STCOMMON ASSAULTOHANDS514.0NORTHERNOld Goucher(39.3165100000, -76.6153300000)1
1809/03/201607:04:006C200 W CHASE STLARCENYINaN141.0CENTRALMid-Town Belvedere(39.3014000000, -76.6197000000)1
1909/03/201607:05:006BNORTH AV & N PORT STLARCENYONaN332.0EASTERNBroadway East(39.3126100000, -76.5838500000)1
2009/03/201607:40:003AK1900 WILHELM STROBBERY - STREETOKNIFE934.0SOUTHERNCarrollton Ridge(39.2836400000, -76.6472200000)1
2109/03/201608:30:006J1700 THAMES STLARCENYINaN213.0SOUTHEASTERNFells Point(39.2818100000, -76.5924400000)1
2209/03/201609:00:005D1400 CHURCH STBURGLARYONaN911.0SOUTHERNCurtis Bay(39.2228200000, -76.5904900000)1
2309/03/201609:30:006E1100 N FREMONT AVELARCENYONaN123.0WESTERNUpton(39.3024300000, -76.6362600000)1
2409/03/201609:30:006J1600 W NORTH AVELARCENYONaN733.0WESTERNPenn North(39.3100200000, -76.6428400000)1
2509/03/201609:30:004A3700 MANCHESTER AVEAGG. ASSAULTIFIREARM614.0NORTHWESTERNCentral Park Heights(39.3425400000, -76.6763600000)1
2609/03/201610:15:005A900 MC ALEER CTBURGLARYINaN312.0EASTERNOldtown(39.2997400000, -76.6044500000)1
2709/03/201610:30:004E1200 W NORTH AVECOMMON ASSAULTOHANDS131.0WESTERNDruid Heights(39.3102600000, -76.6370600000)1
2809/03/201610:35:006G2500 MCHENRY STLARCENYINaN842.0SOUTHWESTERNShipley Hill(39.2839200000, -76.6561400000)1
2909/03/201610:40:004C500 N LUZERNE AVEAGG. ASSAULTOOTHER221.0SOUTHEASTERNMcElderry Park(39.2969400000, -76.5807900000)1
3009/03/201611:30:007A400 MERRYMAN LNAUTO THEFTONaN513.0NORTHERNAbell(39.3282100000, -76.6109100000)1
3109/03/201611:52:006D300 Loneys LnLARCENY FROM AUTOONaN224.0SOUTHEASTERNEllwood Park/Monument(39.2959700000, -76.5726000000)1
3209/03/201612:00:007A300 DENISON STAUTO THEFTONaN843.0SOUTHWESTERNAllendale(39.2908700000, -76.6745500000)1
3309/03/201612:18:006C1600 PENNSYLVANIA AVELARCENYINaN123.0CENTRALUpton(39.3034400000, -76.6345800000)1
3409/03/201612:40:004E1100 WHATCOAT STCOMMON ASSAULTOHANDS743.0WESTERNSandtown-Winchester(39.3017100000, -76.6410600000)1
3509/03/201612:40:004E1100 WHATCOAT STCOMMON ASSAULTOHANDS743.0WESTERNSandtown-Winchester(39.3017100000, -76.6410600000)1
3609/03/201613:00:004A1900 EASTERN AVEAGG. ASSAULTOFIREARM212.0SOUTHEASTERNUpper Fells Point(39.2857500000, -76.5900000000)1
3709/03/201613:09:004F2500 E MADISON STASSAULT BY THREATINaN323.0EASTERNMilton-Montford(39.2998900000, -76.5818200000)1
3809/03/201613:30:005A1900 E LAFAYETTE AVEBURGLARYINaN331.0EASTERNBroadway East(39.3107700000, -76.5914900000)1
3909/03/201614:20:006C2400 BELAIR RDLARCENYINaN434.0NORTHEASTERNBelair-Edison(39.3176600000, -76.5781900000)1
4009/03/201614:30:004E1200 MYRTLE AVECOMMON ASSAULTIHANDS123.0CENTRALUpton(39.2983300000, -76.6317200000)1
4109/03/201614:45:003D3600 E NORTHERN PKWYROBBERY - COMMERCIALINaN424.0NORTHEASTERNNorth Harford Road(39.3583400000, -76.5380200000)1
4209/03/201615:13:006D400 W MONUMENT STLARCENY FROM AUTOONaN143.0CENTRALSeton Hill(39.2974200000, -76.6218600000)1
4309/03/201615:20:007A3600 ELMLEY AVEAUTO THEFTONaN432.0NORTHEASTERNBelair-Edison(39.3174200000, -76.5678900000)1
4409/03/201615:30:003B5300 REISTERSTOWN RDROBBERY - STREETONaN623.0NORTHWESTERNWoodmere(39.3457100000, -76.6874800000)1
4509/03/201616:00:007A200 N GILMOR STAUTO THEFTONaN711.0WESTERNFranklin Square(39.2907600000, -76.6425500000)1
4609/03/201616:16:004A700 BENNINGHAUS RDAGG. ASSAULTIFIREARM523.0NORTHERNMid-Govans(39.3598100000, -76.6067100000)1
4709/03/201616:50:004E0 N CENTRAL AVECOMMON ASSAULTOHANDS211.0SOUTHEASTERNJonestown(39.2915400000, -76.5997300000)1
4809/03/201617:00:004B0 S GREENE STAGG. ASSAULTOKNIFE121.0CENTRALUniversity Of Maryland(39.2882900000, -76.6236700000)1
4909/03/201617:53:004E3000 OAKFORD AVECOMMON ASSAULTOHANDS532.0NORTHERNParklane(39.3413300000, -76.6645300000)1
\n", "
" ], "text/plain": [ " CrimeDate CrimeTime CrimeCode Location \\\n", "0 09/03/2016 23:52:00 4C 3700 DOLFIELD AVE \n", "1 09/03/2016 2304 1F 6100 SHIPVIEW WY \n", "2 09/03/2016 00:00:00 4D 500 MOUNT HOLLY ST \n", "3 09/03/2016 00:30:00 4D 200 W BALTIMORE ST \n", "4 09/03/2016 01:00:00 7A 4000 BAREVA RD \n", "5 09/03/2016 01:01:00 5A 4400 MORAVIA RD \n", "6 09/03/2016 01:15:00 7A 4200 ERDMAN AVE \n", "7 09/03/2016 01:20:00 4B 800 S BROADWAY \n", "8 09/03/2016 01:40:00 4E 600 N EUTAW ST \n", "9 09/03/2016 01:40:00 4B 600 N EUTAW ST \n", "10 09/03/2016 02:00:00 6E 2600 GREENMOUNT AVE \n", "11 09/03/2016 02:07:00 4E 4400 MANORVIEW RD \n", "12 09/03/2016 02:30:00 4E 1800 WASHINGTON BLVD \n", "13 09/03/2016 02:30:00 4E 1800 WASHINGTON BLVD \n", "14 09/03/2016 02:54:00 4E 600 MCKEWIN AVE \n", "15 09/03/2016 03:00:00 4D 4300 N ROGERS AVE \n", "16 09/03/2016 04:25:00 3CO 100 S BROADWAY \n", "17 09/03/2016 05:00:00 4E 2400 SAINT PAUL ST \n", "18 09/03/2016 07:04:00 6C 200 W CHASE ST \n", "19 09/03/2016 07:05:00 6B NORTH AV & N PORT ST \n", "20 09/03/2016 07:40:00 3AK 1900 WILHELM ST \n", "21 09/03/2016 08:30:00 6J 1700 THAMES ST \n", "22 09/03/2016 09:00:00 5D 1400 CHURCH ST \n", "23 09/03/2016 09:30:00 6E 1100 N FREMONT AVE \n", "24 09/03/2016 09:30:00 6J 1600 W NORTH AVE \n", "25 09/03/2016 09:30:00 4A 3700 MANCHESTER AVE \n", "26 09/03/2016 10:15:00 5A 900 MC ALEER CT \n", "27 09/03/2016 10:30:00 4E 1200 W NORTH AVE \n", "28 09/03/2016 10:35:00 6G 2500 MCHENRY ST \n", "29 09/03/2016 10:40:00 4C 500 N LUZERNE AVE \n", "30 09/03/2016 11:30:00 7A 400 MERRYMAN LN \n", "31 09/03/2016 11:52:00 6D 300 Loneys Ln \n", "32 09/03/2016 12:00:00 7A 300 DENISON ST \n", "33 09/03/2016 12:18:00 6C 1600 PENNSYLVANIA AVE \n", "34 09/03/2016 12:40:00 4E 1100 WHATCOAT ST \n", "35 09/03/2016 12:40:00 4E 1100 WHATCOAT ST \n", "36 09/03/2016 13:00:00 4A 1900 EASTERN AVE \n", "37 09/03/2016 13:09:00 4F 2500 E MADISON ST \n", "38 09/03/2016 13:30:00 5A 1900 E LAFAYETTE AVE \n", "39 09/03/2016 14:20:00 6C 2400 BELAIR RD \n", "40 09/03/2016 14:30:00 4E 1200 MYRTLE AVE \n", "41 09/03/2016 14:45:00 3D 3600 E NORTHERN PKWY \n", "42 09/03/2016 15:13:00 6D 400 W MONUMENT ST \n", "43 09/03/2016 15:20:00 7A 3600 ELMLEY AVE \n", "44 09/03/2016 15:30:00 3B 5300 REISTERSTOWN RD \n", "45 09/03/2016 16:00:00 7A 200 N GILMOR ST \n", "46 09/03/2016 16:16:00 4A 700 BENNINGHAUS RD \n", "47 09/03/2016 16:50:00 4E 0 N CENTRAL AVE \n", "48 09/03/2016 17:00:00 4B 0 S GREENE ST \n", "49 09/03/2016 17:53:00 4E 3000 OAKFORD AVE \n", "\n", " Description Inside/Outside Weapon Post District \\\n", "0 AGG. ASSAULT O OTHER 643.0 NORTHWESTERN \n", "1 HOMICIDE Outside FIREARM 243.0 SOUTHEASTERN \n", "2 AGG. ASSAULT I HANDS 843.0 SOUTHWESTERN \n", "3 AGG. ASSAULT O HANDS 111.0 CENTRAL \n", "4 AUTO THEFT O NaN 643.0 NORTHWESTERN \n", "5 BURGLARY I NaN 443.0 NORTHEASTERN \n", "6 AUTO THEFT O NaN 333.0 NORTHEASTERN \n", "7 AGG. ASSAULT O KNIFE 213.0 SOUTHEASTERN \n", "8 COMMON ASSAULT I HANDS 143.0 CENTRAL \n", "9 AGG. ASSAULT I KNIFE 143.0 CENTRAL \n", "10 LARCENY O NaN 513.0 NORTHERN \n", "11 COMMON ASSAULT I HANDS 822.0 SOUTHWESTERN \n", "12 COMMON ASSAULT I HANDS 941.0 SOUTHERN \n", "13 COMMON ASSAULT I HANDS 941.0 SOUTHERN \n", "14 COMMON ASSAULT I HANDS 543.0 NORTHERN \n", "15 AGG. ASSAULT I HANDS 621.0 NORTHWESTERN \n", "16 ROBBERY - COMMERCIAL I OTHER 212.0 SOUTHEASTERN \n", "17 COMMON ASSAULT O HANDS 514.0 NORTHERN \n", "18 LARCENY I NaN 141.0 CENTRAL \n", "19 LARCENY O NaN 332.0 EASTERN \n", "20 ROBBERY - STREET O KNIFE 934.0 SOUTHERN \n", "21 LARCENY I NaN 213.0 SOUTHEASTERN \n", "22 BURGLARY O NaN 911.0 SOUTHERN \n", "23 LARCENY O NaN 123.0 WESTERN \n", "24 LARCENY O NaN 733.0 WESTERN \n", "25 AGG. ASSAULT I FIREARM 614.0 NORTHWESTERN \n", "26 BURGLARY I NaN 312.0 EASTERN \n", "27 COMMON ASSAULT O HANDS 131.0 WESTERN \n", "28 LARCENY I NaN 842.0 SOUTHWESTERN \n", "29 AGG. ASSAULT O OTHER 221.0 SOUTHEASTERN \n", "30 AUTO THEFT O NaN 513.0 NORTHERN \n", "31 LARCENY FROM AUTO O NaN 224.0 SOUTHEASTERN \n", "32 AUTO THEFT O NaN 843.0 SOUTHWESTERN \n", "33 LARCENY I NaN 123.0 CENTRAL \n", "34 COMMON ASSAULT O HANDS 743.0 WESTERN \n", "35 COMMON ASSAULT O HANDS 743.0 WESTERN \n", "36 AGG. ASSAULT O FIREARM 212.0 SOUTHEASTERN \n", "37 ASSAULT BY THREAT I NaN 323.0 EASTERN \n", "38 BURGLARY I NaN 331.0 EASTERN \n", "39 LARCENY I NaN 434.0 NORTHEASTERN \n", "40 COMMON ASSAULT I HANDS 123.0 CENTRAL \n", "41 ROBBERY - COMMERCIAL I NaN 424.0 NORTHEASTERN \n", "42 LARCENY FROM AUTO O NaN 143.0 CENTRAL \n", "43 AUTO THEFT O NaN 432.0 NORTHEASTERN \n", "44 ROBBERY - STREET O NaN 623.0 NORTHWESTERN \n", "45 AUTO THEFT O NaN 711.0 WESTERN \n", "46 AGG. ASSAULT I FIREARM 523.0 NORTHERN \n", "47 COMMON ASSAULT O HANDS 211.0 SOUTHEASTERN \n", "48 AGG. ASSAULT O KNIFE 121.0 CENTRAL \n", "49 COMMON ASSAULT O HANDS 532.0 NORTHERN \n", "\n", " Neighborhood Location 1 \\\n", "0 Dolfield (39.3376100000, -76.6773300000) \n", "1 O'Donnell Heights (39.2765900000, -76.5425400000) \n", "2 Allendale (39.2928100000, -76.6796100000) \n", "3 Downtown (39.2893700000, -76.6182500000) \n", "4 East Arlington (39.3342000000, -76.6711900000) \n", "5 Frankford (39.3284300000, -76.5579800000) \n", "6 Orangeville Industrial Area (39.3123900000, -76.5668000000) \n", "7 Fells Point (39.2824800000, -76.5935200000) \n", "8 Seton Hill (39.2959700000, -76.6213700000) \n", "9 Seton Hill (39.2959700000, -76.6213700000) \n", "10 Harwood (39.3204400000, -76.6095100000) \n", "11 Uplands (39.2873400000, -76.6907600000) \n", "12 Carroll - Camden Industrial Area (39.2751300000, -76.6423500000) \n", "13 Carroll - Camden Industrial Area (39.2751300000, -76.6423500000) \n", "14 Waverly (39.3329500000, -76.6068500000) \n", "15 West Arlington (39.3419200000, -76.6957200000) \n", "16 Washington Hill (39.2902100000, -76.5937400000) \n", "17 Old Goucher (39.3165100000, -76.6153300000) \n", "18 Mid-Town Belvedere (39.3014000000, -76.6197000000) \n", "19 Broadway East (39.3126100000, -76.5838500000) \n", "20 Carrollton Ridge (39.2836400000, -76.6472200000) \n", "21 Fells Point (39.2818100000, -76.5924400000) \n", "22 Curtis Bay (39.2228200000, -76.5904900000) \n", "23 Upton (39.3024300000, -76.6362600000) \n", "24 Penn North (39.3100200000, -76.6428400000) \n", "25 Central Park Heights (39.3425400000, -76.6763600000) \n", "26 Oldtown (39.2997400000, -76.6044500000) \n", "27 Druid Heights (39.3102600000, -76.6370600000) \n", "28 Shipley Hill (39.2839200000, -76.6561400000) \n", "29 McElderry Park (39.2969400000, -76.5807900000) \n", "30 Abell (39.3282100000, -76.6109100000) \n", "31 Ellwood Park/Monument (39.2959700000, -76.5726000000) \n", "32 Allendale (39.2908700000, -76.6745500000) \n", "33 Upton (39.3034400000, -76.6345800000) \n", "34 Sandtown-Winchester (39.3017100000, -76.6410600000) \n", "35 Sandtown-Winchester (39.3017100000, -76.6410600000) \n", "36 Upper Fells Point (39.2857500000, -76.5900000000) \n", "37 Milton-Montford (39.2998900000, -76.5818200000) \n", "38 Broadway East (39.3107700000, -76.5914900000) \n", "39 Belair-Edison (39.3176600000, -76.5781900000) \n", "40 Upton (39.2983300000, -76.6317200000) \n", "41 North Harford Road (39.3583400000, -76.5380200000) \n", "42 Seton Hill (39.2974200000, -76.6218600000) \n", "43 Belair-Edison (39.3174200000, -76.5678900000) \n", "44 Woodmere (39.3457100000, -76.6874800000) \n", "45 Franklin Square (39.2907600000, -76.6425500000) \n", "46 Mid-Govans (39.3598100000, -76.6067100000) \n", "47 Jonestown (39.2915400000, -76.5997300000) \n", "48 University Of Maryland (39.2882900000, -76.6236700000) \n", "49 Parklane (39.3413300000, -76.6645300000) \n", "\n", " Total Incidents \n", "0 1 \n", "1 1 \n", "2 1 \n", "3 1 \n", "4 1 \n", "5 1 \n", "6 1 \n", "7 1 \n", "8 1 \n", "9 1 \n", "10 1 \n", "11 1 \n", "12 1 \n", "13 1 \n", "14 1 \n", "15 1 \n", "16 1 \n", "17 1 \n", "18 1 \n", "19 1 \n", "20 1 \n", "21 1 \n", "22 1 \n", "23 1 \n", "24 1 \n", "25 1 \n", "26 1 \n", "27 1 \n", "28 1 \n", "29 1 \n", "30 1 \n", "31 1 \n", "32 1 \n", "33 1 \n", "34 1 \n", "35 1 \n", "36 1 \n", "37 1 \n", "38 1 \n", "39 1 \n", "40 1 \n", "41 1 \n", "42 1 \n", "43 1 \n", "44 1 \n", "45 1 \n", "46 1 \n", "47 1 \n", "48 1 \n", "49 1 " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head(50)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CrimeDateCrimeTimeCrimeCodeLocationDescriptionInside/OutsideWeaponPostDistrictNeighborhoodLocation 1Total Incidents
27499901/01/201121:00:006J800 ST PAUL STLARCENYINaN142.0CENTRALMount Vernon(39.2993300000, -76.6141300000)1
27500001/01/201121:00:007A2700 MARBOURNE AVAUTO THEFTONaN923.0SOUTHERNLakeland(39.2521100000, -76.6426000000)1
27500101/01/201121:20:004E1700 NORMAL AVCOMMON ASSAULTIHANDS342.0EASTERNDarley Park(39.3155100000, -76.5936400000)1
27500201/01/201121:20:003CF3900 CLAREMONT AVROBBERY - COMMERCIALIFIREARM231.0SOUTHEASTERNHighlandtown(39.2896000000, -76.5643200000)1
27500301/01/201121:30:006J0 E CROSS STLARCENYINaN942.0SOUTHERNFederal Hill(39.2768600000, -76.6142900000)1
27500401/01/201121:40:006E500 W FRANKLIN STLARCENYONaN143.0CENTRALSeton Hill(39.2948300000, -76.6233300000)1
27500501/01/201121:43:004E1700 E LAFAYETTE AVCOMMON ASSAULTOHANDS331.0EASTERNBroadway East(39.3107100000, -76.5944200000)1
27500601/01/201122:00:006D200 EMORY STLARCENY FROM AUTOONaN941.0SOUTHERNRidgely's Delight(39.2861000000, -76.6247400000)1
27500701/01/201122:00:006D1200 N CALHOUN STLARCENY FROM AUTOONaN743.0WESTERNSandtown-Winchester(39.3025800000, -76.6403600000)1
27500801/01/201122:00:005A2300 BOSTON STBURGLARYINaN232.0SOUTHEASTERNCanton(39.2828600000, -76.5842000000)1
27500901/01/201122:00:004E2700 ASHLAND AVCOMMON ASSAULTOHANDS323.0EASTERNMadison-Eastend(39.3010900000, -76.5788000000)1
27501001/01/201122:15:004E6800 MCCLEAN BDCOMMON ASSAULTIHANDS423.0NORTHEASTERNHamilton Hills(39.3704700000, -76.5670500000)1
27501101/01/201122:15:004D6800 MCCLEAN BDAGG. ASSAULTIHANDS423.0NORTHEASTERNHamilton Hills(39.3704700000, -76.5670500000)1
27501201/01/201122:30:006J3000 ODONNELL STLARCENYINaN232.0SOUTHEASTERNCanton(39.2804600000, -76.5727300000)1
27501301/01/201123:00:007A2500 ARUNAH AVAUTO THEFTONaN721.0WESTERNEvergreen Lawn(39.2954200000, -76.6592800000)1
27501401/01/201123:25:004E100 N MONROE STCOMMON ASSAULTIHANDS714.0WESTERNPenrose/Fayette Street Outreach(39.2899900000, -76.6470700000)1
27501501/01/201123:38:004D800 N FREMONT AVAGG. ASSAULTIHANDS123.0WESTERNUpton(39.2981200000, -76.6339100000)1
27501601/01/201108:00:007A4100 MCKENDRE PLAUTO THEFTONaN623.0NORTHWESTERNWoodmere(39.3444400000, -76.6858000000)1
27501701/01/201108:15:006E2300 ORLEANS STLARCENYONaN221.0SOUTHEASTERNMcElderry Park(39.2955600000, -76.5844600000)1
27501801/01/201108:30:005A3000 FLEETWOOD AVBURGLARYINaN424.0NORTHEASTERNWestfield(39.3620300000, -76.5513000000)1
27501901/01/201109:00:006G300 W CAMDEN STLARCENYINaN941.0CENTRALStadium Area(39.2852200000, -76.6200600000)1
27502001/01/201109:00:006E900 N CARROLLTON AVLARCENYONaN743.0WESTERNSandtown-Winchester(39.2996500000, -76.6373700000)1
27502101/01/201109:00:004E4800 COLEHERNE RDCOMMON ASSAULTIHANDS822.0SOUTHWESTERNHunting Ridge(39.2935800000, -76.7019000000)1
27502201/01/201110:00:006J2600 KIRK AVELARCENYINaN411.0NORTHEASTERNColdstream Homestead Montebello(39.3208400000, -76.5993600000)1
27502301/01/201110:00:005A1700 BRADDISH AVBURGLARYINaN723.0WESTERNCoppin Heights/Ash-Co-East(39.3076800000, -76.6610100000)1
27502401/01/201110:00:005A1600 N CALVERT STBURGLARYINaN141.0CENTRALGreenmount West(39.3080600000, -76.6136200000)1
27502501/01/201110:15:005A300 S STRICKER STBURGLARYINaN935.0SOUTHERNNew Southwest/Mount Clare(39.2840800000, -76.6406800000)1
27502601/01/201110:20:005A800 MC ALEER CTBURGLARYINaN312.0EASTERNOldtown(39.3000500000, -76.6051000000)1
27502701/01/201110:30:004E1600 N HILTON STCOMMON ASSAULTIHANDS813.0SOUTHWESTERNRosemont(39.3062000000, -76.6721800000)1
27502801/01/201110:45:006C300 W LEXINGTON STLARCENYINaN111.0CENTRALDowntown(39.2915000000, -76.6197900000)1
27502901/01/201110:50:007A600 BRIDGEVIEW RDAUTO THEFTINaN922.0SOUTHERNCherry Hill(39.2495100000, -76.6219100000)1
27503001/01/201111:00:006J200 E PRESTON STLARCENYINaN141.0CENTRALMid-Town Belvedere(39.3046100000, -76.6125300000)1
27503101/01/201111:00:006J400 W LEXINGTON STLARCENYINaN111.0CENTRALDowntown(39.2913100000, -76.6101000000)1
27503201/01/201111:25:006D5800 ODONNELL STLARCENY FROM AUTOONaN233.0SOUTHEASTERNMedford(39.2813200000, -76.5455400000)1
27503301/01/201112:00:006D1100 COVINGTON STLARCENY FROM AUTOONaN943.0SOUTHERNRiverside(39.2771000000, -76.6070100000)1
27503401/01/201112:00:005B1700 HARLEM AVBURGLARYINaN713.0WESTERNHarlem Park(39.2964600000, -76.6443900000)1
27503501/01/201112:00:006E5200 FAIRLAWN AVLARCENYONaN623.0NORTHWESTERNWoodmere(39.3429000000, -76.6856700000)1
27503601/01/201112:00:006D1000 BRENTWOOD AVLARCENY FROM AUTOONaN311.0EASTERNJohnston Square(39.3013300000, -76.6091100000)1
27503701/01/201112:05:005A600 APPLETON STBURGLARYINaN722.0WESTERNMidtown-Edmondson(39.2955700000, -76.6481800000)1
27503801/01/201112:25:006D900 STILES STLARCENY FROM AUTOONaN211.0SOUTHEASTERNLittle Italy(39.2869800000, -76.6021300000)1
27503901/01/201112:37:004B2500 FEDERAL STAGG. ASSAULTIKNIFE332.0EASTERNBerea(39.3090300000, -76.5818200000)1
27504001/01/201112:40:006D1400 BROENING HWLARCENY FROM AUTOONaN233.0SOUTHEASTERNMedford(39.2776800000, -76.5437500000)1
27504101/01/201113:30:006E2900 GRINDON AVLARCENYONaN421.0NORTHEASTERNLauraville(39.3425600000, -76.5718500000)1
27504201/01/201113:30:006D300 YALE AVELARCENY FROM AUTONaNNaN833.0SOUTHWESTERNIrvington(39.2815900000, -76.6856300000)1
27504301/01/201113:42:006E2000 W FRANKLIN STLARCENYONaN722.0WESTERNMidtown-Edmondson(39.2937900000, -76.6496600000)1
27504401/01/201113:51:003CK1000 N GILMOR STROBBERY - COMMERCIALIKNIFE743.0WESTERNSandtown-Winchester(39.3004100000, -76.6430000000)1
27504501/01/201114:00:006D300 S SMALLWOOD STLARCENY FROM AUTOONaN841.0SOUTHWESTERNCarrollton Ridge(39.2836100000, -76.6511900000)1
27504601/01/201114:30:004E1800 W SARATOGA STCOMMON ASSAULTIHANDS711.0WESTERNFranklin Square(39.2920000000, -76.6464600000)1
27504701/01/201115:30:006D600 LIGHT STLARCENY FROM AUTOONaN112.0SOUTHERNInner Harbor(39.2817400000, -76.6127900000)1
27504801/01/201115:34:004E2200 ANNAPOLIS RDCOMMON ASSAULTOHANDS921.0SOUTHERNWestport(39.2638700000, -76.6335100000)1
\n", "
" ], "text/plain": [ " CrimeDate CrimeTime CrimeCode Location \\\n", "274999 01/01/2011 21:00:00 6J 800 ST PAUL ST \n", "275000 01/01/2011 21:00:00 7A 2700 MARBOURNE AV \n", "275001 01/01/2011 21:20:00 4E 1700 NORMAL AV \n", "275002 01/01/2011 21:20:00 3CF 3900 CLAREMONT AV \n", "275003 01/01/2011 21:30:00 6J 0 E CROSS ST \n", "275004 01/01/2011 21:40:00 6E 500 W FRANKLIN ST \n", "275005 01/01/2011 21:43:00 4E 1700 E LAFAYETTE AV \n", "275006 01/01/2011 22:00:00 6D 200 EMORY ST \n", "275007 01/01/2011 22:00:00 6D 1200 N CALHOUN ST \n", "275008 01/01/2011 22:00:00 5A 2300 BOSTON ST \n", "275009 01/01/2011 22:00:00 4E 2700 ASHLAND AV \n", "275010 01/01/2011 22:15:00 4E 6800 MCCLEAN BD \n", "275011 01/01/2011 22:15:00 4D 6800 MCCLEAN BD \n", "275012 01/01/2011 22:30:00 6J 3000 ODONNELL ST \n", "275013 01/01/2011 23:00:00 7A 2500 ARUNAH AV \n", "275014 01/01/2011 23:25:00 4E 100 N MONROE ST \n", "275015 01/01/2011 23:38:00 4D 800 N FREMONT AV \n", "275016 01/01/2011 08:00:00 7A 4100 MCKENDRE PL \n", "275017 01/01/2011 08:15:00 6E 2300 ORLEANS ST \n", "275018 01/01/2011 08:30:00 5A 3000 FLEETWOOD AV \n", "275019 01/01/2011 09:00:00 6G 300 W CAMDEN ST \n", "275020 01/01/2011 09:00:00 6E 900 N CARROLLTON AV \n", "275021 01/01/2011 09:00:00 4E 4800 COLEHERNE RD \n", "275022 01/01/2011 10:00:00 6J 2600 KIRK AVE \n", "275023 01/01/2011 10:00:00 5A 1700 BRADDISH AV \n", "275024 01/01/2011 10:00:00 5A 1600 N CALVERT ST \n", "275025 01/01/2011 10:15:00 5A 300 S STRICKER ST \n", "275026 01/01/2011 10:20:00 5A 800 MC ALEER CT \n", "275027 01/01/2011 10:30:00 4E 1600 N HILTON ST \n", "275028 01/01/2011 10:45:00 6C 300 W LEXINGTON ST \n", "275029 01/01/2011 10:50:00 7A 600 BRIDGEVIEW RD \n", "275030 01/01/2011 11:00:00 6J 200 E PRESTON ST \n", "275031 01/01/2011 11:00:00 6J 400 W LEXINGTON ST \n", "275032 01/01/2011 11:25:00 6D 5800 ODONNELL ST \n", "275033 01/01/2011 12:00:00 6D 1100 COVINGTON ST \n", "275034 01/01/2011 12:00:00 5B 1700 HARLEM AV \n", "275035 01/01/2011 12:00:00 6E 5200 FAIRLAWN AV \n", "275036 01/01/2011 12:00:00 6D 1000 BRENTWOOD AV \n", "275037 01/01/2011 12:05:00 5A 600 APPLETON ST \n", "275038 01/01/2011 12:25:00 6D 900 STILES ST \n", "275039 01/01/2011 12:37:00 4B 2500 FEDERAL ST \n", "275040 01/01/2011 12:40:00 6D 1400 BROENING HW \n", "275041 01/01/2011 13:30:00 6E 2900 GRINDON AV \n", "275042 01/01/2011 13:30:00 6D 300 YALE AVE \n", "275043 01/01/2011 13:42:00 6E 2000 W FRANKLIN ST \n", "275044 01/01/2011 13:51:00 3CK 1000 N GILMOR ST \n", "275045 01/01/2011 14:00:00 6D 300 S SMALLWOOD ST \n", "275046 01/01/2011 14:30:00 4E 1800 W SARATOGA ST \n", "275047 01/01/2011 15:30:00 6D 600 LIGHT ST \n", "275048 01/01/2011 15:34:00 4E 2200 ANNAPOLIS RD \n", "\n", " Description Inside/Outside Weapon Post District \\\n", "274999 LARCENY I NaN 142.0 CENTRAL \n", "275000 AUTO THEFT O NaN 923.0 SOUTHERN \n", "275001 COMMON ASSAULT I HANDS 342.0 EASTERN \n", "275002 ROBBERY - COMMERCIAL I FIREARM 231.0 SOUTHEASTERN \n", "275003 LARCENY I NaN 942.0 SOUTHERN \n", "275004 LARCENY O NaN 143.0 CENTRAL \n", "275005 COMMON ASSAULT O HANDS 331.0 EASTERN \n", "275006 LARCENY FROM AUTO O NaN 941.0 SOUTHERN \n", "275007 LARCENY FROM AUTO O NaN 743.0 WESTERN \n", "275008 BURGLARY I NaN 232.0 SOUTHEASTERN \n", "275009 COMMON ASSAULT O HANDS 323.0 EASTERN \n", "275010 COMMON ASSAULT I HANDS 423.0 NORTHEASTERN \n", "275011 AGG. ASSAULT I HANDS 423.0 NORTHEASTERN \n", "275012 LARCENY I NaN 232.0 SOUTHEASTERN \n", "275013 AUTO THEFT O NaN 721.0 WESTERN \n", "275014 COMMON ASSAULT I HANDS 714.0 WESTERN \n", "275015 AGG. ASSAULT I HANDS 123.0 WESTERN \n", "275016 AUTO THEFT O NaN 623.0 NORTHWESTERN \n", "275017 LARCENY O NaN 221.0 SOUTHEASTERN \n", "275018 BURGLARY I NaN 424.0 NORTHEASTERN \n", "275019 LARCENY I NaN 941.0 CENTRAL \n", "275020 LARCENY O NaN 743.0 WESTERN \n", "275021 COMMON ASSAULT I HANDS 822.0 SOUTHWESTERN \n", "275022 LARCENY I NaN 411.0 NORTHEASTERN \n", "275023 BURGLARY I NaN 723.0 WESTERN \n", "275024 BURGLARY I NaN 141.0 CENTRAL \n", "275025 BURGLARY I NaN 935.0 SOUTHERN \n", "275026 BURGLARY I NaN 312.0 EASTERN \n", "275027 COMMON ASSAULT I HANDS 813.0 SOUTHWESTERN \n", "275028 LARCENY I NaN 111.0 CENTRAL \n", "275029 AUTO THEFT I NaN 922.0 SOUTHERN \n", "275030 LARCENY I NaN 141.0 CENTRAL \n", "275031 LARCENY I NaN 111.0 CENTRAL \n", "275032 LARCENY FROM AUTO O NaN 233.0 SOUTHEASTERN \n", "275033 LARCENY FROM AUTO O NaN 943.0 SOUTHERN \n", "275034 BURGLARY I NaN 713.0 WESTERN \n", "275035 LARCENY O NaN 623.0 NORTHWESTERN \n", "275036 LARCENY FROM AUTO O NaN 311.0 EASTERN \n", "275037 BURGLARY I NaN 722.0 WESTERN \n", "275038 LARCENY FROM AUTO O NaN 211.0 SOUTHEASTERN \n", "275039 AGG. ASSAULT I KNIFE 332.0 EASTERN \n", "275040 LARCENY FROM AUTO O NaN 233.0 SOUTHEASTERN \n", "275041 LARCENY O NaN 421.0 NORTHEASTERN \n", "275042 LARCENY FROM AUTO NaN NaN 833.0 SOUTHWESTERN \n", "275043 LARCENY O NaN 722.0 WESTERN \n", "275044 ROBBERY - COMMERCIAL I KNIFE 743.0 WESTERN \n", "275045 LARCENY FROM AUTO O NaN 841.0 SOUTHWESTERN \n", "275046 COMMON ASSAULT I HANDS 711.0 WESTERN \n", "275047 LARCENY FROM AUTO O NaN 112.0 SOUTHERN \n", "275048 COMMON ASSAULT O HANDS 921.0 SOUTHERN \n", "\n", " Neighborhood Location 1 \\\n", "274999 Mount Vernon (39.2993300000, -76.6141300000) \n", "275000 Lakeland (39.2521100000, -76.6426000000) \n", "275001 Darley Park (39.3155100000, -76.5936400000) \n", "275002 Highlandtown (39.2896000000, -76.5643200000) \n", "275003 Federal Hill (39.2768600000, -76.6142900000) \n", "275004 Seton Hill (39.2948300000, -76.6233300000) \n", "275005 Broadway East (39.3107100000, -76.5944200000) \n", "275006 Ridgely's Delight (39.2861000000, -76.6247400000) \n", "275007 Sandtown-Winchester (39.3025800000, -76.6403600000) \n", "275008 Canton (39.2828600000, -76.5842000000) \n", "275009 Madison-Eastend (39.3010900000, -76.5788000000) \n", "275010 Hamilton Hills (39.3704700000, -76.5670500000) \n", "275011 Hamilton Hills (39.3704700000, -76.5670500000) \n", "275012 Canton (39.2804600000, -76.5727300000) \n", "275013 Evergreen Lawn (39.2954200000, -76.6592800000) \n", "275014 Penrose/Fayette Street Outreach (39.2899900000, -76.6470700000) \n", "275015 Upton (39.2981200000, -76.6339100000) \n", "275016 Woodmere (39.3444400000, -76.6858000000) \n", "275017 McElderry Park (39.2955600000, -76.5844600000) \n", "275018 Westfield (39.3620300000, -76.5513000000) \n", "275019 Stadium Area (39.2852200000, -76.6200600000) \n", "275020 Sandtown-Winchester (39.2996500000, -76.6373700000) \n", "275021 Hunting Ridge (39.2935800000, -76.7019000000) \n", "275022 Coldstream Homestead Montebello (39.3208400000, -76.5993600000) \n", "275023 Coppin Heights/Ash-Co-East (39.3076800000, -76.6610100000) \n", "275024 Greenmount West (39.3080600000, -76.6136200000) \n", "275025 New Southwest/Mount Clare (39.2840800000, -76.6406800000) \n", "275026 Oldtown (39.3000500000, -76.6051000000) \n", "275027 Rosemont (39.3062000000, -76.6721800000) \n", "275028 Downtown (39.2915000000, -76.6197900000) \n", "275029 Cherry Hill (39.2495100000, -76.6219100000) \n", "275030 Mid-Town Belvedere (39.3046100000, -76.6125300000) \n", "275031 Downtown (39.2913100000, -76.6101000000) \n", "275032 Medford (39.2813200000, -76.5455400000) \n", "275033 Riverside (39.2771000000, -76.6070100000) \n", "275034 Harlem Park (39.2964600000, -76.6443900000) \n", "275035 Woodmere (39.3429000000, -76.6856700000) \n", "275036 Johnston Square (39.3013300000, -76.6091100000) \n", "275037 Midtown-Edmondson (39.2955700000, -76.6481800000) \n", "275038 Little Italy (39.2869800000, -76.6021300000) \n", "275039 Berea (39.3090300000, -76.5818200000) \n", "275040 Medford (39.2776800000, -76.5437500000) \n", "275041 Lauraville (39.3425600000, -76.5718500000) \n", "275042 Irvington (39.2815900000, -76.6856300000) \n", "275043 Midtown-Edmondson (39.2937900000, -76.6496600000) \n", "275044 Sandtown-Winchester (39.3004100000, -76.6430000000) \n", "275045 Carrollton Ridge (39.2836100000, -76.6511900000) \n", "275046 Franklin Square (39.2920000000, -76.6464600000) \n", "275047 Inner Harbor (39.2817400000, -76.6127900000) \n", "275048 Westport (39.2638700000, -76.6335100000) \n", "\n", " Total Incidents \n", "274999 1 \n", "275000 1 \n", "275001 1 \n", "275002 1 \n", "275003 1 \n", "275004 1 \n", "275005 1 \n", "275006 1 \n", "275007 1 \n", "275008 1 \n", "275009 1 \n", "275010 1 \n", "275011 1 \n", "275012 1 \n", "275013 1 \n", "275014 1 \n", "275015 1 \n", "275016 1 \n", "275017 1 \n", "275018 1 \n", "275019 1 \n", "275020 1 \n", "275021 1 \n", "275022 1 \n", "275023 1 \n", "275024 1 \n", "275025 1 \n", "275026 1 \n", "275027 1 \n", "275028 1 \n", "275029 1 \n", "275030 1 \n", "275031 1 \n", "275032 1 \n", "275033 1 \n", "275034 1 \n", "275035 1 \n", "275036 1 \n", "275037 1 \n", "275038 1 \n", "275039 1 \n", "275040 1 \n", "275041 1 \n", "275042 1 \n", "275043 1 \n", "275044 1 \n", "275045 1 \n", "275046 1 \n", "275047 1 \n", "275048 1 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.tail(50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## That applies to individual columns as well" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "['01/01/2011',\n", " '01/01/2012',\n", " '01/01/2013',\n", " '01/01/2014',\n", " '01/01/2015',\n", " '01/01/2016',\n", " '01/02/2011',\n", " '01/02/2012',\n", " '01/02/2013',\n", " '01/02/2014']" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted(df['CrimeDate'].unique())[:10]" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "['12/30/2011',\n", " '12/30/2012',\n", " '12/30/2013',\n", " '12/30/2014',\n", " '12/30/2015',\n", " '12/31/2011',\n", " '12/31/2012',\n", " '12/31/2013',\n", " '12/31/2014',\n", " '12/31/2015']" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted(df['CrimeDate'].unique())[-10:]" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "['0000',\n", " '0001',\n", " '0002',\n", " '0003',\n", " '0004',\n", " '0005',\n", " '0006',\n", " '0007',\n", " '0008',\n", " '0009']" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted(df['CrimeTime'].unique())[:10]" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "['23:56:00',\n", " '23:56:18',\n", " '23:57:00',\n", " '23:57:06',\n", " '23:57:31',\n", " '23:58:00',\n", " '23:58:26',\n", " '23:59:00',\n", " '23:59:26',\n", " '2400']" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted(df['CrimeTime'].unique())[-10:]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## That's a problem. Different data formats. What do you think we should do? First, let's figure out how many different formats there may be." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([8, 4])" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['CrimeTime'].apply(lambda time: len(time)).unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Let's assume that 4-character CrimeTimes are HHMM. Seconds seems like too fine a level of details. So we'll convert everything to a standard format." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "0 23:52\n", "1 23:04\n", "2 00:00\n", "3 00:30\n", "4 01:00\n", "5 01:01\n", "6 01:15\n", "7 01:20\n", "8 01:40\n", "9 01:40\n", "10 02:00\n", "11 02:07\n", "12 02:30\n", "13 02:30\n", "14 02:54\n", "15 03:00\n", "16 04:25\n", "17 05:00\n", "18 07:04\n", "19 07:05\n", "20 07:40\n", "21 08:30\n", "22 09:00\n", "23 09:30\n", "24 09:30\n", "25 09:30\n", "26 10:15\n", "27 10:30\n", "28 10:35\n", "29 10:40\n", " ... \n", "275019 09:00\n", "275020 09:00\n", "275021 09:00\n", "275022 10:00\n", "275023 10:00\n", "275024 10:00\n", "275025 10:15\n", "275026 10:20\n", "275027 10:30\n", "275028 10:45\n", "275029 10:50\n", "275030 11:00\n", "275031 11:00\n", "275032 11:25\n", "275033 12:00\n", "275034 12:00\n", "275035 12:00\n", "275036 12:00\n", "275037 12:05\n", "275038 12:25\n", "275039 12:37\n", "275040 12:40\n", "275041 13:30\n", "275042 13:30\n", "275043 13:42\n", "275044 13:51\n", "275045 14:00\n", "275046 14:30\n", "275047 15:30\n", "275048 15:34\n", "Name: CrimeTime, dtype: object" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['CrimeTime'].apply(lambda time: time[:5] if len(time) == 8 else time[0:2] + ':' + time[2:])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## That seems to have worked, so let's replace the data column. In reality, you'd probably keep the original and add a normalized column." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df['CrimeTime'] = df['CrimeTime'].apply(lambda time: time[:5] if len(time) == 8 else time[0:2] + ':' + time[2:])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Now let's repeat the process with another column." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array(['O', 'Outside', 'I', 'Inside', nan], dtype=object)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Inside/Outside'].unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## nan means no value stored, it's like NULL in SQL. Let's use I and O instead of Inside and Outside, and use U for Unknown instead of nan." ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df['Inside/Outside'] = df['Inside/Outside'].fillna('U')" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array(['O', 'Outside', 'I', 'Inside', 'U'], dtype=object)" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Inside/Outside'].unique()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df['Inside/Outside'] = df['Inside/Outside'].replace(['Inside', 'Outside'], ['I', 'O'])" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array(['O', 'I', 'U'], dtype=object)" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Inside/Outside'].unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## I wonder how many of each type there are?" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "I 137684\n", "O 133246\n", "U 4119\n", "Name: Inside/Outside, dtype: int64" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Inside/Outside'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What other columns are there?" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Index(['CrimeDate', 'CrimeTime', 'CrimeCode', 'Location', 'Description',\n", " 'Inside/Outside', 'Weapon', 'Post', 'District', 'Neighborhood',\n", " 'Location 1', 'Total Incidents'],\n", " dtype='object')" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.columns" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "1 275049\n", "Name: Total Incidents, dtype: int64" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Total Incidents'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Clearly we can ignore total incidents. What about CrimeCode?" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "4E 46227\n", "6D 37610\n", "5A 26427\n", "7A 24116\n", "6G 15972\n", "6J 12627\n", "6C 12507\n", "6E 12424\n", "4C 10847\n", "5D 8499\n", "4B 7190\n", "3AF 6876\n", "3B 5764\n", "4A 5131\n", "4D 3684\n", "5B 3493\n", "6B 3420\n", "4F 3418\n", "5C 3314\n", "9S 2612\n", "6F 2569\n", "3CF 1974\n", "7C 1674\n", "3AK 1536\n", "3K 1484\n", "2A 1413\n", "1F 1155\n", "3AO 1045\n", "3JF 1035\n", "5F 844\n", " ... \n", "3H 96\n", "3NK 84\n", "7B 82\n", "8AV 76\n", "3AJK 73\n", "8BO 72\n", "3EF 69\n", "3M 61\n", "3AJO 57\n", "8EO 52\n", "3NO 47\n", "3GK 44\n", "3F 42\n", "3GO 22\n", "3LF 21\n", "8GO 18\n", "3LO 17\n", "3EK 17\n", "8BV 13\n", "8CO 10\n", "8I 9\n", "8EV 8\n", "3EO 7\n", "3N 5\n", "8GV 5\n", "8FV 4\n", "8CV 4\n", "6K 2\n", "3LK 1\n", "8DO 1\n", "Name: CrimeCode, dtype: int64" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['CrimeCode'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## There are too many crime codes. What about descriptions?" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "LARCENY 60541\n", "COMMON ASSAULT 46227\n", "BURGLARY 43377\n", "LARCENY FROM AUTO 37610\n", "AGG. ASSAULT 26852\n", "AUTO THEFT 25872\n", "ROBBERY - STREET 16173\n", "ROBBERY - COMMERCIAL 3756\n", "ASSAULT BY THREAT 3418\n", "ROBBERY - RESIDENCE 2893\n", "SHOOTING 2612\n", "RAPE 1644\n", "ARSON 1486\n", "HOMICIDE 1405\n", "ROBBERY - CARJACKING 1183\n", "Name: Description, dtype: int64" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Description'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## That seems more manageable. What about weapons?" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "HANDS 49911\n", "FIREARM 20156\n", "OTHER 13933\n", "KNIFE 9588\n", "Name: Weapon, dtype: int64" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Weapon'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What about district?" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "NORTHEASTERN 43615\n", "SOUTHEASTERN 38033\n", "CENTRAL 32421\n", "SOUTHERN 31726\n", "NORTHERN 30828\n", "NORTHWESTERN 27608\n", "SOUTHWESTERN 25216\n", "EASTERN 23172\n", "WESTERN 22375\n", "Name: District, dtype: int64" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['District'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Let's take inventory and see what's left." ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Index(['CrimeDate', 'CrimeTime', 'CrimeCode', 'Location', 'Description',\n", " 'Inside/Outside', 'Weapon', 'Post', 'District', 'Neighborhood',\n", " 'Location 1', 'Total Incidents'],\n", " dtype='object')" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Location, Location 1, and Neighborhood probably have too many values to deal with right now" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## It looks to me like the Post is an integer and not a float. All of them end in '.0'. Or do they?" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
CrimeDateCrimeTimeCrimeCodeLocationDescriptionInside/OutsideWeaponPostDistrictNeighborhoodLocation 1Total Incidents
2360303/07/201610:105A400 S JANNEY STBURGLARYINaN2.4SOUTHEASTERNCanton Industrial Area(41.6091500000, -76.5455300000)1
2360403/07/201610:105A400 S JANNEY STBURGLARYINaN2.4SOUTHEASTERNCanton Industrial Area(41.6091500000, -76.5455300000)1
\n", "
" ], "text/plain": [ " CrimeDate CrimeTime CrimeCode Location Description \\\n", "23603 03/07/2016 10:10 5A 400 S JANNEY ST BURGLARY \n", "23604 03/07/2016 10:10 5A 400 S JANNEY ST BURGLARY \n", "\n", " Inside/Outside Weapon Post District Neighborhood \\\n", "23603 I NaN 2.4 SOUTHEASTERN Canton Industrial Area \n", "23604 I NaN 2.4 SOUTHEASTERN Canton Industrial Area \n", "\n", " Location 1 Total Incidents \n", "23603 (41.6091500000, -76.5455300000) 1 \n", "23604 (41.6091500000, -76.5455300000) 1 " ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['Post'].notnull() & (round(df.Post) - df.Post != 0.0)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Now that's an outlier, and a duplicate record to boot! I wonder how many duplicate records there are?" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "10974" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df) - len(df.drop_duplicates())" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df.drop_duplicates(inplace = True)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
CrimeDateCrimeTimeCrimeCodeLocationDescriptionInside/OutsideWeaponPostDistrictNeighborhoodLocation 1Total Incidents
2360303/07/201610:105A400 S JANNEY STBURGLARYINaN2.4SOUTHEASTERNCanton Industrial Area(41.6091500000, -76.5455300000)1
\n", "
" ], "text/plain": [ " CrimeDate CrimeTime CrimeCode Location Description \\\n", "23603 03/07/2016 10:10 5A 400 S JANNEY ST BURGLARY \n", "\n", " Inside/Outside Weapon Post District Neighborhood \\\n", "23603 I NaN 2.4 SOUTHEASTERN Canton Industrial Area \n", "\n", " Location 1 Total Incidents \n", "23603 (41.6091500000, -76.5455300000) 1 " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['Post'].notnull() & (round(df.Post) - df.Post != 0.0)]" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "264075" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df)" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df = df.drop(23603)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "264074" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
CrimeDateCrimeTimeCrimeCodeLocationDescriptionInside/OutsideWeaponPostDistrictNeighborhoodLocation 1Total Incidents
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [CrimeDate, CrimeTime, CrimeCode, Location, Description, Inside/Outside, Weapon, Post, District, Neighborhood, Location 1, Total Incidents]\n", "Index: []" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['Post'].notnull() & (round(df.Post) - df.Post != 0.0)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## OK, let's get rid of columns we're not going to use" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Index(['CrimeDate', 'CrimeTime', 'CrimeCode', 'Location', 'Description',\n", " 'Inside/Outside', 'Weapon', 'Post', 'District', 'Neighborhood',\n", " 'Location 1', 'Total Incidents'],\n", " dtype='object')" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## In df.drop() the axis is rows=0 or columns=1" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df.drop('Location', axis=1, inplace=True)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df.drop('Location 1', axis=1, inplace=True)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df.drop('Neighborhood', axis=1, inplace=True)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df.drop('Total Incidents', axis=1, inplace=True)" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CrimeDateCrimeTimeCrimeCodeDescriptionInside/OutsideWeaponPostDistrict
009/03/201623:524CAGG. ASSAULTOOTHER643.0NORTHWESTERN
109/03/201623:041FHOMICIDEOFIREARM243.0SOUTHEASTERN
209/03/201600:004DAGG. ASSAULTIHANDS843.0SOUTHWESTERN
309/03/201600:304DAGG. ASSAULTOHANDS111.0CENTRAL
409/03/201601:007AAUTO THEFTONaN643.0NORTHWESTERN
509/03/201601:015ABURGLARYINaN443.0NORTHEASTERN
609/03/201601:157AAUTO THEFTONaN333.0NORTHEASTERN
709/03/201601:204BAGG. ASSAULTOKNIFE213.0SOUTHEASTERN
809/03/201601:404ECOMMON ASSAULTIHANDS143.0CENTRAL
909/03/201601:404BAGG. ASSAULTIKNIFE143.0CENTRAL
1009/03/201602:006ELARCENYONaN513.0NORTHERN
1109/03/201602:074ECOMMON ASSAULTIHANDS822.0SOUTHWESTERN
1209/03/201602:304ECOMMON ASSAULTIHANDS941.0SOUTHERN
1409/03/201602:544ECOMMON ASSAULTIHANDS543.0NORTHERN
1509/03/201603:004DAGG. ASSAULTIHANDS621.0NORTHWESTERN
1609/03/201604:253COROBBERY - COMMERCIALIOTHER212.0SOUTHEASTERN
1709/03/201605:004ECOMMON ASSAULTOHANDS514.0NORTHERN
1809/03/201607:046CLARCENYINaN141.0CENTRAL
1909/03/201607:056BLARCENYONaN332.0EASTERN
2009/03/201607:403AKROBBERY - STREETOKNIFE934.0SOUTHERN
2109/03/201608:306JLARCENYINaN213.0SOUTHEASTERN
2209/03/201609:005DBURGLARYONaN911.0SOUTHERN
2309/03/201609:306ELARCENYONaN123.0WESTERN
2409/03/201609:306JLARCENYONaN733.0WESTERN
2509/03/201609:304AAGG. ASSAULTIFIREARM614.0NORTHWESTERN
2609/03/201610:155ABURGLARYINaN312.0EASTERN
2709/03/201610:304ECOMMON ASSAULTOHANDS131.0WESTERN
2809/03/201610:356GLARCENYINaN842.0SOUTHWESTERN
2909/03/201610:404CAGG. ASSAULTOOTHER221.0SOUTHEASTERN
3009/03/201611:307AAUTO THEFTONaN513.0NORTHERN
...........................
27501801/01/201108:305ABURGLARYINaN424.0NORTHEASTERN
27501901/01/201109:006GLARCENYINaN941.0CENTRAL
27502001/01/201109:006ELARCENYONaN743.0WESTERN
27502101/01/201109:004ECOMMON ASSAULTIHANDS822.0SOUTHWESTERN
27502201/01/201110:006JLARCENYINaN411.0NORTHEASTERN
27502301/01/201110:005ABURGLARYINaN723.0WESTERN
27502401/01/201110:005ABURGLARYINaN141.0CENTRAL
27502501/01/201110:155ABURGLARYINaN935.0SOUTHERN
27502601/01/201110:205ABURGLARYINaN312.0EASTERN
27502701/01/201110:304ECOMMON ASSAULTIHANDS813.0SOUTHWESTERN
27502801/01/201110:456CLARCENYINaN111.0CENTRAL
27502901/01/201110:507AAUTO THEFTINaN922.0SOUTHERN
27503001/01/201111:006JLARCENYINaN141.0CENTRAL
27503101/01/201111:006JLARCENYINaN111.0CENTRAL
27503201/01/201111:256DLARCENY FROM AUTOONaN233.0SOUTHEASTERN
27503301/01/201112:006DLARCENY FROM AUTOONaN943.0SOUTHERN
27503401/01/201112:005BBURGLARYINaN713.0WESTERN
27503501/01/201112:006ELARCENYONaN623.0NORTHWESTERN
27503601/01/201112:006DLARCENY FROM AUTOONaN311.0EASTERN
27503701/01/201112:055ABURGLARYINaN722.0WESTERN
27503801/01/201112:256DLARCENY FROM AUTOONaN211.0SOUTHEASTERN
27503901/01/201112:374BAGG. ASSAULTIKNIFE332.0EASTERN
27504001/01/201112:406DLARCENY FROM AUTOONaN233.0SOUTHEASTERN
27504101/01/201113:306ELARCENYONaN421.0NORTHEASTERN
27504201/01/201113:306DLARCENY FROM AUTOUNaN833.0SOUTHWESTERN
27504301/01/201113:426ELARCENYONaN722.0WESTERN
27504401/01/201113:513CKROBBERY - COMMERCIALIKNIFE743.0WESTERN
27504501/01/201114:006DLARCENY FROM AUTOONaN841.0SOUTHWESTERN
27504601/01/201114:304ECOMMON ASSAULTIHANDS711.0WESTERN
27504701/01/201115:306DLARCENY FROM AUTOONaN112.0SOUTHERN
\n", "

264074 rows × 8 columns

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" ], "text/plain": [ " CrimeDate CrimeTime CrimeCode Description Inside/Outside \\\n", "0 09/03/2016 23:52 4C AGG. ASSAULT O \n", "1 09/03/2016 23:04 1F HOMICIDE O \n", "2 09/03/2016 00:00 4D AGG. ASSAULT I \n", "3 09/03/2016 00:30 4D AGG. ASSAULT O \n", "4 09/03/2016 01:00 7A AUTO THEFT O \n", "5 09/03/2016 01:01 5A BURGLARY I \n", "6 09/03/2016 01:15 7A AUTO THEFT O \n", "7 09/03/2016 01:20 4B AGG. ASSAULT O \n", "8 09/03/2016 01:40 4E COMMON ASSAULT I \n", "9 09/03/2016 01:40 4B AGG. ASSAULT I \n", "10 09/03/2016 02:00 6E LARCENY O \n", "11 09/03/2016 02:07 4E COMMON ASSAULT I \n", "12 09/03/2016 02:30 4E COMMON ASSAULT I \n", "14 09/03/2016 02:54 4E COMMON ASSAULT I \n", "15 09/03/2016 03:00 4D AGG. ASSAULT I \n", "16 09/03/2016 04:25 3CO ROBBERY - COMMERCIAL I \n", "17 09/03/2016 05:00 4E COMMON ASSAULT O \n", "18 09/03/2016 07:04 6C LARCENY I \n", "19 09/03/2016 07:05 6B LARCENY O \n", "20 09/03/2016 07:40 3AK ROBBERY - STREET O \n", "21 09/03/2016 08:30 6J LARCENY I \n", "22 09/03/2016 09:00 5D BURGLARY O \n", "23 09/03/2016 09:30 6E LARCENY O \n", "24 09/03/2016 09:30 6J LARCENY O \n", "25 09/03/2016 09:30 4A AGG. ASSAULT I \n", "26 09/03/2016 10:15 5A BURGLARY I \n", "27 09/03/2016 10:30 4E COMMON ASSAULT O \n", "28 09/03/2016 10:35 6G LARCENY I \n", "29 09/03/2016 10:40 4C AGG. ASSAULT O \n", "30 09/03/2016 11:30 7A AUTO THEFT O \n", "... ... ... ... ... ... \n", "275018 01/01/2011 08:30 5A BURGLARY I \n", "275019 01/01/2011 09:00 6G LARCENY I \n", "275020 01/01/2011 09:00 6E LARCENY O \n", "275021 01/01/2011 09:00 4E COMMON ASSAULT I \n", "275022 01/01/2011 10:00 6J LARCENY I \n", "275023 01/01/2011 10:00 5A BURGLARY I \n", "275024 01/01/2011 10:00 5A BURGLARY I \n", "275025 01/01/2011 10:15 5A BURGLARY I \n", "275026 01/01/2011 10:20 5A BURGLARY I \n", "275027 01/01/2011 10:30 4E COMMON ASSAULT I \n", "275028 01/01/2011 10:45 6C LARCENY I \n", "275029 01/01/2011 10:50 7A AUTO THEFT I \n", "275030 01/01/2011 11:00 6J LARCENY I \n", "275031 01/01/2011 11:00 6J LARCENY I \n", "275032 01/01/2011 11:25 6D LARCENY FROM AUTO O \n", "275033 01/01/2011 12:00 6D LARCENY FROM AUTO O \n", "275034 01/01/2011 12:00 5B BURGLARY I \n", "275035 01/01/2011 12:00 6E LARCENY O \n", "275036 01/01/2011 12:00 6D LARCENY FROM AUTO O \n", "275037 01/01/2011 12:05 5A BURGLARY I \n", "275038 01/01/2011 12:25 6D LARCENY FROM AUTO O \n", "275039 01/01/2011 12:37 4B AGG. ASSAULT I \n", "275040 01/01/2011 12:40 6D LARCENY FROM AUTO O \n", "275041 01/01/2011 13:30 6E LARCENY O \n", "275042 01/01/2011 13:30 6D LARCENY FROM AUTO U \n", "275043 01/01/2011 13:42 6E LARCENY O \n", "275044 01/01/2011 13:51 3CK ROBBERY - COMMERCIAL I \n", "275045 01/01/2011 14:00 6D LARCENY FROM AUTO O \n", "275046 01/01/2011 14:30 4E COMMON ASSAULT I \n", "275047 01/01/2011 15:30 6D LARCENY FROM AUTO O \n", "\n", " Weapon Post District \n", "0 OTHER 643.0 NORTHWESTERN \n", "1 FIREARM 243.0 SOUTHEASTERN \n", "2 HANDS 843.0 SOUTHWESTERN \n", "3 HANDS 111.0 CENTRAL \n", "4 NaN 643.0 NORTHWESTERN \n", "5 NaN 443.0 NORTHEASTERN \n", "6 NaN 333.0 NORTHEASTERN \n", "7 KNIFE 213.0 SOUTHEASTERN \n", "8 HANDS 143.0 CENTRAL \n", "9 KNIFE 143.0 CENTRAL \n", "10 NaN 513.0 NORTHERN \n", "11 HANDS 822.0 SOUTHWESTERN \n", "12 HANDS 941.0 SOUTHERN \n", "14 HANDS 543.0 NORTHERN \n", "15 HANDS 621.0 NORTHWESTERN \n", "16 OTHER 212.0 SOUTHEASTERN \n", "17 HANDS 514.0 NORTHERN \n", "18 NaN 141.0 CENTRAL \n", "19 NaN 332.0 EASTERN \n", "20 KNIFE 934.0 SOUTHERN \n", "21 NaN 213.0 SOUTHEASTERN \n", "22 NaN 911.0 SOUTHERN \n", "23 NaN 123.0 WESTERN \n", "24 NaN 733.0 WESTERN \n", "25 FIREARM 614.0 NORTHWESTERN \n", "26 NaN 312.0 EASTERN \n", "27 HANDS 131.0 WESTERN \n", "28 NaN 842.0 SOUTHWESTERN \n", "29 OTHER 221.0 SOUTHEASTERN \n", "30 NaN 513.0 NORTHERN \n", "... ... ... ... \n", "275018 NaN 424.0 NORTHEASTERN \n", "275019 NaN 941.0 CENTRAL \n", "275020 NaN 743.0 WESTERN \n", "275021 HANDS 822.0 SOUTHWESTERN \n", "275022 NaN 411.0 NORTHEASTERN \n", "275023 NaN 723.0 WESTERN \n", "275024 NaN 141.0 CENTRAL \n", "275025 NaN 935.0 SOUTHERN \n", "275026 NaN 312.0 EASTERN \n", "275027 HANDS 813.0 SOUTHWESTERN \n", "275028 NaN 111.0 CENTRAL \n", "275029 NaN 922.0 SOUTHERN \n", "275030 NaN 141.0 CENTRAL \n", "275031 NaN 111.0 CENTRAL \n", "275032 NaN 233.0 SOUTHEASTERN \n", "275033 NaN 943.0 SOUTHERN \n", "275034 NaN 713.0 WESTERN \n", "275035 NaN 623.0 NORTHWESTERN \n", "275036 NaN 311.0 EASTERN \n", "275037 NaN 722.0 WESTERN \n", "275038 NaN 211.0 SOUTHEASTERN \n", "275039 KNIFE 332.0 EASTERN \n", "275040 NaN 233.0 SOUTHEASTERN \n", "275041 NaN 421.0 NORTHEASTERN \n", "275042 NaN 833.0 SOUTHWESTERN \n", "275043 NaN 722.0 WESTERN \n", "275044 KNIFE 743.0 WESTERN \n", "275045 NaN 841.0 SOUTHWESTERN \n", "275046 HANDS 711.0 WESTERN \n", "275047 NaN 112.0 SOUTHERN \n", "\n", "[264074 rows x 8 columns]" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The precise time may not be useful, but maybe the hour would be" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df['CrimeHour'] = df['CrimeTime'].apply(lambda time: time[:2])" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "18 15908\n", "17 15436\n", "15 15096\n", "16 14984\n", "20 14550\n", "21 14476\n", "19 14351\n", "22 13870\n", "12 13555\n", "23 12921\n", "14 12593\n", "13 11575\n", "00 11480\n", "01 10908\n", "11 10633\n", "10 10317\n", "08 9699\n", "09 9636\n", "02 7582\n", "07 7176\n", "03 5391\n", "06 4372\n", "04 3987\n", "05 3577\n", "24 1\n", "Name: CrimeHour, dtype: int64" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['CrimeHour'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## That 24 that occurs once looks sketchy. Let's get rid of it." ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
CrimeDateCrimeTimeCrimeCodeDescriptionInside/OutsideWeaponPostDistrictCrimeHour
18790309/24/201224:009SSHOOTINGOFIREARM714.0WESTERN24
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" ], "text/plain": [ " CrimeDate CrimeTime CrimeCode Description Inside/Outside Weapon \\\n", "187903 09/24/2012 24:00 9S SHOOTING O FIREARM \n", "\n", " Post District CrimeHour \n", "187903 714.0 WESTERN 24 " ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['CrimeHour'] == '24']" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df = df.drop(187903)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
CrimeDateCrimeTimeCrimeCodeDescriptionInside/OutsideWeaponPostDistrictCrimeHour
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [CrimeDate, CrimeTime, CrimeCode, Description, Inside/Outside, Weapon, Post, District, CrimeHour]\n", "Index: []" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[df['CrimeHour'] == '24']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Likewise, the day of the week might be more interesting than the precise date" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df['CrimeDay'] = df['CrimeDate'].apply(lambda date: pd.Timestamp(date).weekday_name)" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Friday 40136\n", "Monday 38675\n", "Tuesday 37774\n", "Wednesday 37719\n", "Thursday 37483\n", "Saturday 37175\n", "Sunday 35111\n", "Name: CrimeDay, dtype: int64" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['CrimeDay'].value_counts()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## Final cleanup" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Index(['CrimeDate', 'CrimeTime', 'CrimeCode', 'Description', 'Inside/Outside',\n", " 'Weapon', 'Post', 'District', 'CrimeHour', 'CrimeDay'],\n", " dtype='object')" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.columns" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df.drop('CrimeDate', axis=1, inplace=True)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df.drop('CrimeTime', axis=1, inplace=True)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CrimeCodeDescriptionInside/OutsideWeaponPostDistrictCrimeHourCrimeDay
04CAGG. ASSAULTOOTHER643.0NORTHWESTERN23Saturday
11FHOMICIDEOFIREARM243.0SOUTHEASTERN23Saturday
24DAGG. ASSAULTIHANDS843.0SOUTHWESTERN00Saturday
34DAGG. ASSAULTOHANDS111.0CENTRAL00Saturday
47AAUTO THEFTONaN643.0NORTHWESTERN01Saturday
55ABURGLARYINaN443.0NORTHEASTERN01Saturday
67AAUTO THEFTONaN333.0NORTHEASTERN01Saturday
74BAGG. ASSAULTOKNIFE213.0SOUTHEASTERN01Saturday
84ECOMMON ASSAULTIHANDS143.0CENTRAL01Saturday
94BAGG. ASSAULTIKNIFE143.0CENTRAL01Saturday
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" ], "text/plain": [ " CrimeCode Description Inside/Outside Weapon Post District \\\n", "0 4C AGG. ASSAULT O OTHER 643.0 NORTHWESTERN \n", "1 1F HOMICIDE O FIREARM 243.0 SOUTHEASTERN \n", "2 4D AGG. ASSAULT I HANDS 843.0 SOUTHWESTERN \n", "3 4D AGG. ASSAULT O HANDS 111.0 CENTRAL \n", "4 7A AUTO THEFT O NaN 643.0 NORTHWESTERN \n", "5 5A BURGLARY I NaN 443.0 NORTHEASTERN \n", "6 7A AUTO THEFT O NaN 333.0 NORTHEASTERN \n", "7 4B AGG. ASSAULT O KNIFE 213.0 SOUTHEASTERN \n", "8 4E COMMON ASSAULT I HANDS 143.0 CENTRAL \n", "9 4B AGG. ASSAULT I KNIFE 143.0 CENTRAL \n", "\n", " CrimeHour CrimeDay \n", "0 23 Saturday \n", "1 23 Saturday \n", "2 00 Saturday \n", "3 00 Saturday \n", "4 01 Saturday \n", "5 01 Saturday \n", "6 01 Saturday \n", "7 01 Saturday \n", "8 01 Saturday \n", "9 01 Saturday " ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head(10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Let's see if we can learn a decision tree that predicts Weapon" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.tree import DecisionTreeClassifier, export_graphviz" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df2 = df.copy()" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CrimeCodeDescriptionInside/OutsideWeaponPostDistrictCrimeHourCrimeDay
04CAGG. ASSAULTOOTHER643.0NORTHWESTERN23Saturday
11FHOMICIDEOFIREARM243.0SOUTHEASTERN23Saturday
24DAGG. ASSAULTIHANDS843.0SOUTHWESTERN00Saturday
34DAGG. ASSAULTOHANDS111.0CENTRAL00Saturday
47AAUTO THEFTONaN643.0NORTHWESTERN01Saturday
55ABURGLARYINaN443.0NORTHEASTERN01Saturday
67AAUTO THEFTONaN333.0NORTHEASTERN01Saturday
74BAGG. ASSAULTOKNIFE213.0SOUTHEASTERN01Saturday
84ECOMMON ASSAULTIHANDS143.0CENTRAL01Saturday
94BAGG. ASSAULTIKNIFE143.0CENTRAL01Saturday
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" ], "text/plain": [ " CrimeCode Description Inside/Outside Weapon Post District \\\n", "0 4C AGG. ASSAULT O OTHER 643.0 NORTHWESTERN \n", "1 1F HOMICIDE O FIREARM 243.0 SOUTHEASTERN \n", "2 4D AGG. ASSAULT I HANDS 843.0 SOUTHWESTERN \n", "3 4D AGG. ASSAULT O HANDS 111.0 CENTRAL \n", "4 7A AUTO THEFT O NaN 643.0 NORTHWESTERN \n", "5 5A BURGLARY I NaN 443.0 NORTHEASTERN \n", "6 7A AUTO THEFT O NaN 333.0 NORTHEASTERN \n", "7 4B AGG. ASSAULT O KNIFE 213.0 SOUTHEASTERN \n", "8 4E COMMON ASSAULT I HANDS 143.0 CENTRAL \n", "9 4B AGG. ASSAULT I KNIFE 143.0 CENTRAL \n", "\n", " CrimeHour CrimeDay \n", "0 23 Saturday \n", "1 23 Saturday \n", "2 00 Saturday \n", "3 00 Saturday \n", "4 01 Saturday \n", "5 01 Saturday \n", "6 01 Saturday \n", "7 01 Saturday \n", "8 01 Saturday \n", "9 01 Saturday " ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df2.head(10)" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "collapsed": false }, "outputs": [], "source": [ "df2.drop(['CrimeCode', 'Description', 'Post'], axis=1, inplace=True)" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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Inside/OutsideWeaponDistrictCrimeHourCrimeDay
0OOTHERNORTHWESTERN23Saturday
1OFIREARMSOUTHEASTERN23Saturday
2IHANDSSOUTHWESTERN00Saturday
3OHANDSCENTRAL00Saturday
4ONaNNORTHWESTERN01Saturday
5INaNNORTHEASTERN01Saturday
6ONaNNORTHEASTERN01Saturday
7OKNIFESOUTHEASTERN01Saturday
8IHANDSCENTRAL01Saturday
9IKNIFECENTRAL01Saturday
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" ], "text/plain": [ " Inside/Outside Weapon District CrimeHour CrimeDay\n", "0 O OTHER NORTHWESTERN 23 Saturday\n", "1 O FIREARM SOUTHEASTERN 23 Saturday\n", "2 I HANDS SOUTHWESTERN 00 Saturday\n", "3 O HANDS CENTRAL 00 Saturday\n", "4 O NaN NORTHWESTERN 01 Saturday\n", "5 I NaN NORTHEASTERN 01 Saturday\n", "6 O NaN NORTHEASTERN 01 Saturday\n", "7 O KNIFE SOUTHEASTERN 01 Saturday\n", "8 I HANDS CENTRAL 01 Saturday\n", "9 I KNIFE CENTRAL 01 Saturday" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df2.head(10)" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "264073" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df2)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df2.dropna(inplace=True)" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "85454" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df2)" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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Inside/OutsideWeaponDistrictCrimeHourCrimeDay
0OOTHERNORTHWESTERN23Saturday
1OFIREARMSOUTHEASTERN23Saturday
2IHANDSSOUTHWESTERN00Saturday
3OHANDSCENTRAL00Saturday
7OKNIFESOUTHEASTERN01Saturday
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11IHANDSSOUTHWESTERN02Saturday
12IHANDSSOUTHERN02Saturday
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" ], "text/plain": [ " Inside/Outside Weapon District CrimeHour CrimeDay\n", "0 O OTHER NORTHWESTERN 23 Saturday\n", "1 O FIREARM SOUTHEASTERN 23 Saturday\n", "2 I HANDS SOUTHWESTERN 00 Saturday\n", "3 O HANDS CENTRAL 00 Saturday\n", "7 O KNIFE SOUTHEASTERN 01 Saturday\n", "8 I HANDS CENTRAL 01 Saturday\n", "9 I KNIFE CENTRAL 01 Saturday\n", "11 I HANDS SOUTHWESTERN 02 Saturday\n", "12 I HANDS SOUTHERN 02 Saturday\n", "14 I HANDS NORTHERN 02 Saturday" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df2.head(10)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## The scikit-learn decison tree wants EVERYTHING to be numbers, which is a pain. So we need to convert somehow. We'll use a one-hot encoding." ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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Inside_Outside_IInside_Outside_OInside_Outside_UDistrict_CENTRALDistrict_EASTERNDistrict_NORTHEASTERNDistrict_NORTHERNDistrict_NORTHWESTERNDistrict_SOUTHEASTERNDistrict_SOUTHERNDistrict_SOUTHWESTERNDistrict_WESTERNCrimeDay_FridayCrimeDay_MondayCrimeDay_SaturdayCrimeDay_SundayCrimeDay_ThursdayCrimeDay_TuesdayCrimeDay_Wednesday
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" ], "text/plain": [ " Inside_Outside_I Inside_Outside_O Inside_Outside_U District_CENTRAL \\\n", "0 0.0 1.0 0.0 0.0 \n", "1 0.0 1.0 0.0 0.0 \n", "2 1.0 0.0 0.0 0.0 \n", "\n", " District_EASTERN District_NORTHEASTERN District_NORTHERN \\\n", "0 0.0 0.0 0.0 \n", "1 0.0 0.0 0.0 \n", "2 0.0 0.0 0.0 \n", "\n", " District_NORTHWESTERN District_SOUTHEASTERN District_SOUTHERN \\\n", "0 1.0 0.0 0.0 \n", "1 0.0 1.0 0.0 \n", "2 0.0 0.0 0.0 \n", "\n", " District_SOUTHWESTERN District_WESTERN CrimeDay_Friday CrimeDay_Monday \\\n", "0 0.0 0.0 0.0 0.0 \n", "1 0.0 0.0 0.0 0.0 \n", "2 1.0 0.0 0.0 0.0 \n", "\n", " CrimeDay_Saturday CrimeDay_Sunday CrimeDay_Thursday CrimeDay_Tuesday \\\n", "0 1.0 0.0 0.0 0.0 \n", "1 1.0 0.0 0.0 0.0 \n", "2 1.0 0.0 0.0 0.0 \n", "\n", " CrimeDay_Wednesday \n", "0 0.0 \n", "1 0.0 \n", "2 0.0 " ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X.head(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What about CrimeHour? Is it already a number?" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Inside/Outside object\n", "Weapon object\n", "District object\n", "CrimeHour object\n", "CrimeDay object\n", "dtype: object" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df2.dtypes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Nope. Let's convert it and add it to our dataframe." ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "collapsed": false }, "outputs": [], "source": [ "X['CrimeHour'] = df2['CrimeHour'].astype(float)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What do things look like now?" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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\n", "
" ], "text/plain": [ " Inside_Outside_I Inside_Outside_O Inside_Outside_U District_CENTRAL \\\n", "0 0.0 1.0 0.0 0.0 \n", "1 0.0 1.0 0.0 0.0 \n", "2 1.0 0.0 0.0 0.0 \n", "3 0.0 1.0 0.0 1.0 \n", "7 0.0 1.0 0.0 0.0 \n", "8 1.0 0.0 0.0 1.0 \n", "9 1.0 0.0 0.0 1.0 \n", "11 1.0 0.0 0.0 0.0 \n", "12 1.0 0.0 0.0 0.0 \n", "14 1.0 0.0 0.0 0.0 \n", "\n", " District_EASTERN District_NORTHEASTERN District_NORTHERN \\\n", "0 0.0 0.0 0.0 \n", "1 0.0 0.0 0.0 \n", "2 0.0 0.0 0.0 \n", "3 0.0 0.0 0.0 \n", "7 0.0 0.0 0.0 \n", "8 0.0 0.0 0.0 \n", "9 0.0 0.0 0.0 \n", "11 0.0 0.0 0.0 \n", "12 0.0 0.0 0.0 \n", "14 0.0 0.0 1.0 \n", "\n", " District_NORTHWESTERN District_SOUTHEASTERN District_SOUTHERN \\\n", "0 1.0 0.0 0.0 \n", "1 0.0 1.0 0.0 \n", "2 0.0 0.0 0.0 \n", "3 0.0 0.0 0.0 \n", "7 0.0 1.0 0.0 \n", "8 0.0 0.0 0.0 \n", "9 0.0 0.0 0.0 \n", "11 0.0 0.0 0.0 \n", "12 0.0 0.0 1.0 \n", "14 0.0 0.0 0.0 \n", "\n", " District_SOUTHWESTERN District_WESTERN CrimeDay_Friday CrimeDay_Monday \\\n", "0 0.0 0.0 0.0 0.0 \n", "1 0.0 0.0 0.0 0.0 \n", "2 1.0 0.0 0.0 0.0 \n", "3 0.0 0.0 0.0 0.0 \n", "7 0.0 0.0 0.0 0.0 \n", "8 0.0 0.0 0.0 0.0 \n", "9 0.0 0.0 0.0 0.0 \n", "11 1.0 0.0 0.0 0.0 \n", "12 0.0 0.0 0.0 0.0 \n", "14 0.0 0.0 0.0 0.0 \n", "\n", " CrimeDay_Saturday CrimeDay_Sunday CrimeDay_Thursday CrimeDay_Tuesday \\\n", "0 1.0 0.0 0.0 0.0 \n", "1 1.0 0.0 0.0 0.0 \n", "2 1.0 0.0 0.0 0.0 \n", "3 1.0 0.0 0.0 0.0 \n", "7 1.0 0.0 0.0 0.0 \n", "8 1.0 0.0 0.0 0.0 \n", "9 1.0 0.0 0.0 0.0 \n", "11 1.0 0.0 0.0 0.0 \n", "12 1.0 0.0 0.0 0.0 \n", "14 1.0 0.0 0.0 0.0 \n", "\n", " CrimeDay_Wednesday CrimeHour \n", "0 0.0 23.0 \n", "1 0.0 23.0 \n", "2 0.0 0.0 \n", "3 0.0 0.0 \n", "7 0.0 1.0 \n", "8 0.0 1.0 \n", "9 0.0 1.0 \n", "11 0.0 2.0 \n", "12 0.0 2.0 \n", "14 0.0 2.0 " ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X.head(10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Nice! Now let's get a Y dataframe based on the type of weapon." ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn import preprocessing" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "collapsed": true }, "outputs": [], "source": [ "le = preprocessing.LabelEncoder()" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "collapsed": false }, "outputs": [], "source": [ "Y = le.fit_transform(df2['Weapon'])" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array(['FIREARM', 'HANDS', 'KNIFE', 'OTHER'], dtype=object)" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "le.inverse_transform([0, 1, 2, 3])" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "collapsed": false }, "outputs": [], "source": [ "dt = DecisionTreeClassifier()" ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None,\n", " max_features=None, max_leaf_nodes=None,\n", " min_impurity_split=1e-07, min_samples_leaf=1,\n", " min_samples_split=2, min_weight_fraction_leaf=0.0,\n", " presort=False, random_state=None, splitter='best')" ] }, "execution_count": 72, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dt.fit(X.values, Y)" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Index(['Inside_Outside_I', 'Inside_Outside_O', 'Inside_Outside_U',\n", " 'District_CENTRAL', 'District_EASTERN', 'District_NORTHEASTERN',\n", " 'District_NORTHERN', 'District_NORTHWESTERN', 'District_SOUTHEASTERN',\n", " 'District_SOUTHERN', 'District_SOUTHWESTERN', 'District_WESTERN',\n", " 'CrimeDay_Friday', 'CrimeDay_Monday', 'CrimeDay_Saturday',\n", " 'CrimeDay_Sunday', 'CrimeDay_Thursday', 'CrimeDay_Tuesday',\n", " 'CrimeDay_Wednesday', 'CrimeHour'],\n", " dtype='object')" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X.columns" ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "collapsed": false }, "outputs": [], "source": [ "with open(\"dt.dot\", 'w') as f:\n", " export_graphviz(dt, out_file=f, feature_names=X.columns)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Grab graphviz from http://www.graphviz.org/" ] }, { "cell_type": "code", "execution_count": 75, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import os" ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "os.system('dot -Tpng dt.dot -o dt.png')" ] }, { "cell_type": "code", "execution_count": 88, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from IPython.display import Image" ] }, { "cell_type": "code", "execution_count": 91, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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Q5uRcg/akcltwlLakuBIuvXry/S84t0TN4h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\nU0eNRbM/1cvP+al+bkXhJbfccovr/3rvK5xB39u77rrLW2XRH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mTbK5c+eG+zRq1MjatWsXft4cC2rnvv/++66t2759e2vbtm3GM5zRPtoc3xjnRAABBBBAAAEE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\nGIxlM2fOtHnz5plmBd5hhx2sXLl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y8uijj5qXvXwfiPu///s/0wmi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\nAoo8efKI9kEGTtoPGW5AMC3v+/ykDiAwb948v2r++usvOXbsmNx7772iCfN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3b5ZGjRq5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IvuX6ZMGXn66aelX79+0qtXL/XCm0XFZ1FJgARIgARIgARI\ngARIgARIICsILF68WFq0aCGY337//feFxiey4rHlVCFbt24tH330kWzYsEGaN28us2fPzqn6sTIk\nQAIkQAIkQAIkQAIkQAIkQAK5RwBz2XDA8dBDD6lM5d1331WHCi+++KLKWWrWrCkXXnihGqnYsmVL\n7gFgjUiABEiABEiABDKaAA1QZPTjYeFIgARIgARIgATykcC8efNkyJAh0qxZM4FXjssvv1wqVKgg\njzzyiKxZs0bgueOKK66Q+vXr5yMe1pkESIAESIAESIAESIAESIAESCDPCIwePVp69+4tAwYMkKee\nekqghMFAAlEIlC5dWuUqF198sZxyyilq7DPK9UxLAiRAAiRAAiRAAiRAAiRAAiQQn8Drr78uLVu2\nlGrVqsmHH34oDRo0iJ+YZ0igCAnUqVNHDaA0btxY2rRpIy+88EIR3o1ZkwAJkAAJkAAJkAAJkAAJ\nkAAJkED6CJQqVUoOPfRQGTFihHz11Vcyd+5c6d+/v7z55pvSrl07lbsMHDhQJk+eLBs3bkzfjZkT\nCZAACZAACZAACcQhQC3NOGAYTQIkQAIkQAIkQALFRQBCoLfeeksmTJggEydOlBUrVsjuu++unl1h\niKJDhw707FpcD4P3IQESIAESIAESIAESIAESIAESyCgC8PRx/vnny6BBg+S2227LqLKxMNlHYPjw\n4VKpUiU555xzZP369fpeZV8tWGISIAESIAESIAESIAESIAESyBwCI0eOVE+cxx9/vDz++OOc186c\nR5O3Jdlxxx1V7+Kyyy6TE088UZYsWSLXX3+9YCEPAwmQAAmQAAmQAAmQAAmQAAmQAAlkCwEYV8Qf\n1hJ8/vnnMm7cOP0bNWqU7LDDDtKlSxfp2bOndO7cWSpWrJgt1WI5SYAESIAESIAEsogADVBk0cNi\nUUmABEiABEiABHKHwM8//6wWSF955RWZMmWKLno48MADpV+/ftK9e3c56KCDqACRO4+bNSEBEiAB\nEiABEiABEiABEiABEkiBwLBhw+Tqq6+WW2+9VQYPHpxCDryEBAoSuPbaa9UIxUUXXaTymKFDhxZM\nxBgSIAESIAESIAESIAESIAESIIGEBLZs2SKXXnqp3H///XLTTTfJddddlzA9T5JAcRLYZptt5J57\n7pEGDRrIeeedJ4sXL5YnnnhCtttuu+IsBu9FAiRAAiRAAiRAAiRAAiRAAiRAAmkhUL9+fbnqqqv0\nb+XKlTJ+/Hg1RnHCCSdI2bJl5cgjj1RjFN26dZOddtopLfdkJiRAAiRAAiRAAiRAAxR8B0iABEiA\nBEiABEigmAgsW7ZMYHBiwoQJMmvWLDUw0aZNG8FCBxidqFWrVjGVhLchARIgARIgARIgARIgARIg\nARIggcwmAIMTt99+uzzwwAO6UCCzS8vSZRuBCy64QL3CDBw4UH799Ve57777aAg02x4iy0sCJEAC\nJEACJEACJEACJFBiBH777TfBAocZM2bI888/L8cdd1yJlYU3JoFEBM4880ypW7eu9O7dW6CbAV2N\n6tWrJ7qE50iABEiABEiABEiABEiABEiABEggownsueeecuGFF+rfunXrdKwLgxRnnHGG/PPPP9Ku\nXTs1RtGjRw+pVq1aRteFhSMBEiABEiABEshsAqUcEzK7iCwdCZAACZAACZAACWQnAXSzPvzwQzU6\nAcMTn332mVSuXFmOPvpoNTjRqVMn9biZnbVjqUkgfwhAEQmC2A0bNqil4PypOWtKAiRAAiRAAiRA\nAiRAAsVPAGNpeKZ89NFH1TPlKaecUvyF4B3zhsBLL70kffv2lRNPPFEef/xxgYdUBhIgARIgARIg\nARIgARIgARIggfgEli9fLl27dpUffvhBFzg0b948fmKeIYEMIfDFF1/oe/vnn3+q/kaTJk0ypGQs\nBgmQAAmQAAmQAAmQAAnkDoFy5crJqFGj5KSTTsqdSrEmJJBFBNavXy+TJk2ScePGyWuvvSZ//fWX\ntGzZUo1R9OzZU2rXrp1FtWFRSYAESIAESIAEMoDA5NIZUAgWgQRIgARIgARIgARyhgCENRMnThR4\n0ITnDAhu4PXliCOOkOnTpwssjT7zzDNy/PHH0/hEzjx1VoQESIAESIAESIAESIAESIAESCAdBDZv\n3iynnnqqKia9+OKLQuMT6aDKPBIR6NWrly48wfsGj70bN25MlJznSIAESIAESIAESIAESIAESCCv\nCXzwwQcCgxOlS5dWRww0PpHXr0NWVb5evXqC93efffaR1q1bCzzDMpAACZAACZAACZAACZAACZAA\nCZBALhHYcccd1fEC5r6xXgGGKPbee28ZOnSo1KlTR5o2bar7ixYtyqVqsy4kQAIkQAIkQAJFSKCU\n8SbmFGH+zJoESIAESIAESIAEcp7AmjVr5NVXX9UFC2+88Yb8/fffqnjTvXt3wV+jRo1yngErSAK5\nROCRRx4ReG+yAfuvv/66nH766THecGFYpl27djYZtyRAAiRAAiRAAiRAAiRAAoUgsGHDBjXWOG3a\nNF0E0LFjx0LkxktJIBqBWbNmSZcuXeSQQw7R969ChQrRMmBqEiABEiABEiABEiABEiABEshxAnC6\n0L9/f3W88Nxzz8n222+f4zVm9XKRAIyfXnDBBYL54FtuuUUGDx6ci9VknUiABEiABEiABEiABEig\nyAm8++67MmnSpJj7PP7449KmTRuBATgbqlatKhdeeKE95JYESKAECGzatElmzpypBilefvll+f77\n79VAY8+ePQV/zZo1K4FS8ZYkQAIkQAIkQAJZQGAyDVBkwVNiEUmABEiABEiABDKPAKx/vvLKKzJh\nwgT17lK+fHnp0KGDGpzo1q2bVKtWLfMKzRKRAAmEIlCjRg1ZvXq1lClTJm56eMU955xz5KGHHoqb\nhidIgARIgARIgARIgARIgARiCdx5551SqVIlGThwYMyJP/74Q3r06CGzZ8+WyZMny6GHHhpzngck\nUBwEPvnkEznqqKNU2QYKc3hXveGZZ56Rr7/+Wq699lpvNPdJgARIgARIgARIgARIgARIIOsJwMHC\n+++/H9fw+k033ST4u/jii2XEiBFSunTprK8zK5DfBO6//3655JJLpG/fvvLYY49JuXLlCgBZvHix\nVKlSRbBgjoEESIAESIAESIAESIAESCCWwJVXXil33HGHlC1bNvaE5wgG4HbccUf5+eefPbHcJQES\nKEkC//zzj8qAxo0bpwYpvvnmG6lZs6Yce+yxaoyiVatWlPuU5APivUmABEiABEggswjQAEVmPQ+W\nhgRIgARIgARIIFMJQBAKb5gwOoG/r776SnbbbTfp2rWrGp2AZ1Z6x8zUp8dykUA0ApgcufvuuwVW\nfxOFN998M64iXqLreI4ESIAESIAESIAESIAE8pHAsmXL1NsNFBpGjRqlXlPB4ZdffpGjjz5avvzy\nS3n99delcePG+YiHdc4QAlhcAhkPZD5Tp06VXXfdVUs2ZswYOeGEE3T/008/lUaNGmVIiVkMEiAB\nEiABEiABEiABEiABEig8gUGDBsnw4cMF3moHDBjgZgjDFDh+8cUX5YEHHpCzzjrLPccdEsh2Ahj3\nH3/88dKwYUMZP368ygJsnT777DNp3ry5HHDAAbowx8ZzSwIkQAIkQAIkQAIkQAIksJXAxx9/LAcf\nfHBCHNtuu62cfvrpMnLkyITpeJIESKDkCMydO1cNUcAgBZxzYp78mGOOUWMU7du3T2hkpuRKzTuT\nAAmQAAmQAAkUEwEaoCgm0LwNCZAACZAACZBAFhJYv369LjaYMGGCemCFFd799ttPDU50795dDjnk\nEFr5zMLnyiKTQDIC8+bNkyZNmiRMtssuu8iaNWvYBiSkxJMkQAIkQAIkQAIkQAIk8B+Bk08+WbCI\nH4beSpUqpfuHH364HHnkkfLjjz/KtGnTZJ999vnvAu6RQAkR+Prrr+WII45QZRq8l/Pnz1dZ0JYt\nW6RMmTLSuXNnNU5aQsXjbUmABEiABEiABEiABEiABEggrQSWLl2qC/Ax5tlmm210fN62bVtZu3at\n9OjRQ2Cob+zYsdKhQ4e03peZkUAmEMD7DacjeP9fffVVNTj5ww8/6Fzx6tWrNX706NECuRYDCZAA\nCZAACZAACZAACZBALIHatWvL8uXLYyN9R++88460atXKF8tDEiCBTCQAGREMUeAPRmYqVaqkY+ae\nPXtKp06d6KgzEx8ay0QCJEACJEACRUuABiiKli9zJwESIAESIAESyDYCK1eu1EUEr7zyisycOVMV\nCiD8hMEJ/NWtWzfbqsTykgAJpEAAv/Wvvvoq8EpY5r7gggvkzjvvDDzPSBIgARIgARIgARIgARIg\ngVgC8JTRqFEjcRzHPYFFLdWqVZPttttOF7fUqlXLPccdEihpAt9995107NhRfvrpJzWQsnnz5pj3\nd/bs2dKsWbOSLibvTwIkQAIkQAIkQAIkQAIkQAKFJoCxD+bFMe4pXbq0VKxYUZ577jk577zz1Agf\nFuXvu+++hb4PMyCBTCUAw6hYTAOvr0899ZTcfvvtutAGvwkEOCZYtmyZ7LDDDplaBZaLBEiABEiA\nBEiABEiABEqEwA033CDDhg1TBwRBBahatarAsBucEzCQAAlkF4EVK1bI+PHj1RjFrFmzpFy5cmqE\nAuNnGHKsXLlydlWIpSUBEiABEiABEkiFAA1QpEKN15AACZAACZAACWQWgV9++UXeeOMN6dOnT0oF\n++STT2TChAlqeGLevHmqOHDUUUepwYkuXbpIlSpVUsqXF5EACWQvgZtvvlmGDBmiynZBteBioyAq\njCMBEiABEiABEiABEiCBYALHHnusepG0ivtIBUUj/L300kvqUTX4SsaSQMkRmDZtmnTu3FmNk3qN\np5QpU0batGmjhlNKrnS8MwmQAAmQAAmQAAmQAAmQAAkUngDmyHv06BGTEcY8FSpUkIYNG8rEiRNl\n5513jjnPAxLIRQKbNm2Ss88+W995GKPcsmWLW038JuCc4K677nLjuEMCJEACJEACJEACJEACJCCy\nZMkS2W+//QJRwMnXJZdcogbeAhMwkgRIIGsIrF27VtdZjBs3TqZPn67lbt++vRpzPOaYYwTGZhhI\ngARIgARIgARykgANUOTkY2WlSIAESIAESCCPCLz//vvSu3dvgWfKhQsXqiJMsupv2LBBZsyYoQYn\noDTz7bffSo0aNdTgRPfu3aVdu3ZStmzZZNnwPAmQQA4T+PLLL6VevXqBNYRn5m+++SbwHCNJgARI\ngARIgARIgARIgARiCcDo40EHHRQb+e8RPKuWL19e3n777bhpAi9kJAkUMYHPPvtMDj30UPnjjz9i\nFp14b4v3tnXr1t4o7pMACZAACZAACZAACZAACZBA1hD4+++/pX79+rJq1Sr5559/YsqNBfctWrTQ\nOXUsGmIggXwgcMcdd8hVV10lXiOUtt6QYS1YsEAaNGhgo7glARIgARIgARIgARIgARIwBBo1aiSY\nVwsKc+fOlcaNGwedYhwJkECWEvj111/V+QiMUUyZMkUgXzrssMPUGAUck0C/moEESIAESIAESCBn\nCEwunTNVYUVIgARIgARIgATyigCUYIYNGyatWrWSNWvWCJRgXnnllbgMfvzxRxk9erQaq9hll13U\ng+UHH3wgp59+usyZM0dWrlwpDz74oBx11FE0PhGXIk+QQP4QqFu3rk5+wCOzN0DJrl+/ft4o7pMA\nCZAACZAACZAACZAACSQgMHjwYB2zByXB2B5GIjt06CCLFi0KSsI4Eih2AsuWLZO2bdsmND6xzTbb\nyKBBg4q9bLwhCZAACZAACZAACZAACZAACaSLwIgRI9TJg9/4BPLfvHmzYC797LPPTtftmA8JZDSB\nCRMmxDU+gYLDAMU555yT0XVg4UiABEiABEiABEiABEigJAicdtppgXPBe++9N41PlMQD4T1JoIgJ\nVKpUSU466SR56aWXZN26dTJ27Fg1OnHTTTdJ7dq1pVmzZnLrrbfKkiVLirgkzJ4ESIAESIAESKA4\nCJQyFpud4rgR70ECJEACJEACJEAC6SLw/fffy4knnqgeUr0KMU2bNlVjEvY+X3zxhRqlgGGKd999\nV7A4oF27dtK9e3fp1q2b7LnnnjYptyRAAiRQgMA999wjl19+eQFvt4sXL5Z99923QHpGkAAJkAAJ\nkAAJkAAJkAAJxBJ477331NtFbGzwUc2aNWX58uXBJxlLAsVIoGHDhqENosCrC4yZMpAACZAACZAA\nCZAACZAACZBANhGAcwYYY9+4cWPSYsNQxWWXXZY0HROQQLYSmD9/vrRo0UJ/D8lUaV944QU57rjj\nsrWqLDcJkAAJkAAJkAAJkAAJpJ3At99+W0AXGw4Fr7/+ernuuuvSfj9mSAIkkJkENm3aJG+++aaM\nGzdOYOQRzkX3228/6dmzp/5hjQcDCZAACZAACZBA1hGYTAMUWffMWGASIAESIAESyG8CU6dOVeMT\nv/32m3pe8dOYOHGizJo1S4UXsJ5ZpUoVOfroo9XoRKdOnWSHHXbwX8JjEiABEggksHr1atljjz3E\nq2iEhUgLFy4MTM9IEiABEiABEiABEiABEiCBWAKtWrWSDz/8MHD8jpQwFLllyxapX7++3HjjjTre\nj82BRyRQ/ATGjx+vSnEY+0FBDp5/gwLe30aNGsm8efOCTjOOBEiABEiABEiABEiABEiABDKWQK9e\nvQTz6lgckCiULl1aKlSoIOvXr5dSpUolSspzJJC1BHr06KH6JckqgN/AbrvtJl999ZVUrFgxWXKe\nJwESIAESIAESIAESIIG8IXDooYfKBx98EKNnCQeCMHzIQAIkkH8E4FwUjkNhjAJz73BEUqtWLTn2\n2GMFMim0GZA5hQ2Yrx8yZIj0799f6tSpE/YypiMBEiABEiABEig8gcnhv9iFvxlzIAESIAESIAES\nIIGUCUD5ZdCgQQIjEr/++mug8j+EEb1795aXXnpJjU7MnDlT1q5dK6NHj5Y+ffrQ+ETK9HkhCeQn\ngerVq0vr1q1dQScWHp122mn5CYO1JgESIAESIAESIAESIIGIBKZPn65KBUGL97fddlvNrW3btgJD\nk0uXLqXxiYh8mbzoCEDxZcGCBTJjxgzp2LGj3si+s967wngKvKS+/PLL3mjukwAJkAAJkAAJkAAJ\nkAAJkEBGE8BYBwsA4hmfsOOfPffcU2666SZZvHgxjU9k9BNl4QpLYNSoUXLvvfdKgwYNNCv7G/Dn\nC6cFP/74owwdOtR/isckQAIkQAIkQAIkQAIkkNcE+vXr544bYbitcePGND6R128EK5/vBLCeA7rX\nd999t3zzzTfy8ccfy0knnSRTpkzR+N13313OOuss1RWJJ5/yMoQs6+abb5YDDjiAc/NeMNwnARIg\nARIggWIgUMoIxp1iuA9vQQIkQAIkQAIkQAIpE/j666/V4uWnn36qnlHjZQSBRVuzeAWLXBhIgARI\nIB0EHn/8cTnzzDMFFnkRVq5cKTVq1EhH1syDBEiABEiABEiABEiABHKawEEHHaSL87FI3wYYdYPS\n0cknnyyXX365q9hvz3NLAplI4PPPP1flGCxIwdjQa1QFsqh69erJokWLXOOFmVgHlokESIAESIAE\nSIAESIAESIAEQADjmYYNG8qXX37pzn0hHmN1/GHhPRw7DBw4UA4//HB3ARHSMJBAPhCAocknnnhC\nnnzySXWMss022xTQUUEcDLNAHsBAAiRAAiRAAiRAAiRAAiQgaqitatWq2ndGf3nEiBFy8cUXEw0J\nkAAJFCCA8TQMo+Lvk08+kcqVK0vXrl2lZ8+e6qR0u+22K3DN2WefLdDlhu4JlsBecsklcvvtt6sc\nq0BiRpAACZAACZAACaSTwGQaoEgnTuZFAiRAAiRAAiSQdgJjxoyRAQMGyIYNG2IU/OPdqGzZsvLL\nL79IkAAi3jWMJwESIIF4BNCe7Lrrrtr+tGzZUt577714SRlPAiRAAiRAAiRAAiRAAiTwL4GJEydK\n9+7d9cguYqlUqZJceOGFcu6558puu+1GViSQdQR++uknefjhh9UYBTyeIlgb788884z07ds36+rE\nApMACZAACZAACZAACZAACeQXgXvvvVcuvfRS1/gEDE7A02SzZs3U8+Txxx8vO+ywQ35BYW1JIIAA\nfhevvvqqLnB57bXX1BiLNbIKA6twjPLGG28EXMkoEiABEiABEiABEiABEshPAp06dZKpU6dq33nV\nqlVSvXr1/ATBWpMACYQmsHz5ctcYBXSzy5cvr0YoYIwCRimgYwIHEdDhxly9DTB007hxY722Zs2a\nNppbEiABEiABEiCB9BOgAYr0M2WOJEACJEACJEAC6SDw119/yQUXXKAT+lHzmzBhgrvQJeq1TE8C\nJEACfgLdunVTBSMsNDrrrLP8p3lMAiRAAiRAAiRAAiRAAiTgIYAF+Y0aNZJFixZpbN26deXKK6+U\nk08+WRUGPEm5SwJZSWDjxo3y/PPPq1cV+57XqlVLPQhjEQoDCZAACZAACZAACZAACZAACWQigXXr\n1kmdOnXkjz/+0OLtvPPO6ggCziD23XffTCwyy0QCGUFg7dq18vTTT8sjjzwin3/+uS6og/zr5Zdf\nlmOOOSYjyshCkAAJkAAJkAAJkAAJkEBJE4CxdswHH3744fLWW2+VdHF4fxIggSwjsGbNGh1njxs3\nTmbMmKFj7/bt28thhx0m1113XYHaYF4ezkqfe+456dKlS4HzjCABEiABEiABEkgLARqgSAtGZkIC\neUpg9913l9WrV+dp7VltEiCBTCUAz6r9+/dPyXBFptaJ5Uo/AQi4IZiCZVQGEiABEkg3gSpVqmg/\nuWzZsunOmvmRAAmQAAnkCAH2R3PkQbIaJJChBIqyPwqDoXvssYf8/PPPGVp7FosE8oMAZKCjR4+W\nk046KT8qzFqSAAmQAAmQQJoINGnSRObNm5em3JgNCZAACYQjAOOcX3zxRbjEEVPBMCLaNhhLZCAB\nEiCB4iQwePBgufXWW4vzlrwXCZAACZBAMRBg/7IYIPMWJEACgQTYvwzEkpeRv/zyi0ycOFFgjALr\n1T755BPZtGlTARaYL4WByEGDBsktt9wi1lnEueeeKyNHjiyQnhEkQAKZQ2CnnXaSVatWqSGZzCkV\nS0ICJBBAYDJdMQVQYRQJkEByAliwi878ZZddJi1atEh+AVOQAAmQQEQC69evl6+//lo2bNhQ4A/K\nE3///bcqUSxYsECNCBxwwAHy+++/6x+8tTCQQCIC33//vQqdxowZkygZz5GASwDeoCpWrOgec4cE\n4hGYP3++CrPxnaIBiniUGE8CJEACJMD+KN+BXCeA8fn222+f69XMyPoVdX8UBihgfOL666+XRo0a\nZSSDkigU3/mSoJ7f94TiFA2E5/c7wNqTAAmQAAmkRuC7776TAQMGSKdOnVLLgFeRQBYTgJ4P5i4q\nVKiQxbXIvqLDEO2oUaOKrODr1q1TvYnHHntMKlWqVGT3YcaxBDZv3iz4K1++fOwJHpFAnhC47bbb\ndKFInlSX1SQBEiCBvCLA/mVePe60V5Y6lmlHmjcZsn+ZN486VEUrV64sp5xyiv7VqFEj0PgEMoLx\nCYQRI0bI22+/LWPHjlVnGljU3rp1a7ngggv0PP+RAAlkFoGFCxfKkCFD5M8//6QBisx6NCwNCQQS\noAGKQCyMJAESCEugZcuW0qtXr7DJmY4ESIAE0k7gjDPOkBUrVsjUqVPTnjczzH0Cffr0yf1KsoYk\nQALFSgDKfbCmzEACJEACJEACYQiwPxqGEtOQAAlEIVBc/dE2bdpI+/btoxSNaUmABNJI4Iorrkhj\nbsyKBEiABEiABPKLQNOmTYXj8fx65qwtCZQkAShSF6UBClu37t27y2677WYPuSUBEiCBIiXwv//9\nr0jzZ+YkQAIkQAIlT4D9y5J/BiwBCeQTAfYv8+lph6/r3LlzQxm+g9HVjz/+WBo2bCgvvPCC3qBm\nzZqUAYdHzZQkUKwE6Gy4WHHzZiRQaAKlC50DMyABEiABEiABEiABEiABEiABEiABEiABEiABEiAB\nEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiABEiCB\nQhAYN26cbLvttqFy2Lx5s6xfv146deokixcvFhilYCABEiABEiABEig8gTKFz4I5kAAJkAAJkAAJ\nkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJ\nkAAJkAAJkAAJkAAJkAAJkAAJkEDqBMaMGSMwLAEjFKVKlSqQkeM4amjCu0WiL774QipXrlwgPSNI\ngARIgARIgASiE6ABiujMeAUJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJ\nkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkAAJkEAaCZx66qmyfPlyKVeu\nXMxf2bJlY47teRt/8803y5577pnGkjArEiABEiABEshfAjRAkb/PnjUnARIgARIgARIgARIgARIg\nARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIgARIg\nARIgARIgARIggYwgcM0116RUjpEjR0qZMlwumxI8XkQCJEACJEACPgKlfcc8JAESIAESIAESIAES\nIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAESIAES\nIAESIAESIAESIAESIAESIAESIAESIAESIAESyDMCNOmUZw+c1SWBkiLw9ttvy6pVq2Juv+2228pu\nu+0m1atXl3r16sWc8x7cddddUr58eTn33HO90WnbL+r8bUFXr14tM2fO1MNSpUpJr169BAy84Z13\n3pFvv/3Wjdpjjz3k8MMPd49/+eUXmTFjhixYsEDWr18vjRo1kkMPPVTq16/vpsHO66+/Lj/++GNM\nXLly5ZRz3bp1ZbvttnPP/f777zJx4kT3ONFOs2bNBPXwP8sDDjhAGjZsKPHyatKkicydOzcm6y5d\nusinn34qK1eujIlv3bq11KhRQ+OmTJkiP//8s+5XqFBBy+2vV8zF/x50795dKlas6J6aN2+eTJgw\nQct30EEHSYcOHWTq1Kly8skna5r3339fvvnmGzd9vB0w3H777QuwDUqPMuAZ2WfuTVOtWjXZZ599\nZPfdd/dG67732e27774Cdt6Ad+C1117zRkmnTp1kp512iokr7oMNGzbIW2+9JWDdqlUrOeSQQ6R0\n6XB2riZNmqSsbJnxTpx//vmCZ85AAiRQ/ATwG/zkk0+0jcbvGN/ogw8+WPDtwjcKv/FEobi+q/g+\n4DvhDSjjCSecoFFBbft+++0njRs39l6S8/v4/h111FHal/JX9rfffpNnn31Wvv76a0H/oG/fvqHb\nXrbdfpo8JgESIAESIAESSBcB9kfTRTIz8knUH4UcacyYMSqTgRyhY8eOBWRl8WrB/mg8MpkXT7lw\nwWcCORpkaPPnz9fxWM2aNQXj1RYtWsi4cePkpJNOCpTvFsxJxC+DjCJ3hmw6rEy0ZcuWkeWcQeX9\n4YcftO5HHHFE0OnAelvZc+AFJRyJ8TRkE5C3H3300TrfEaZIK1askHfffddNunnzZtlhhx2kR48e\nbhx3SIAESIAESIAESp4A+7KxzyDZnHtsatG5ptmzZ8vixYtVJwT9uvbt2wvm3G1Yt26dTJs2zR66\n2z59+rheCtFvQv/Jhlq1aumcVdi+7C677BJZvwE6C9DdSBbq1Kmj8+Lx0mHM27t376Tz5snYBs15\nBd0TbOP13f3pbdm9+gk2TTzdEpz3pqc+Q3bqM2Rq27Zs2TIZOnSoDBkyxNUZsu9kUW03btwoo0eP\nVh2sPffcU+fBoXsDvST8lvwhrM7Wm2++KWvWrIm53Pt7+fXXX2Xy5Mkx59u2bRs47o5J9O9Bqrpb\nxdm2JWMbT78sXn0x/g6rL5ZPulqUSwS9MYwjARIgARIobgLsX/5HPFkf6L+UW/fYv9zKIczYORlb\n9i/9b1dqx+xfpsaNV+UugWzWX8JTqVSpklStWlXXAey4444Z8aCStecZUch/CwG5NnSTDjzwQNVn\nyqSyFaYsbOsLQ4/XkkCeEnAYSIAESCAFAlu2bHFMs+mMHTs21NVmkahz88036zVly5Z1Hn74Yeeh\nhx5yLrvsMscssHdq167tXHPNNY7pUBbIzxg2cIzybYH4dEUUdf62nP/8849jlIqdvfbaSzmcffbZ\n9pS7/emnn5w77rhDz19//fWOmZB0z7344ouOMdbhXHLJJc6HH37ofPnll87jjz/umEGBcvzjjz/c\ntLjuzDPP1HyMEQvlPWzYMOe4445zttlmG6dfv36OWXSq6T/77DNNd8wxxzhmMte57777HDOxqnEo\nC/7OOussxxh0cO655x4Hz/Kmm27S83gHxo8f7/z111/uvY1xDMcYxtDzxniG8/nnnztGsONcddVV\nGof7L1q0SNPjOtwT+ZQpU8ZZuHChA042mElBp127do5Z/OwYBRJn7dq1zoUXXqjpjfEG54knnnDM\nZLD+PfLII86ll17qGGUIvafN43//+59jlHe1XkbQqfyMkonG2TRGgcVBfpdffrljFk5rfVEmM8Hr\n3Hvvvc4NN9zgmMXXTuXKlSOVAb8ToxDjmAGblvn000/XZ4FymoW+ek9jCMMWQ7dghWeP+5tBn7N0\n6dKY8+AzZ84cZ//993caNGjgGIMkMcxiEhfTAd43o6DiPPbYY45REnKuuOIKxxgYcVD/ZMEMzByj\nGK/1RZ3xZxaPJ7ss5vzAgQOdI488MiaOBySQjMDzzz+v716ydPl03iyA0XbQGH3S3/Grr77qGOUY\nB98Po2ijvO68886kSIrzu2oMZbjf1c6dOztGMcktn1HccVBe27Y89dRTjvdb6SbM0R08P2N0SeuP\n/oU/LFmyxDEGkfQbi74ZOO29996OMTTlT1rgOB1td4FMcygC33bwxDvIQAIkQAIkQALxCLA/WpAM\n+6MFmWRzTJj+KGQjZrJWZVTGMJpjFuE7xrhl0mqzP5oYUVH3R42yv/Z3p0+fnrgg/56lXDgWE+S6\nxpiw07x5c5UTvvfee87TTz/tdOvWTcfdkGMiRJGDpip3jiITTUXOGVvzrUe33nqrYxQ0gk5pnLfe\nkCNDLoHvQyaG2267TeXHkN+axYmOMSLiQP4cJkD+aeUV2EI+irYtSjALL53hw4dHuYRpSYAESIAE\nSIAEDAHjIMN54IEHQrFgX/Y/TGHm3G1q9OlOPPFEnX+AjgPm+THWQx/ILMB2Zs2aZZPqPDfmvjHX\njH4R5nqgB+ENxoiZq2sC3QIcR+nLpqLfgP6vMfrg7Lzzzlou6HZYvYQnn3xS55/QpzeGvb1FjdnH\nnBTm16BPkSiEYRulvlHLHkW3BPWgPkN0fQa8M8ZoXaLXoFDnjFMUfU+9+kWJMszUtg3tBdoBY5gh\nUfHTdg6/UYxPjSF/xxjCUf0j6CehDEFz4lF0tiA7gZ4R8sIf2oE///zTLTvG8WgLoVtljPPomBL6\nUkhblLpbUdsHt8CenTBtWxi2UXXVvPKCZPpiqcgwsrFtK2m5BPTCTj31VM/bwV0SIAESIIFcIcD+\nZWpPMkwfyJsz+5dbabB/mTlrAdi/9P5CuZ/tBIwTB8c4fUi5Gtmov2QM3KoOOGQLXbt2dSBzhCz1\nlFNO0TVJxuGtyjtThpKGC6N+K9Nwy5SzgIz6oosuUlnNqFGjUs4n0y4s6bbe8oC+Ed5VyPoZSIAE\nMp7AJMn4IrKAJEACGUkAkzX44Ic1QIFKGAtweg0UMb0BE2sQpGCRvvF06MDogDdgksc7Eec9F28f\nHeawIZX8MbH12muvhb1FTLpbbrlFOYDf//3f/8WcwwF4VKhQIWbxPgwtIP2jjz5aIP3y5cudKlWq\n6KSo9ySUXnGN8bzmjdY8EH/sscdq/Mcff1xgwb+xlq/XGuuq7rW4NzqcCPZZwrhFUICRDNzDrwBr\nvM5rPCYSvQGKJkgPYxX+cNppp8VMMKO8SAvjFkEBRiQwMYvw999/q6GJM844IyYpDGDAuIN3GFPv\nAABAAElEQVQ1woFBpjWKgYRYJIF7XHzxxe51yAsGHxCilAHpO3TooPl99NFHONQAtsgPysVz5861\n0e7WLgbG78X/m0AiDAhhCKSkA9qCVq1aOWBog/HY50AB+sorr7RRcbd4NjOMEQ28x/gz3mtiDJrE\nvdBzggYoPDC4G5oAF/zFooJBoKZNm2rbiO+HP0CQAuNEMCaVLKTyXU2WZ6LzMO6DNhtGcPwBBgBw\nDgt40F7lS7BtKhQ8Uf8gAxRQ4oRhLAT0a9CWIu2AAQOSYkpH2530JlmcoKgX/GUxGhadBEiABEjA\nQ4D9UQ8Ms8v+aCyPbD8K2x9FX94bYDDVeGL0RgXusz8aiMWNLOr+aFQDFCiYlSXmglwY9Ykie0Z6\nG5555hk1wotFapA1+sPVV1+txoNtfFQZZFS5c1SZKMqVipzT1gcyQ2v4GIYl4gVbbxhVzNSAuYHS\npUs7MIxpA+QSWKCI9z1RwALMXr16ufJQtJnff/99oksCz0H+6pe/ByZkJAmQAAmQAAmQQAyBKAYo\ncCH7suHn3MEL43vM/cNYedDcBOby0Y/yGqHAdYnmenAeOhSY68EWIWpf1j7HqPoNUNbG3ElQ/xX1\nS2SAAg40cG08vQbUo6j0GZB3lLKH1S1BvjZQn8GSSL7NNAMUKLH9TRT1OD2qbhUcnkQNUe9h84eB\nRLRH/jEc5E5wpuQNqehsWcbx2h3kj7l3OINAwFjY76ylqHS3orQPWjjPvzBtWxi2qdTXygvitate\nfTEUORUZRra0bZkgl6ABCs8Pg7skQAIkkGMEohqgQPVt34f9S/Yv/T+HdIyd2b/0U03/MfuX6WfK\nHEuWAGSHqRqgyAX9pRdeeCHmAaxatUrnp2Egddy4cTHnivMgTHsetjypyoPC5o90WF8G+S4cYOZC\nyIS23nKkAQpLglsSyAoCk0qbxpCBBEiABIqFgDEwEXgfswBfevfuLcbAgbzxxhtiFM1l48aNbtqK\nFSuK6ey6x8l2zGJ2Mcq6yZK556PmbxawilEkEKMo6uYRZQf1PfPMM6VMmTJy3nnnifF6F3M5zteu\nXVvMRKfGf/vtt2IMIYixfC9mcWhMWhwY75By6aWXilEuF2PQwj1vFDDcfe+OGUzpvZHeWOcT40lO\njEKHN0ng/vHHHy/GQ4ees8/Sbv0X2Hi7tefPPfdc3TWTszZKt7ZexjpcTLxRShbj8USOPPJINz5e\nvWwCsKpRo4YeLlu2TIyRCTHGHuxp3Rohpz6D7777To+NAQVBXKJQrlw56d+/vyaJUgZcEJTeGMCQ\nHj16wBCUGIMXBW5tvIBqvY3nOzEW4zWdN5FRZnafhzc+7D7eYzO4DJs8bjrj1U+MgpCYSXg3Dd4p\ns2hEjPcgMZYK3Xj/jlGslk8//VRQV7zH+DNK6FK+fHl/Uh6TAAkUMQFj1EbMogm54oorBG2iP+y9\n995y3XXXJfxN22uiflftdalu7bfGbr352Ljtt9/e/a56z2fSfrraZdTJtqnoTwQFfFvRHzAedfT0\nrrvuKkOGDFFGxvtu0CVuHNtuFwV3SIAESIAESIAE0kiA/dE0wkwxq+Lsj6KIq1evFmOgNKa0kL1A\nVpUosD+aiE7mnrNjM38Js00ujPJHlT3bOhsFCDn//PMFLEaOHCl43/3hxhtvVLmm/R0EyRS913jl\noIiPKneOKhPFPYLKlEzOiesQJkyYIG3atNFy3nPPPVsjA/7be0C+kO4Amb7xZF3obI2hZmnSpIn+\n2cxOPvlkMUY55fHHH7dRgdu7775bjIcZMYtf3fF71apVA9MykgRIgARIgARIoOQJsC8rEnbOHU/r\n2muvlSVLlgj6tla3wPsUr7/+eqlcubLOuxtlbveU5Wy37ol/d9DXxdwHtghR+7I2X7v9N1t3Y+Pt\n1p6wfVN77N2ifon0UkaPHi1G2V0wn24cUngvdffDso1aX9wgStnjpfXrlrgFNztFrc+Ae6Wj/059\nBu9T+2/f/67bM+kcp6eiW7XLLrvYooTapnIPm7HxDCrGqI0YhzA2SrcY7xnjm25cqjpblrHduhl6\ndtAe4g+hOHW34v3mUY50tG1h2KZS30TlRtn9cpKg9MlkGEXdtqVLBku5BJ44AwmQAAmQQCYRiNfn\nYf9ShP3Lwo+d2b+M/2tn/zI+G54hgVQJ5IL+kr/uu+++uxhnGbLPPvvour3nnnvOn6RYjsO052EK\nUhh5UJj8bRq7ns9ubXxxb9nWFzdx3o8ESMBPgAYo/ER4TAIkUGIEYODg6KOPFuONW2bPnu2WA8q5\nfsMEiIMRg9tvv13Gjh2rSg+4AArAxxxzjBodMFbXZeLEiZrPzz//LA899JDuG8tdeh2MGyAE5Y94\nYzld7rrrLjGW1gSdXQQo/6Kc06ZNE+MFQnAPKMxHDe3bt5c777xT8+vZs6dAed4bYJzCBiziNx7c\nVQnDKlTYc3Z72mmn6S4GPMkClGDRCd20aZMuNG3cuLEcccQRyS5T5WgYzihMMNb6pUKFCgJlC8sf\n+RkvKJqtsQ6nZbP3mDJlirRr104nWm1coi3Sw1gJJgwRMEgynuBk/PjxagzBe+0ll1wiVapU0Sgs\nuA4TjLX8pMn8ZUh0gTWM4WVh0+MdMB5xBYu+X375ZfE/WwxkUhnM4F7GS6M0aNBAzjrrLHu7lLdg\ni7D//vvH5AGDKTA+MXny5Jh478H999+vBlhgdGKvvfYS4/mjgKENb3rukwAJFA0BfIPuuOMObZ8v\nvPDCuDeBYRnjfdQ9D0MFxuK5rFmzRq//6KOP9FzQdxVKhGjT/vzzT1UWwzcZbRu+RwjIw3gK1UUa\nfiUfnMd313hy1W+5V+EH51INMFAEQzxQgsTiEGOJ3c0K3/YHH3xQsCDGLopDHwPH+FuxYoWbNlEf\nw02UYCfd7XKCW7mnYJgCxrS8oXr16vp8gxRCvenYdntpcJ8ESIAESIAESCAdBNgfzb/+KN4byMM+\n+OADefrpp/U1grwKMgYoiicK7I8mopO956LIhWHMFWNRjM3wPsCgMUI8uTDORRm/In2QXBjxie6B\n84kCZHsYP8JAbzxFzG233VbrhQUwyUI8GWQUuXM6ZaKJ5Jy2Lg8//LAMHz5cZdEwyPvll1/aU0W+\nxb0GDBgg9erVK2AQOurNf/jhB50b8MtDYVQXstwxY8bEzRLvAGQQMOaLRUaQl3tlDHEv5AkSIAES\nIAESIIGMJZAPfdmwc+6YG4axLczVY8wXFLAYGOe++OKLyM4SsFjZhnT2ZW2eUbYYl0BRu2HDhoGX\nvfXWWwI9jCuvvFLPY/wSFMKyTWd9k5XdW06/bon3XFHpM+Ae6ey/U5/B+9TC70dp24L0txLpVsWb\nW8VYGONur76YLXHQOD3RPex1ibbWEQ7mwGFkwgboEcEJkA3p1tmy+WLr1fspTt0tbxm8+8nah7Bt\nWxi26a5vPDmJt352P5EMo6jatnTqBFAuYZ8ktyRAAiRAAtlEgP1L9i+D3lf2L2PHBEGM4sWxfxmP\nDONJoHAEikN/Cc5pIf+AHGTSpEm6Xs3qryMOa9Sg0w99Gn+A812sq4PDwenTp/tPJzyGgww4jMY9\n/GvzPv/8c8E6LqyVsrI0ZAZ9fazvwR/WH1kju5ADw6AF4pcvX57wvt6TYeQFNj3WHWDdH9YOwJjT\nqlWr9FQ8eRDWDUIGax06Y42AXQfgddobTy5l7wtjtuCLdYp2Ht+7hi9euXA9ngmY4A+yY5QVAesr\nEAeHHVEC2/ootJiWBEigKAnQAEVR0mXeJEACkQm0aNFCr0HHDYtS0dGCdXGv5whMBMFQRZ8+fbST\nO27cOPXajguxaBLevNFBxmQ9Frajs1ujRg256KKL1AjB4MGD5aqrrpIFCxYE5o984OUdHfpzzjlH\nunTpIgcffLDAYMHff/+t3smQZo899tB7wOBBKgGLfDGRiYFA79691SBEUD6ffvqpRsfzYo6TWDQK\nBWV04GGsIl7AgAHKzpg0PPXUU/WaeGmLIh4KJb169dKFxlAytgGLDaCwCxYYKNiAgQw8x4UJ6GDD\nWAgGNDZgshYDIZy74IIL9N528AFmUb0n2HzjbYPKEC8t3r+XXnpJ4MnvxBNPDEyG9xkLtLfffnu5\n4YYbxMss8IIEkTA4ggEVfhfwtnjssce6St7gPmvWrIR/7777bmDuUA5CAE9vgAc/BAxI44XDDz9c\noCwDjy2Y0O/fv79gYGkXpMe7jvEkQALpJQCBENoIGIIJ8gJi71a2bFn9XuFbg2/jYYcdpoImGLO5\n6aabZNiwYYHfVUwUHHjggdrWYbEJ0n3zzTcCr0mYXELbdNlll8mbb76pCzC87f7GjRs1DkoUXbt2\nVaEbjBYtWrTIFiulLYxdofz4dp533nmCvgUM8+C7g4A2De0Yvv1WiAeDSDCOgTh470KI18cIU75E\n7TK8sSZrl63AUQsS8d/OO+/segnzXoo8O3fu7I0qsM+2uwASRpAACZAACZAACRSSAPuj+dcfxSsD\nI6eQUZxyyimq1A95EQy9xpOR2NeM/VFLIve2YeTCqDU8KmMxEoyVtGzZUo8RHyQXjjp+RT7x5MLx\n7oH4MOHDDz/UZFhgkSj06NFDDewmSpNMBhlW7pzoHlHOhZFzLly4UI0BV6tWTWWTkFPfd999UW6T\nUlqM39HOQJYAZR4onuDdKYw8FF6qUX6/PBQFhCwB7yfk70EBsgAoycDwBNJC2WW//faLkYkHXcc4\nEiABEiABEiCBzCaQ633ZsHPuMOiNflLNmjUTOlKAAwkEqweR2U83uHQwhAfj6fECFqzD+Nyhhx4q\nTZo0USPtfqckuDYs23j3SSU+WdltnmF0S9Kpz4D7FkX/nfoM9olG34Zp2+Lpb8XTrYo3t4qxGuaN\nYVRxzpw5MYWNN06Pd4+YixMcQAaF9grGLZo2baqOdGxyr8FB21alQ2fL5p+p22TtQ9i2LSzbdHFI\nJifx3ieMDCOdbVtR6ARQLuF9otwnARIgARLIJgLsX259Wuxf/vfWsn/5H4uwe+xfhiXFdCSQGoGi\n1F+CQQSsa4KuOto/rG3C+hysFapTp446fYX+PIwUwBFH69atYxwrwGgFHC5C1oj5ZegVQP89SsC1\nWAsAHXWMpRFgtAHrADCnjjVGMMo5cuRIPQddc8gvscYHxhVwPQLWP0F2iPUBkK2EDWHlBTCKC8cS\nWKeHdX8oK3T+YfwhnjyoW7duuh4B6xkQsB4C6+WwBuvee+/VuHhyKavzf80116h8CGsaMJ8PQxQI\n1gBFonIhHfRXRowYobzQ78GaRoTmzZurQQs8tzCBbX0YSkxDAiRQrASMEhQDCZAACUQmYBaIQ4PS\nGTt2bOhrjWEEvcZ0nOJeY4xJaBqz+NFNYzxgOFWrVnWPTYfaadOmjXtsJlacZ5991j02nWnHGJ5w\nj7FjFrlqvsgfwSib6hb//PkbowCOMS7hnrdpmjVrpnHz5s3TvIynspg0YQ+MkQTHeIHX5KYD7JgO\npeZ39tlnu1kYIxruvumU63mjpOzGBe0YRQ1NZzz66WlbzkaNGjnGs5xjFGsdswDYOeKIIxzjhc0x\ni3qDstE41BXP10wWB6axz9IYRnCOOeaYAn9mAYFebxYOFLjeTFjqOdPJ13PGipxjBiPO1KlTNd4Y\nRnDjvRxsRkuXLtV0xkOcYyaf9Q/vg1HY1Xhjac4mdbdmQbFjPK3oeTOYcB577DH3XNCOMfSgacEs\nKEQtA95J8DTGFhwzqHGM8RTHDBQd4/HEMQrJQbdwvHXHO2kGLloH3BsBbM3gM/BabyTesYceesjB\ne4TnZQZhzrp167xJnLvuukvLhzLG+zOLtGOusQdmIt4x3mbsobs1lvo0LzOwdeMS7eB9NYrgeo1Z\nnJ4oaYFzAwcOdIzhigLxjCCBRATQDuN3xeA4xlKq/vZsuxyGiVHW0mvQBhjBjmM827hti/+7ivxs\nO/Piiy+62aM9QpuDNs4GI7xxjMDFQT8DwQhiHCP80X38MwYS9JqjjjrKjTMGITQO366gbxLuYRaF\nuOmNRVFtb66//no3Djt9+/Z1jGDNMQqSGm8Wx2i+xkCGm+6VV17ROHyzbEjUx7BpvNsw7bLxhqv3\nidcmI94sWPFmG7hvjG5pPj/99FPgeW+kEQQ6xmCXY4Sc3uiE+4VpuxNmnOUnbZ8G/SUGEiABEiAB\nEohHgP3R/8iwP7qVRT72RzGO2HvvvbXPaiZiHbMY578XI8Qe+6PBkIq6P2q8XOgzMwoGwQUIiLWy\nxMLKhY0Sg2MMyjpGucK9izG26+4HyYWjjF+TyYVxo6B7uAWIs4NyQy6HsZxZSBMnVcHoqDLIqHJn\n/x2TyUSRPhU5J64zRmccjDsRMOaHLBtMguTPtt7G4IymT+WfWVDiGKUQxyjEOGhfjCfUmGysnCLR\nuDuePNTKBozCSUyeODCGs/U5++WvBRKaCKM44hjD21pGY5jDgZw8SgBDyP0ZSIAESIAESIAEohHA\nnHKYOVaba773ZS0HbJPNuRvPedoX8up6eK+3+0888YSm887v2rkeY6DLJiuw9c6f+08m68va5xhV\nv8EoRWtZoc9gdROwj/nxAQMG+Iuhx9BX6Nixo3sOeiXod5pF9G6cfycZW3/6ZPVF+ihlT0W3xPs8\nCqPPgLIWZf89E/QZnnzySccozKOqRRJmzpyp79iaNWtC529/E4UdpyfS37LvlV+3Kt7cqlmIp/Uw\nixzceiQbp8e7h5tBkh0w69Spk94Xv1P8djEf7Q2p6myFYWw8caruj/d+3v2i0t2K0j7Y8kRt28Kw\ntXnbbbL6WnlBWH2xVGQY6WrbilInIFPkEsZpiWMW89jHxy0JkAAJkEAOEWD/Uhx/Hzbs4w3TB2L/\ncitN9i/TvxYgVZ1T9i/D/sKZLpsIdO/eXdePRS1zcegvYU2TcY7s/Pnnn1o84xjRwby0MVjgxhmH\nvKrPbnUhoNdtnEw6xgCCW6XTTz9d5RnGmIQbF1bGChmIXZtmnEU73vU+GEtjztsbIF/D3DTmt20w\njp4d4wzSHobehvlWGufGOodudYis/AfrkxDssf97bZxCqx68tzAoO/QFbIgnl5o8ebLKfCHPscEY\nrFDGdq1isnLhOtumeterGecYDsqWLOSDLMEygL4R3kPjoNRGcUsCJJC5BCaVMT9YBhIgARLIGAKw\nCoYAq2g2WMtf9hjeymAtDRbe7r77brX4tvvuu9vTurVWxmykPW8WpmoU8rDBnz88kMGzuzcYQxti\nFGO9Ua4ls5jIiAe4tzGKIWYSTeAVHlszGIjJxXqjh8W2RMGeNwKEmGTly5dXC3BGAVmtv5kOsFrO\ni0mU4gE81uEZ+AMs4ZmJP3+0HsNjgTHwoV7dVq9erVb6jEEGMYYxxAxMxChLiFmAIOPHjxd4v4wX\nzKSfWtKz502HW9q2bWsPY7awyGcmigXe/8ziZznjjDPEDEDUs6b/XYm5MMlBlDIgK9Qbnl9QBjzn\n2267Lckdtp42i7kFFvXMIFKtFVqPiYkuBo9HH31UzEBYzMBUrSTCIiEsEfoDLCgaAyj+6FDHRkkn\nMJ39veAdCROMcRT1ZAHvp88995xaKwxzHdOQAAkUnkCZMluHBPZ3GyZH+13F99Io2cmuu+7qXub/\nruKEEZjpea+3GPzeEfD7twHfZ2MgQj2RGmMIYhaE6LfRa6UV1xmDCvYSd9uvX78C32+chDVYbzCL\nTtSD0iGHHOKNFmPUQvCNNAIpufPOO2POJTqwLIL6GN7rorTLQV6wvHlh3wgc/VEpH+PZG4McYgRf\nEq9dD8qcbXcQFcaRAAmQAAmQAAlEJcD+6FZi+dgfRd/bGBXVP7NQSeAB4O233w7tIYH90ai/tsxO\nH0YuDDkexoTwigq5F8Zh8BLiDX5Znx2zhRm/FpVcGGXC2Bkhytjb1iuqDBLXhZE72/xT2UaRc8Ij\nrlECUVks7gUvKUYhReV/xuijwINIugLuAxkqZO7wMPLaa6+JWdhYIPt0yEP97xpugucL9vCWmizg\n+4d3DvJTyK2NYRUxxpmTXcbzJEACJEACJEACGUggl/uyXtzJ5twLq9fgvVdR7aei34CyYN6oXbt2\nbrHgmXDixInusXcHeh/GAJsbBc9+xlGF6oMYA2QC/Q1/SMbWnz7KcZSyp6pbkoo+A+pQnP13PzM7\nNqM+g5/Mf8dh2rZ06m8FzTEX1Tjd1tIYJdJxozEWrOMy41BHvXli27hxY03Gtm0rrahtWxi29jlE\n3UaVk0SRYXjLkkrbVhw6AXY+n3IJ79PiPgmQAAmQQDYQYP+S/Uvve8r+ZQ9J91qAVHVO2b/0vpnc\nz3cCxaG/hLVexlGLGGOlihtyB+g01KtXz42rUKGCGIfM8vXXX2sarK3BWrFBgwa5jwi/eeRjnOGK\nXx/eTRSw4/8eG8NT7tq9RYsWiTHMqWuPvJfivsb5g2BNHbbGEIXeF+PzqCGMvADyVGM4QowTa8E4\nG2sHEYzzETHGO9xbBo2L3ZNxdqz+iF/n3zjQlYMOOki8a/GMo2nNxd4nTLm6du0qxuCrrn/AejFc\ni7UJxoBjnBKJ1jHsui+29XEx8gQJkEAREihdhHkzaxIgARKITOCTTz7Ra6BwHi/AgAEUi9ERQ6fZ\neMhQpU5vetvJs3FQakWwWxvv32KSGQYCateuHXMK+dkBhT3hv4eNj7rFRJex2i/G67pgga1foNCw\nYUPN8ttvv42bNRbrGq9qmodd0GsTo5OODvLo0aMFAwbsG29q9nShtlj8WqdOnQJ/iRRs8QxgPGTz\n5s1iPHmIsQwnxpKcPpv+/fvrgATxKC/ShQ1QhoDCBgZcQQGKA2PGjBFMHCOtsSon7733XlDSlOOS\nleHQQw8V48FADjvsMF3gbLzrhL6X8agn3bp1k8WLF+sAxBi3SngtBoM33HCDrFq1Sg1uXHXVVYHG\nJ5AJ3m0MYpP9Bd0Qg1v8bvAOeoOxtKiHDRo08EYn3Mezw/uJwSEDCZBA8RGw35kovz37PbULaFIp\nbZASkTWqYKy3ChaoGKufMnDgQG070X7ib8mSJWpEyH9PfO+Cvkn+dBCQIVjBuT3funVr3UU7GyVY\nFnYb79oo7XKy9hjn/f2SePcNE49+FYwUGa9dYZLHpGHbHYODByRAAiRAAiRAAikQYH90K7R8649C\nnmc82+qCdBiiwB9kGF7jc2FeJ/ZHw1DKjjRh5MKoCeRpmPQ3njfUoC3Gjt7gl9nasVqy8WtRy4Wt\njCzK2NtbL+9+MhmkTZtM7mzTpbKNIueEgRkYIrYGZ7CFgV4E4y03JaMc8coMGShk7TB0PHz48EDj\nE7i2sPJQ5AHZhT9AJlq/fn3X4Ij/fNAxDKrgPU3HuxGUP+NIgARIgARIgASKnkCu92W9BBPNudvx\nfSK9BuQFJWYEr4IydCUQrFEAPfD98/f1fadDHaai3xCUsfGiKHYc7z2POXOMb+HEw/Z/O3XqpP1D\n6HM888wz3uQx+4nYxiQs5EG8siPbwuiWRNVnwP2Kq/9OfQbQjh7CtG25or+FxROYQ4bjHON5UY3G\nWGJh2rYgnS20N2i3ErVrGzduVD0ve69Ut5nctiVim2p9/dclk5NEkWH4847athWHTgD0tBAol/A/\nLR6TAAmQAAlkOgH2L7c+IfYvRfXNUx07s38Zfy1Aqjqn7F9meuvJ8hUnAdtGR5m3DauPkKge8fTp\n7bgP69uqV68eo0sPp78wPhFlvRV0K5YtWyYwegEjCQjQKYBjXzhMgP481uf9888/McXt3bu37LXX\nXq5zx8mTJwtkjIUJidpzMIXxCThWhCNLW1Z/uVKRF9vnZbe2DvPnz5dGjRrZQ9368w9TLlwDY8Rg\nCU4I06ZNk86dO+t+0D/KEoKoMI4ESCCTCGx1d5xJJWJZSIAE8pYAFtS/8847OvnesWPHuBzQcbPK\no+eff74MGDBA1q5dK1deeaV7jb+z555IsoMyoGMKbxWDBw9OmDrVewRliskuKNueddZZAgvqEALY\n0LZtWzWcgE4tDDUEBQwqUHZYWYu3IBVe/q655hr1AIcOOzq0yRSvg+6Vjjh48Lj99tt1QADl65o1\na2q2MECByTsoZGARMQYqUYIdyGBwhIXFI0eOlHPPPTemnlDonT59uhqgGD9+vBqDiHKPZGn9ZfA/\nD0z8whAGFvlecsklgoGq11tKvPzxvj399NPqDRQeVZYuXZpwUQYUWb755ht9r8AThj7gTRC/Geuh\nwd5r9uzZOrCxx0FbvCteq4k2jR3QQVGobt26Nlon5XFglevdE0l24CEDStoMJEACxUcAFjvRZkKo\n9NVXX6nwqDjunug7inNWuLNgwQI1wJOuMlWpUkWzev/992OUA7E4BW10IiNKhSlDlHYZAjO/YR//\nvaG4iP5DYQOspuKbZL9fqeTHtjsVaryGBEiABEiABEjAEmB/dCuJfOuPQk6BCVYrN4F87+OPP9aF\nOpDrVK5c2b4iSbfsjyZFlPEJwsqFURF4IIWSIhYqPfLII+r5AuNGO9ZLNNZMBKKo5cKQ8WIcCi+q\nffv2TVSUUOfsGM7KQe1vyX9xIrmzP23U4zByTsjaYWwYC3n8hiChqAJjEZDRYj9KwHxApUqVChim\nnjJlis4xQMYMI8CYZ7jpppukZcuWMdkXRh4KRbyKFSu6Cye9GWOhUlTjjrvuuqu+v5SJeklynwRI\ngARIgASyh0A+9GWhxxBmzh1e+qCwvGLFCnWIEW++ZeHChfqAvXMcBx54oMZhnioowLlFkCJ2UNri\niMMc1mmnnaa3gmEJ9OkQ4AzjnHPOUUcRGvHvP9R5//33l3vuuUfg+c6GsGxt+nRs45Xdm3cquiVR\n9Rlwv+Lov1Ofwftkw++HbduyVX8LHkQ//fRTdZBiqeyyyy4CA4rQVYLiv5VPpaqzBb0vtIvLly9X\nBz1B4/affvpJ09gylPQ2XvsQpW2Lwjad9U0mJwkjwwgqT9S2rTh0AiiXCHpSjCMBEiABEsh0Auxf\nsn+Z6tiZ/cvwawFS1Tll/zLTW1CWrzgJZJr+ktV9wDoerB3atGmT6rmnyuTtt9/WS4866ihXR/+6\n666Tt956S6ZOnapr2DB/7w+4P9YhwaEM8oCziXvvvdefLOFxlPYcaSGPgdPKrl27yueffx6Yt+UT\neDJCJGTPf/75ZwFH0jYLe5+w5cKaP3C98847pbZxjI31YkFyIZs/ZQmWBLckQAKZSqB0phaM5SIB\nEsg/AliMP2fOHDUuYRUMgijA6iUUV6E8OnfuXOnQoYMusrdp0cFLZEHepgvaomOHCegPPvhAF+J6\n08AbxV9//aUW6hGf6j3Q8Q9aVHrmmWfK2Wefrd7ef/31V/fWiMdgBgtEvfFuArMDgxzwCoJOtg0Q\n2PkDlG3B7fXXX48x2OFPF3StN01hz6MTDQULKArDGIUNMEQBjwLweH/cccfZ6MhbWPJDGTGRi/fF\nH6yBE1jBDwrJ6hd0jT/OlgHx/vx23313VT5BPOoJQxHegHgMYvwB3h1hfALK1bCKlywg3bXXXqsc\nYEnPGvYYNmyY/P777+7lGJSNHTs24V/QYBIZQEEGyj7vvvuumx928FvGgoCoitNQOD/mmGNi8uIB\nCZBA0RLYeeeddTEGvmtBhma8d583b573sEj30eZBwQfGhPD99QYY5IECI4K/jfWmCzrXokULTWIF\naTY9lP/wjbaLUqyw5++//7ZJCr0N2y6jrU/WLi9ZsqTQ5UGbC0annnpqTF4QJkYJbLuj0GJaEiAB\nEiABEiABPwH2R7cSybf+KJT8ocjvDZAHwPPjmjVrvNFJ99kfTYoo4xOElQtDpjp69Gg1rgo56KRJ\nk2T16tUybtw4rWNRy4Vxk1TvAWPHkAnCGAMMDccLkBP+/PPP8U4XiPfKIKPKnf2ZBY2hk6VJJuec\nMGGCGk32G59AvvCigoBFeFHDGWecEWN02Hs9PFHD0Md7772nihxY2AglGhgAsaEw8lDIQiETxRyC\n18vK+vXrBd5wosq1Z82apfm0atXKFo9bEiABEiABEiCBLCKQD33ZsHPumFd54IEHdFx33333BT5F\nzHGjHw+HGdDzsMHO3WCsGBTQl7Npgs4n68sW9nzQPRH35ptvxugjQPEaBhb9Ad7z4JQCY394vLMh\nLFub3m6T1cemS7T1lj0ov0S6JUifDn0GlK+o++/UZ0j0FsQ/F7ZtS6S/ZZXzU9WtKkr9LRibQB39\nultYeLXPPvsoGGv0JlWdLWSCdgv3iLdQ4sMPP5SDDz447oMI+m16Exf2vDcv7763fUB8lLYtClvv\nPbGfrD7+9EHHXjmJP79kMgykT0fbVtQ6AZRLBD15xpEACZAACWQ6AfYvxTWqyP4l+5dFtRYgVZ1T\n9i8zvQVl+YqTQKbqL2Ft3R9//CEPP/xwDA7o3Dz00EMxcfEOMI89cOBA1cu3+cCgwtChQwVjaetA\n2Tv/7c0LjoZhhPfGG29UnQmwihKiyAtwD+g+wPgEgr9M8WROkCWlovNvZVBwCp1IXylZuSwPrOu7\n+OKLZcaMGYI1XGCXLFCWkIwQz5MACZQkARqgKEn6vDcJ5BkBu8jev4gU8bCGBiWECy64QCf5vGgw\nGQfDC7AshoDOLxRIESpUqCA9evQQdEhtqF69unz//feuJ3d0tvGH8OOPP9pk7taf/w033KCTWlAA\ngELwa6+9pt4rMNGEjjXyR4CSA+LiKUG4N/DtfPvtt2JZ+E4pA7+iKSzGPfHEE6pYfZrxomHrYq/F\nhC6MA8BC2gEHHGCjXSV+771grf7ZZ58VTJoiPbxNBgW7ACCewQt7HnUJmiy213nv7b8PlErA0+/d\nrl+/fjoo6dWrl/8SPYYSBoItgx78+w/vFgSVGFTAen3dunXl6quvLmAcAdb58e7AulxQsHnbevjT\nRCkDrrX5eXng/brlllsEXvGwwOK3335zbwPF+VWrVgUOgDDZDWMoeJZhAxS8r7zySsH9wQO/NVjT\nu/322zULcIDBiER/mPgOCtWqVZPzzz9fjaDYyVsM3CZOnKjKNt5yQqEG9YbyNybYMbCCERkbMGjD\n+w2jGQwkQALFSwCLPrBAAot2sIjD/61Gu4fJD9tW2W8R2jB/8H9Xcd5eh3M2WEM48Oxig83XCoAg\neMG3pn379uppBm0GvtNon2G0CMG2sbZttnlha9txWNC2eUMQh28NDFBYIxZIiwUf8EKDeiLAgA7a\nSnwzkDcMPsBqKwLKYQVaNt+gPoYmDviXrF1G2RK1yTgXpMDov5VdtGR5es9DwRHfAQjpoBCKPygP\nnXXWWTF9GxglgdARgW23lyD3SYAESIAESIAE0kmA/dH8649CngfDEbZfjfcJi7kh20K/3Ab2Ry2J\n7N5amZh/rIn4KHJhyJ6gDGFlUEceeaTKha1sOJFcOMz4NZlcGE8h6B5hns4OO+ygxjOqVKkiRx99\ntI5JvddhvIwx54gRI6RixYp6yo5z7bjXm94vB8W5qHJnb37Yt/exY2n/eW8a+0wRF0/Oied06623\nyrHHHhuUlRx++OFSo0YNld16jdvaesMgjT9gIQi+GVACwV+iAAOTkydPltmzZwsMER922GEC7yGQ\nQRZGHop7XnrppWooxGu094UXXtC5ip49e7rF8spDEYnni3fYLmix7zSMT9v32L2YOyRAAiRAAiRA\nAhlBwPZ78rkvG2XOHWM99NegiwCved4AHQ4o22L+xa8Yvddee2k/GYslXnnlFe9l2s/F/DHyjReS\n9WXt+aj6DbZvaq/33v+jjz7S+Sbr/ALz49BRgC5GUOjbt69G2zl6HERh683TlidR3z1K2W1+9n3H\nvRLplqRbnwH3K6r+O/UZQLdgsM+6sG1bIv2teLpV8eZW7Tyyd/yebJwe7x4FaxwbgzE6xmWYF7X3\nRYoFCxbIokWL1JGOXXiRqs4W8oMBFOQD2YefNdoCOHXZbbfdkDQw2N9mvN+6PZ9JbVsUtv5K2/rE\nq2+idi1ITmLzs+877hdPhoFz6W7bilInIKxcAvXyylcplwARBhIgARIggaIgYL+3/j4P4qPMA7F/\nKap3HbQmAM+N/cv/dE+D+u7+d9v2B9m//G99QDydU/Yv/W8Pj/OZQFHqL2FuGHIRrywCrKFP79Wl\nRxzSWd3v448/XmWOl19+ua7ZgZHfMWPGqL671xlw0PcYa/CwNgC6FTA4AwcS1niE1eOHnjycLbzz\nzjuqxwDdc5yzuv8oD+QbWDMEowonnngioiKFKPIC1B1jdMz1Q05kZclwcoy2PZ48CHVEeqy9Qx7Y\nQrd/2bJlrhMQxCP4df6x1goB6xnxfKDLhPl/BKwvQPpk5dLE//6DzAlGJVAeOG8OGyhLCEuK6UiA\nBIqVgPmAMZAACZBAZALG6IBjGivHeOcOda1REnDatm2r1+A6M3nsmIl4p0uXLo5ZfO9cdtlljlEE\njcnLTPY5ZqG8Yzq4ep2ZEHGMRTHn+uuvd/bdd1/n/vvvd4wxBcd08p1PPvnEvdZ0ah2jfOpUrlxZ\nr/+///s/Z4899tA8zOJaxyyk17Tx8sfJxx57TK9HWY2lSccohbr5Y8d449D8zMSUYya4Ys7FOzAT\nfo5Z/O8YwwdaJ+P1zjHCtgLJjeKFYyYZC8SbjrxjDFA4TZo0cczCfWfIkCGO6SQ7xmK+Y5QbYtIb\n4ZNjPLtpGY0xBscI8ByzcNZNYxT6HWNZzTFKA5qX6djqObC56KKL9DrU3ShDO88995x7HXamTJmi\nzw3n8WeUdR2zEFbTmEGGc8cddzhmglTPGevxWk4zcInJAwdfffWVYwZDBeLNYEXfjQInTIQxvOA0\nb97cLd9BBx3kmEXJ+m6ZBcWOGRTpOeM1Ty9//fXXHeMtwDFeM5w+ffo4RjFFeRmlFmf69OkFbmGU\nmvW9atCggeZjOv2OseqnZbWJo5TBGJFwrrvuOmUNVmYRhWMGQDYrxwxMHKOEo/fCOTOgc4yiuWOU\nrzUOvxHjWcBN790xxiscs1jYGxV6H+8dfltmYXXoaxIlRD3MoMsxVgY1X7zbxnhLgUvM4FTrhd8u\n3hnwBRf8jnC9mWB38LuMGszCaP0tRL2O6fObAN5HtI8MsQSMJ1nHGHZwqlat6nTv3t0xAmcHbSa+\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GvI/4M8oT7mVLlixxqlWr5tSrV88xiyb0/N577+2sXr3aTfPUU0/FXG/zwbZbt26a7p9/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ZSUoz0f9XoOGbkm/1vCyzlbPM97vJ7P6NpF/Q/pnY96dYrm+agXS6lHqnt430U6347mfolUJ6+e\n4bpH+unH89FoBKDgmjrSno/+65H+Drx8djPTH+ilBZHqFF6HAudEGnjg5XvF6/bC2430c9++fSkr\nVqxIt/8m0vvDr2fl71zvLUsAijAhPxFAAAEEEMiUQCwDUGR0nqvzLZ2zhIv6sXU+4aXoPCZc0rsX\nHq97R6pHemMbvJxThtvh5aeXvn4v6/FyPZuZukfrPNBL3aN9Dutlm9FYJt719vpZ8XJtkdXz84zc\ngh6AIqPvtvC97XD79ffmpSTifXEv16VebLx+H3n9O4vUl6U6ea17RmO2vLQtvIzXuoeXP5qfXseS\neTGI9vEkWp5efGLx3cYEQS/yLIMAAggEUyDeASgyOt/kWvrQz1Ckczsv55JeltFWo33uc2hLsvbI\na90jnW9mZtyj1+vNSC3y4hlpHXrdi4G25WUuiNdz5VjPAQi3m/PLsAQ/oyFwNAEoOC5FHq/v9XtG\n+9LL9Xak722v2/PyHem1TtH63vb6Xev1cx/Jyut6tFxGfaWZmeeWleMEASgys6dYFoFsF/jwmFDE\nGAoCCCDga4F8+fKlW7/jjz/+kNdCWUMOeZzeg2LFih18KZRd++DvqX8JZSCwUAbt1E/F9PfQQIWY\nrj+88qJFi4Z/PeKn/CpXrnzE82k9EYoua82bN0/rpYPPhTKaW/Xq1Q8+TuuXQoUKpfV0ms9lVPfQ\nYCHTv0hFzl999ZWFssNFWvSoX4/UtlNPPdX0z0uJZ729fA68LBNuV+hiLvwrPxFIGIFYHJt0PAof\nk3Lnzp2uVWiCQbqvxeKFWB6f2rZt66nKOXPmtOLFi0dc1suxKeJKPC4Q6Ts+9WpKliyZ+uERv3s5\nXsbzOBCuYK5cudJ197rvtK547hdtL0eOHFaqVCn9mm7xuv84hqVLyAsIIIAAAtkswPlo5B3g9Rwy\n8pr+t4SXc7Z4nvd4PZ/RZyWjvgevTtE8H/ViKfVIdQ/vu0jn29HcL5Hq5NUzXPdIPxP1fJTvsEh7\nPvqvR/o78PLZzUx/oJcWRKpTeB3ly5cP/5ruTy/fK163l+5GDnvh2GOPtdDky8OezfzDRP07z7wE\n70AAAQQQQCD4Ahmd5+p8S+cs4aJ+bJ1PeClexjb44d6Rl3NKL+0NL+Olrz+8bEY/vVzPZqbu0ToP\nzKjO4deifQ4bXm+sf8a73l4/K16uLTg/P/LTkdF3W1bHbCXifXEv16VH6h75jNfvI69/Z5H6slQD\nr3XPaMzWkS1J/xmvdU9/Dd5f8TqWzItBtI8n0fL0osF3mxcllkEAAQQQyC6BjM43uZY+dK9EOrfz\nci7pZRltNdrnPoe2JGuPvNY90vlmZsY9er3ejNQiL56R1qHXvRh4vZ/n9VyZc0kve4ZlEkmA41Lk\n8fpev2f0ufByvR3pe9vr9rx8R3qtU7S+t71+13r9G4pk5XU9Wi6jvtLMzHPjOJEZdZZFIJgCBKAI\n5n6j1gggkGACBQoUsA8++MA0eUA3aPv27XtwErIfmxrKYmAFCxa0Ro0a+bF6GdZp7ty59uCDD9ox\nxwTrEBjEej/99NMWyshqb7zxhp1wwgluQnCGO4cXEUDAVwIKgqG/3e7du1v9+vWtVq1aEQMPZWcD\ngnxs8uIWxOOA2hXE/bJo0SL7+OOPbd26da7+4cAwXvYTyyCAAAIIIIBA9AQ4H42eZTTWxPloNBS9\nrYPzUW9Ofl/KT99hfrwui3ed4r29SJ9P/s4jCfE6AggggAACCPhZIGhjG7ieje+nyW+Ct09VAABA\nAElEQVTn3l5az/m5F6XEXsZP1/BepIP4dxZuV5DrHrTjCd9t4U8dPxFAAAEEEPCHANfS8dkPfj3f\nDNq5pPYWcwDi85llKwhkl4Bfjkt8b3v/BPjNiuOE933HkggEXSBHSqgEvRHUHwEE4i/wzz//mLJi\nv/nmm9ahQ4f4V4AtIoAAAv9foEePHm6S8JQpUzBBwLPAxIkTrXPnzqbjGQUBBBCIpsDUqVOtZcuW\ntmPHDhfEJZrrZl0IIIAAAokjwPlo4uxLWoKA3wRifT66detWO/HEE2369OnWpEkTvzWf+iCQNALl\nypWz3r172+233540baahCCCAAAIIREOgePHiNnDgQLvpppuisTrWgQACCEQUGD9+vPXq1cv27NkT\ncdmsLDBr1iyXPOa3334zZVWkIIAAAvEQaN26tesj1HccBQEEEEAgsQQ4v0ys/UlrEAiKAOeXQdlT\nwajnpZde6pICT5gwIRgVppYIJJnAjBkzrGnTpvb777+7voUkaz7NRSBoApNzBq3G1BcBBBBAAAEE\nEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBA\nAAEEEEAAAQQQQAABBBBAILoCBKCIridrQwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAAB\nBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBAInQACKwO0yKowA\nAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAII\nIIAAAggggAACCCCAAAIIIIAAAghEV4AAFNH1ZG0IIIAAAggggAACCCCAAAIIIIAAAggggAACCCCA\nAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBA4ASOCVyN\nqTACCPhK4LHHHrOJEyf6qk6Zrcwff/xhe/futWLFimX2rSyPAAI+EJg3b55VrlzZBzWhCkETSElJ\nscsvvzxo1fZtff/55x/buXOnFSpUyLd1TOSK7dmzx/LkyWO5cuVK5GYGom2//vprIOpJJRFAAAEE\nsl8gKOej+/btsy1btljJkiWzH40aIIBARIF4nY/ed9999tRTT0WsDwsgkAgC+/fvt+3bt/vqHsLm\nzZsTgZY2IIAAAgggkC0Czz77rM2aNStbth3Ljeo+zcaNG61UqVKx3AzrRgCBTAqsWbMmk+/I2uLd\nu3e34447Lmtv5l0IIBBzgU2bNtnxxx9vefPmjfm24rGB7777zpo3bx6PTbENBBBAAIFsEuD8Mpvg\n09nsrl273LlEOi/zdAwE/v77bze/ROdwlNgLcH4Ze+Nk28Jnn33GHIFk2+m017OA7iOcfPLJljNn\nTs/vieaC6iOhIIBAcARyDQ6V4FSXmiKAgF8EcuTIYdu2bcu2E45oOGiA5vfff2/z58+33bt3W7ly\n5aKxWtaRCQENiJ8xY4YLHqDPFAWBrAhoElT79u2tRo0aWXk770lSgXz58pkuXjXpj3L0AjqOfv75\n57Z69WqrVKmS8Z1+9KaZWYM+xxos+8svv1jp0qXxzwxeDJYtUKCAnX/++dauXTv2RQx8WSUCCCCQ\nKAJBOB9Vv8+iRYvsm2++cefOCvzHeV72fQLXrVtnX3zxBQEYs28XBGbLsT4fPfbYY019egS/C8xH\n4oiKTpkyxfXrFy5c+IjXeCJtgbVr19pXX33lglAo8KYCQGZ3qVq1ql155ZUEiMruHcH2EUAAAQQC\nJ6DkFArUkEjlwIED9tNPP9nXX39tmuiue6dMQo/fHtYECZ0vEvgjfuZB25KuIVq2bBmzidr58+d3\nwWfotwvaJyO+9V2yZIktXryYsXHxZT9ka19++aX98MMPpnMR9d8F/VhdpkwZN5mrWrVqh7STBwgg\ngAACwRfg/NJ/+3DBggX27bffWoUKFeyYY8g/HK89pHNouRcsWJDgH3FA5/wyDshJtAn1/+rai5I4\nAh988IFprN0JJ5yQOI3KppZozsfMmTPdvQSN+1HfZbz7FXW+ed5551mHDh0CPSc1m3Yhm0Ug3gIr\ncoQmKzHrLt7sbA8BBLJNQFk7X3vtNXviiSdc8IkGDRrYLbfc4iavM2g6/rvl3XfftbZt25r2iwav\nUxBAAAEEgiegTp2uXbu6gXVvvPGGaQIEJf4C8+bNs6ZNm1rjxo3tzTff5GZT/HcBW0QAAQQQQCAh\nBJTFY9KkSTZq1CgX7OD000+3Pn362FVXXZUwmdmCuqNefPFFu+GGG1yWlaC2gXojgIA/BE466SRT\nbPobb7zRHxUKSC0UuKN///4uONN1111nQ4YMsRIlSgSk9lQTAQQQQAABBBJRQNlPx44da48//rjt\n2LHDrr/+euvXr5+VLVs2EZvr2zbdddddNnnyZNOEIAoCCCDgV4Fu3bq5IMMfffSRX6uY8PX666+/\n7OWXX7bhw4ebJjO2atXKHbd1f5+CAAIIIIAAAgikJ9C3b1978skn7aWXXrLOnTuntxjPx0BAcxt6\n9epl48ePtwceeMB0/U9BAAEEEMgeASWIeO6551yChuypQWJtdf369fbQQw/Zs88+axo/omOc7i8w\npy+x9jOtQSBKApNzRmlFrAYBBBDwtYCy3GtAqAZb9OjRw6pXr25z5851kyk6duxIxj5f7z0qhwAC\nCCDgRwFNTtTEizZt2rhgQnPmzCH4RDbuqFq1apkGDE2fPt11sCnjGQUBBBBAAAEEEPAq8Pvvv9uD\nDz5o5cuXdwNXihUrZjNmzHAZ2dSPkjdvXq+rYrkYCegm3/79+2O0dlaLAALJJKAJD7lz506mJkel\nrcpYrOzWGtiiYBSVKlWye++91zTxk4IAAggggAACCMRTQNfwOg9RZsihQ4faNddc47KVjR49muAT\n8dwR/39bOi9ctWpVNmyZTSKAAALeBVavXu0yZnt/B0tGW0D9u9dee60LbPn++++bMo42adLEateu\nba+//rpxfz/a4qwPAQQQQACB4AvcfPPNpmt9BbEi+ET892d4srMCfw4cONA6depke/bsiX9F2CIC\nCCCAAAJRFihVqpSNGTPGVq5c6eaBKOBVxYoV3XMKwERBAAEEUgsQgCK1Br8jgEDCCSjLhG7eaPCF\nOmEUlWvNmjWuM0Y3cCgIIIAAAgggkHmBjRs3usEQiq6t6JeafMGkxMw7RvsdDRo0MA1W0T+d//zz\nzz/R3gTrQwABBBBAAIEEE5g/f74pi3vp0qVd5jUNmtCkibffftvIvOavna0ByhqEzDmev/YLtUEg\niAIKQEHmiqztuZw5c1rXrl1t2bJlNnjwYHfPQQMxdO+BIEFZM+VdCCCAAAIIIOBdYMOGDaaBoEq6\n8dRTT9ltt91m69ats4cfftiKFy/ufUUsGVWBypUru0nEundGQQABBPwq8NNPPxGAwic7J0eOHNa6\ndWubNWuWKclHuXLl3IRSHU/Uv8CkRp/sKKqBAAIIIIBANgv07t3bxo4da6+++qpdccUV2Vyb5N58\nnz59XGDyadOm2Xnnnef6YpJbhNYjgAACCCSKgAJRqC9CYwXbtWtnt99+uwtEoecIRJEoe5l2IHD0\nAgSgOHpD1oAAAj4T0ED8d999102UqFGjhn3zzTemCbIafKEMICVLlvRZjakOAggggAACwRH45JNP\nTMfXTZs2uQERCnRA8Y9Ao0aN7J133nFZUnr27GkpKSn+qRw1QQABBBBAAAFfCPz999/25ptv2vnn\nn29nn322zZ0710aOHGnr16+3YcOGuQGvvqgolThEIHfu3O6xJo5TEEAAgaMRUKAEAlAcjaDZcccd\nZ/369XMDMRSQQgMxqlevbm+88cbRrZh3I4AAAggggAACaQgoC1mPHj3cxGGdb2jMw9q1a23AgAFW\nqFChNN7BU/EUqFSpktuc9hMFAQQQ8KPAn3/+aQqSU6FCBT9WL6nrVKdOHdeXsHz5cmvVqpXdcccd\nLsmWMmxrPAYFAQQQQAABBJJPQGP9brzxRnv66adt4sSJdtlllyUfgg9b3KRJEzcfRWMtatWqZbNn\nz/ZhLakSAggggAACWRM45ZRTbNSoUW78Q4cOHdxYCPUjaR6m+pUoCCCQ3AIEoEju/U/rEUgogV27\ndrkJE4oIruhb+fLls6lTp9qiRYvcgAwysyfU7qYxCCCAAAJxFlCAJ2X3vPDCC61p06Y2b948O+OM\nM+JcCzbnRaBFixZuoMoLL7xgN998s5e3sAwCCCCAAAIIJIHAli1b7KGHHrLy5cu7LClFihSx6dOn\nu36Tf/3rX64fJQkYAtvE8GRxTRynIIAAAlkV0MBFDY4LB7XJ6np43/8EdCwdPny4LVu2zOrVq+eO\nr3Xr1mXgIR8QBBBAAAEEEIiKwMKFC11G9GrVqtnMmTNtzJgxpgz2t9xyC9fwURGOzkqUACV//vy2\nYsWK6KyQtSCAAAJRFlizZo1LWqB+YYo/BSpWrOiO80qu9e9//9vGjRtnZcuWNSWc4Pjiz31GrRBA\nAAEEEIiFgO7h6Pj/zDPPuORT7du3j8VmWGcWBXQ+/eWXX1rDhg2tWbNm7pwti6vibQgggAACCPhS\nQH3dSmKl+xAdO3a0/v37u4Cmeo5AFL7cZVQKgbgIEIAiLsxsBAEEYimgk5u+fftaqVKl7J577nET\nY5cuXWoffvihNW/ePJabZt0IIIAAAggkhYCyayiowcMPP2yjR4+2V1991QoUKJAUbQ9qIy+55BJ7\n5ZVXbOzYsS5TSlDbQb0RQAABBBBA4OgFFixYYNdff73rN3n00Ufd5Fhl5XznnXdMmToowRAITxb/\n66+/glFhaokAAr4UCAexCQe18WUlA1gpTQp56aWX7Ntvv7WCBQvaBRdcYLouX7JkSQBbQ5URQAAB\nBBBAILsFvvrqK3cucdZZZ7nziQkTJpjGP3Tv3t04j8vuvZP29itVqsQE4bRpeBYBBHwgoHF1Kspc\nSfG3QNGiRW3QoEGmQBQjRoywadOmmQJRafKpzg8oCCCAAAIIIJC4Ago+oaQRSjj15ptvWtu2bRO3\nsQFumcbMav8MGDDAbrrpJrvhhhssfO8twM2i6ggggAACCBwiUKJECXviiSdcIIpOnTrZXXfd5RJe\n6bm9e/cesiwPEEAg8QUIQJH4+5gWIpCwArNmzbJ27dpZ5cqVbdKkSe5ifv369S4ieJUqVRK23TQM\nAQQQQACBeArMnj3batSoYatXr7YvvvjCevXqFc/Ns62jELjsssts/Pjx9thjj9nAgQOPYk28FQEE\nEEAAAQSCJnDgwAF766233ARYnct9/fXX9vjjj9uGDRtcpnay3QVtj9rBSUYEoAjevqPGCPhJIPwd\nwsTF2OyVmjVr2tSpU23KlCmmexVnnnmmmyi6cePG2GyQtSKAAAIIIIBAQgl88skn1rhxY2vQoIFt\n2bLF3n//ffv+++9NAzxz5cqVUG1NtMYoAIWCfVIQQAABPwroPv+JJ55oJ5xwgh+rR53SEMibN68b\nl7F8+XKX/Vz9Cjo/OO+88+zdd981TVClIIAAAggggEDiCPzzzz8uoYQCXesef5s2bRKncQnYkhw5\ncrixmJq7ogRhSvqhBG8UBBBAAAEEEk3g5JNPdgEy1bfUpUsXlzBcYw4VNHPPnj2J1lzagwAC6QgQ\ngCIdGJ5GAAF/CmiArCZSaiBno0aN3AX7a6+95iJr9evXzwoVKuTPilMrBBBAAAEEAiagQQsPP/yw\n6yCvW7euy+J5zjnnBKwVVPfKK6+0//73v/bAAw/YQw89BAgCCCCAAAIIJLiAJqjoHE43ey6//HLX\nT6IsaYsXL7aePXtavnz5ElwgcZsXnixOBpXE3ce0DIF4CIQDUOTOnTsem0vabbRo0cK+++47e/75\n5122UgXRvueee2znzp1Ja0LDEUAAAQQQQCBtAd2Lefvtt6127dqmcwidp3366af25ZdfWuvWrU2T\nGij+F9D53ooVK/xfUWqIAAJJKfDTTz9ZhQoVkrLtQW90zpw5rUOHDi7AtBJ1FS5c2CXrOvXUU90Y\ngH379gW9idQfAQQQQACBpBdQ8InrrrvOBTJQ/4D6AijBEGjbtq07T/vll1+sVq1a7r5QMGpOLRFA\nAAEEEMicQPHixV0yTAWiuPrqq+3ee+91fU1KkEkgisxZsjQCQRQgAEUQ9xp1RiAJBRQZcsiQIVam\nTBnr0aOHVa9e3ebOnesysXfs2JGMH0n4maDJCCCAAAKxE9i6datdcsklLlLzo48+6gY/EuQpdt6x\nXrNuUo0ePdruvvtul/k81ttj/QgggAACCCAQf4GFCxe6DOulS5e2Rx55xNRXookPyobWtGnT+FeI\nLUZdIDxZPDx5POobYIUIIJAUAuEgNuGgNknR6GxqpCaLavDFsmXL3L2NcePGWcWKFW3UqFEW3g/Z\nVDU2iwACCCCAAAI+EPj7779NmU1PO+00N7FU1/PffPONTZ061SXi8EEVqUImBCpVqmSrVq3KxDtY\nFAEEEIifgAJQKGAxJdgC559/vr3//vsu2PS5555rvXv3trJly9qDDz5o27ZtC3bjqD0CCCCAAAJJ\nKnDgwAHr1q2bTZw40d3Xb9WqVZJKBLfZ6tfRfJaqVavaeeedZ6+++mpwG0PNEUAAAQQQiCBw0kkn\n2bBhw2zNmjXWtWtXGzRokOtz0nO7d++O8G5eRgCBoAoQgCKoe456I5AkAgsWLLBrr73WBZ548skn\n7frrr3cnKy+//LLLApIkDDQTAQQQQACBuAnMmTPHatasaZrEqCwat956a9y2zYZiJ3DjjTe66KPa\nn5r0QkEAAQQQQACB4AtoQMqkSZPcxJSzzjrLZUdVZPH169e74z5Z7YK/j1O3IDxZnAAUqVX4HQEE\nMisQ/g4JB7XJ7PtZPvMCefLksdtvv91NSLzmmmvsjjvuMGUq1YBSZTynIIAAAggggEByCfz555+u\nj75y5couw6kyZC5atMhd3+t3SjAFtD81wHbjxo3BbAC1RgCBhBZQdkr6ihNnF6tP4dlnn3XjJzWm\nUpM8FMjqlltusbVr1yZOQ2kJAggggAACCS6ge/2auPnWW2/Ze++9Zy1btkzwFidu84oUKWIff/yx\n9ezZ07p06WL9+/e3f/75J3EbTMsQQAABBJJeoFixYqYEp+pzUt/Efffd5wJR6DkCUST9xwOABBQg\nAEUC7lSahEDQBXTRrQydjRs3tho1arhMHwo+8fPPP9vQoUOtZMmSQW8i9UcAAQQQQMCXAiNHjrSG\nDRu6jFvz58+3+vXr+7KeVCprAgo+oXOpm266yZ5//vmsrYR3IYAAAggggEC2C2zdutXdxNGg4Y4d\nO9rxxx/vMqQuWbLEevXqZfnz58/2OlKB6AuEA1Ds378/+itnjQggkDQC4QAU4e+UpGm4DxpauHBh\nNylk+fLl1qBBAzcIsW7dujZz5kwf1I4qIIAAAggggECsBXbt2uXOBZSBXn31ymq6YsUKe/HFF616\n9eqx3jzrj7GAAlCorFy5MsZbYvUIIIBA5gV++uknAlBkns337yhRooQ99NBDbjzl/fffb2+//bZV\nqlTJ9Td89913vq8/FUQAAQQQQCCZBf7++2+76qqr3PH7/ffft+bNmyczR0K0PVeuXDZixAh74YUX\nTGNwW7dubTt27EiIttEIBBBAAAEE0hNQIIqHH37YBaJQsnH1T5QrV84eeeQR++OPP9J7G88jgEDA\nBAhAEbAdRnURSGQBDbrQRbduzrdr187y5cvnJlAo40ePHj0sb968idx82oYAAggggEC2Caiz+7LL\nLrPbbrvNBg8ebB9++KGdeOKJ2VYfNhw7gbvvvtsGDBhg3bt3t1deeSV2G2LNCCCAAAIIIBB1gR9+\n+MH1j5QqVcoefPBB69Chg2kSK4NSok7tyxXmzp3b1Ss8edyXlaRSCCDge4FwEBsCUGTfripTpoyb\naKrJIApKoUDcGoio+yAUBBBAAAEEEEg8gS1bttigQYOsbNmybvDl1Vdf7QZjjh071g3ETLwWJ2eL\nNAlYAUEVVISCAAII+Eng999/N43HUzBjSmIKFChQwPr27WurVq1yEx4VqPqcc86xZs2a2ZQpUxKz\n0bQKAQQQQACBAAso+ESXLl3svffec2M0mzZtGuDWUPXDBbp162azZ8+2BQsWWJ06dWzp0qWHL8Jj\nBBBAAAEEEk6gaNGiLkjmmjVr3NhGJctUIAoFzlS/FAUBBIItQACKYO8/ao9AQggo0rpuhGgCxT33\n3GMXXnihu+DW5FeieibELqYRCCCAAAI+Fpg/f74bgPDFF1/YtGnTTAEKcuTI4eMaU7WjFbjvvvtc\nhrWuXbvaW2+9dbSr4/0IIIAAAgggEEOBAwcOuMwnmpx65pln2ueff27Dhw+39evXuwwaFStWjOHW\nWbWfBMKTxcOTx/1UN+qCAALBEQgHsQkHtQlOzROvpmeddZabCPLJJ5/Yxo0bTY+VFWTDhg2J11ha\nhAACCCCAQBIK6PiuoN8KPDFmzBi75ZZbbO3atfboo4/aySefnIQiid9kZZ0nAEXi72daiEDQBDQm\nT4UAFEHbc5mv7zHHHGNXXnmlff/99y7hV86cOd0YTPU3vPTSS0a/cuZNeQcCCCCAAALRFlDwiU6d\nOtnkyZPdP40BoCSegAJPzJs3z4oUKWL16tVzgUYSr5W0CAEEEEAAgSMFlPxUSbUUiKJnz54uAEX5\n8uXdcwSiONKLZxAIigABKIKyp6gnAgkoMGvWLGvXrp1VrlzZJk2a5LJxawKFBmBUqVIlAVtMkxBA\nAAEEEPCXwH/+8x+rX7++KfumBiI0atTIXxWkNjETGDZsmPXq1cs6d+5sH3zwQcy2w4oRQAABBBBA\nIGsC27ZtMx2vFWCiQ4cOLoumspUpe9mNN95oympGSS6B8GTx8OTx5Go9rUUAgWgJhCcbhIPaRGu9\nrCfrAspI+u2339qLL75oM2bMcPdLFBx0x44dWV8p70QAAQQQQACBbBNQ9vEbbrjBNKjytddeMwWE\nVuCJgQMHWuHChbOtXmw49gIKQLFy5crYb4gtIIAAApkQUAAKBSYoXbp0Jt7FokEXUMKvqVOnmpKR\nnHHGGXbddde5ICSPPfYYmUeDvnOpPwIIIIBAYAV0f+byyy93gak/+ugju+CCCwLbFioeWaBEiRI2\nc+ZMa9++vbVp08ZNwI38LpZAAAEEEEAgMQQUhOmBBx5wgSg0V+GRRx6xcuXK2dChQ23nzp2J0Uha\ngUASCRCAIol2Nk1FwA8CGiQ/fvx4q1mzppvkumnTJjfwQje8+vXrZ4UKFfJDNakDAggggAACCS2w\ne/duu+qqq1wAAh1/p02bZsWLF0/oNtO4IwVGjRpl11xzjV122WVuAMqRS/AMAggggAACCMRbYNGi\nRW6iSqlSpdyNGAXuXL58uQsY1aJFC8uRI0e8q8T2fCIQnixOAAqf7BCqgUBABcLfIeHvlIA2I+Gq\nreO7spQuXbrUHf8VMFRBqEaOHGnhfZZwjaZBCCCAAAIIJJjADz/8YF26dLGqVava9OnT7cknn7TV\nq1fbrbfe6oJKJlhzaU4aAkq8smLFijRe4SkEEEAg+wR0LFLwCQWhoCSfQI0aNWzChAmmAFkaEzB4\n8GD3eejfv79t3Lgx+UBoMQIIIIAAAtkkoH7+jh07ujGaH3/8sTVs2DCbasJm4ymQJ08ee+655+zx\nxx93gUk7depke/bsiWcV2BYCCCCAAALZKqBAFPfff78LRNG7d2+XjEuBKPQcgSiyddewcQQyJUAA\nikxxsTACCGRVQIEmhgwZ4jKs9+jRw6pXr25z5861L774wnWq5MqVK6ur5n0IIIAAAgggkAmBxYsX\nW+3atQ9G09ZFfM6cXBZkgjBhFtUEl6eeespFV2/btq2Lup0wjaMhCCCAAAIIBEjgn3/+sXfeecea\nNGnispHNmjXLHn30UduwYYMbjKAMmhQEwpPFlR2HggACCGRVIBzMIHfu3FldBe+LoYAGI2qSqiaG\nXH/99XbnnXfaqaee6oJ4p6SkxHDLrBoBBBBAAAEEsirw9ddfu0yWZ511limo5EsvvWTLli2zf/3r\nXxa+jsvqunlfsATUf6PzOAoCCCDgJwElhKpQoYKfqkRdskGgTJky7l7Dzz//bAo+8eKLL1r58uXt\nuuuuM40foSCAAAIIIIBA7AR0X6ZDhw726aefuvGa5557buw2xpp9KdCnTx+375Uk7rzzzrN169b5\nsp5UCgEEEEAAgVgJFC5c2M0nXbNmjem4OGLECCtbtqzdd999tmPHjlhtlvUigECUBJhpFiVIVoMA\nAmkLLFiwwK699loXeEJZPjRoUicNL7/8spv8mva7eBYBBBBAAAEEYiGggQR16tQxRZScP3++tWzZ\nMhabYZ0BElDwkeeff94uueQS9+/LL78MUO2pKgIIIIAAAsEW2LZtmw0fPtxlOG/fvr3lzZvXlPHk\nxx9/tJtuuskKFCgQ7AZS+6gKhCeLhyePR3XlrAwBBJJGIBzEhsmQ/t7lhQoVskceecSWL1/uMqFd\neeWVrj9HA1QpCCCAAAIIIOAPAU0aUCDJ+vXr2+bNm+3dd981jY3o3LmzkXzDH/so3rWoXLmy7d69\nm4zy8YZnewggkKGAAlAo0AAFAQmov+Guu+5yYzfHjh1rCqR1xhlnWOvWrU2BsSkIIIAAAgggEF2B\nffv2Wbt27eyzzz6zqVOnuj6E6G6BtQVFQH1IStz6999/W61atWz27NlBqTr1RAABBBBAIGoC6pcY\nPHiw65e45ZZbXLDMcuXKuee2b98ete2wIgQQiK4AASii68naEEAgJKDMnRpg0bhxY6tRo4Z98803\npuATiqI9dOhQK1myJE4IIIAAAgggEEeBvXv3Wvfu3a1bt25244032syZM61UqVJxrAGb8rOABsMq\nOFjTpk3toosusnnz5vm5utQNAQQQQACBwAsoo1jPnj3d+dj999/vMqUqO+qHH37oAoTlyJEj8G2k\nAdEXOOaYY0yfDQJQRN+WNSKQTALh7xACUARjr5cuXdpeeOEFF0S0aNGibpKrrtt/+OGHYDSAWiKA\nAAIIIJBgAikpKfbOO++4wFDNmzd3gSZmzJhhX331lQvwzPV8gu3wTDZHAShUVq5cmcl3sjgCCCAQ\nOwEFoKhQoULsNsCaAymQJ08el0RM9yo0xnPnzp3WqFEjd47zxhtv2IEDBwLZLiqNAAIIIICAnwT+\n/PNPa9u2rSkZlIJP1K1b10/Voy7ZIKDzcn0eGjZsaM2aNbNx48ZlQy3YJAIIIIAAAtkvULBgQRs0\naJALRHHrrbfaqFGjTIEo9JwSelEQQMBfAgSg8Nf+oDYIBFpg165dNnLkSNONdUXszJcvn+s0WbRo\nkfXo0cNl8gx0A6k8AggggAACARRYsWKF1atXz9566y03eGDYsGGmyWsUBFIL6DPx+uuvu0jrLVu2\ndJnaUr/O7wgggAACCCBwdALhYJ0aSHD66aebMpg//PDDtn79+oN9KUe3Bd6dDAKaML5///5kaCpt\nRACBGAmEA1Dkzp07RltgtbEQOPPMM+2jjz4yZVr/7bffXODva6+91p1HxGJ7rBMBBBBAAAEEDhVQ\ndsoJEya4DOHt27e3U045xebMmWOffPKJS8px6NI8SlaBEiVKWP78+U335SgIIICAHwR0/FKyKAJQ\n+GFv+LMOCp51ySWXuAzcX3/9tZUpU8Y6depkVapUsTFjxtiePXv8WXFqhQACCCCAgM8FFHzi0ksv\nPdh3UKdOHZ/XmOrFS6BAgQL25ptv2oABA+ymm26yG264gfv/8cJnOwgggAACvhNQIIp7773XBaK4\n/fbbbfTo0S4QhZ4jEIXvdhcVSmIBAlAk8c6n6QhES0DR0vv27esyd95zzz124YUX2tKlS13mTmX+\noCCAAAIIIIBA9ggooMA555xjmqg2f/58l107e2rCVoMgoM/J22+/7Say6BxuyZIlQag2dUQAAQQQ\nQMDXAtu3b7fHHnvMKlWq5IJ16nirCaTqN/n3v/9txx9/vK/rT+X8JaAJ4+HJ4/6qGbVBAIGgCISD\n2BCAIih77NB6Nm3a1ObNm2cvvfSSzZo1ywUDv/POO23Hjh2HLsgjBBBAAAEEEIiKwL59++ypp55y\nkzAV/KlmzZr2ww8/uH50Jo9EhTjhVqL+HwJQJNxupUEIBFZg3bp1duDAAQJQBHYPxrfiysquyZDL\nli0zJazo16+fC0ih7KObN2+Ob2XYGgIIIIAAAgEW2Lt3rwvwpL58BZWuVatWgFtD1WMhoCBgAwcO\ntEmTJtkrr7xiTZo0sU2bNsViU6wTAQQQQACBQAiccMIJLjjTmjVrrH///jZ27FgXiEIBm7Zu3RqI\nNlBJBBJZgAAUibx3aRsCMRbQAMd27dq5QY66CNbBXZk7FQFbkbApCCCAAAIIIJA9ApqUpgmNV1xx\nhXXt2tW++OILdyGePbVhq0ESOO644+y9996zqlWrmjK0M1AySHuPuiKAAAII+ElAgZx69erlgnUO\nGTLEWrdu7YJOTJ482QXu1KACCgKZFVAAk/Dk8cy+l+URQAABCai/gOATwf4s6ByiS5cu7rziwQcf\ntGeeecYqVqxojz/+OEGKgr1rqT0CCCCAgI8E/vjjDxs+fLiVL1/ebrnlFjcJc/ny5S4I1Gmnneaj\nmlIVvwkoAMXKlSv9Vi3qgwACSSqghFIqFSpUSFIBmp0VAR3LNNFj7dq11rt3b/d72bJl3f0OjnFZ\nEeU9CCCAAALJJLBnzx43LkCJwqZPn25nn312MjWftmZSoG3btvb111/bL7/84gKVfPfdd5lcA4sj\ngAACCCCQWAJK5HX33XebAlEoEYcChJcrV86UKH3Lli2J1Vhag0CABAhAEaCdRVUR8IOABqiOHz/e\nZfdo1KiRi7j42muvmW5aKfJ1oUKF/FBN6oAAAggggEDSCuii+9xzz3XH64kTJ9ro0aNNE9UoCHgV\nyJ8/v2lybOnSpU3ZVfWZoiCAAAIIIIBAZIF//vnH3n//fWvevLlpQooGlWhi6IYNG2zUqFEE64xM\nyBIRBHRer745CgIIIJBVAQWxoY8gq3r+ep/2Y9++fW3VqlXWvXt3N+iiWrVqLltWSkqKvypLbRBA\nAAEEEAiIgDJpDR482DTJUsEkr7zySlu9erWNGzfOBaMISDOoZjYKVK5cmcDe2ejPphFA4FABjeXT\nwP0TTzzx0Bd4hIAHgWLFirnzIgWiUGCuqVOnuiQWHTp0cBMlPayCRRBAAAEEEEgqgd27d9vFF19s\nCxcudOMEatSokVTtp7FZE9C4krlz57rzrPPOO89effXVrK2IdyGAAAIIIJBAAurPuuuuu9z8BQWk\nePrpp10gCj33+++/J1BLaQoCwRAgAEUw9hO1RCDbBTZt2uQGWZQpU8Z69Ohh1atXdxe8yqjesWNH\ny5UrV7bXkQoggAACCCCQ7ALvvfeei5ytSWnz5s2zyy+/PNlJaH8WBdR5M2XKFCtatKg1adLE1q9f\nn8U18TYEEEAAAQQSX2DHjh02YsQI0ySDSy+91I455hj78MMPbdmyZdanTx83yDfxFWhhPARy585N\nAIp4QLMNBBJYQP0FBKBIrB1csGBBe/jhh01Z2RU0/Oqrr3aZshQIi4IAAggggAAC3gQ2btxot99+\nuws88eSTT7preU22HDZsmJUoUcLbSlgKgZCAssYrQBgFAQQQ8IOAgihVqFDBD1WhDgEWyJcvn914\n442u30FJyn7++WerX7++NWzY0AXkJghmgHcuVUcAAQQQiJqAgk9cdNFFtnjxYpsxY4adddZZUVs3\nK0p8gSJFitjHH39sPXv2tC5dulj//v1NyU8oCCCAAAIIJLtAgQIF7M4773SBKO6991579tlnXbBw\nPUcgimT/dND+eAoQgCKe2mwLgQAKLFiwwK699lpT4AllUL/++uvdwfvll1+22rVrB7BFVBkBBBBA\nAIHEE/j777+tX79+bsJj+/btXcaJKlWqJF5DaVFcBQoVKuQymeTPn98Fofj111/jun02hgACCCCA\ngN8FfvzxRzfw8pRTTrFBgwa5QSV67qOPPnK/58iRw+9NoH4BE9Ck8f379wes1lQXAQT8JKAAFApm\nQ0k8gVKlStlzzz1n33//vRUvXtyaNWtmrVq1ctnWEq+1tAgBBBBAAIHoCCgzvAb3a3LuK6+8cjDL\nt67xNfifgkBmBRScVBOPFNSEggACCGS3gI5zBKDI7r2QONtXcjIlKVOG7pkzZ5oCYiogt5KYaQLI\nvn37EqextAQBBBBAAIFMCPzxxx924YUX2tKlS+3TTz+1M844IxPvZlEE/iegcy0lPXnhhRds5MiR\n1rp1a1MiFAoCCCCAAAIImGkewx133GEKtjpw4EB7/vnnrVy5ci5o0+bNmyFCAIEYCxCAIsbArB6B\nIAooauK7775rjRs3tho1atg333xjyvSxbt06Gzp0qJUsWTKIzaLOCCCAAAIIJKTAhg0bXIbLsWPH\n2vjx4+2ZZ56xvHnzJmRbaVT8BYoWLWrTpk2znDlzWtOmTY2OmvjvA7aIAAIIIOAvAfWZfPDBB9ai\nRQs3sPKTTz5xfSU6J1PfSdWqVf1VYWqTUAKaNK7J4xQEEEAgqwIKYqNgNpTEFdDg1smTJ7ssa8r6\nUbNmTbvmmmtchtLEbTUtQwABBBBAIHMCixYtsquuusoUyFvX9RrYr4GLt912mymjFgWBrApUqlTJ\nvXXlypVZXQXvQwABBKImQACKqFGyosMELrjgAnefROdU9evXd4G6NfHjoYcesm3bth22NA8RQAAB\nBBBIXIFdu3ZZy5YtbcWKFS74xGmnnZa4jaVlcRHo1q2bzZ4925RAtk6dOi6wSVw2zEYQQAABBBAI\ngIACUShhq+7nDBkyxAVuUn+Entu0aVMAWkAVEQimAAEogrnfqDUCMRFQR4gGVygrQ7t27Sxfvnwu\n67VuFvTo0YPJrDFRZ6UIIIAAAghkXWDq1KkuWNSWLVtcpomuXbtmfWW8E4F0BJQ5dfr06fbnn39a\n8+bNGTSSjhNPI4AAAggktoCySzzxxBNuckqbNm0sR44cboDl8uXL7eabb7YTTjghsQFonS8ENGmc\nABS+2BVUAoHACug7RMFsKIkvoADjykr68ssv22effebOYfr372/bt29P/MbTQgQQQAABBNIRmDNn\njrVt29bOPPNMN5BfQb11XX/DDTdYnjx50nkXTyPgXUDJXDQIVpOPKAgggEB2CygARfny5bO7Gmw/\ngQWqV69uzz33nJv4ocmSjzzyiJUpU8b69u3rEp0lcNNpGgIIIIAAArZz506XtEITIGfOnOmSV8CC\nQDQEFHhi3rx5VqRIEatXr559+OGH0Vgt60AAAQQQQCBhBDTXVQHFdR52//3320svveT6wG6//Xb7\n7bffEqadNAQBvwgQgMIve4J6IJCNArrhpI7/UqVK2T333GMXXnihi5ioC1ZNMqQggAACCCCAgL8E\nlHl74MCB1qpVK3cjQx3ORND21z5KtNqccsopLnuqMpYocrtuolEQQAABBBBIBoGlS5da7969XZ/J\nvffe6/pMlixZYlOmTLGLL77YBaJIBgfa6A8BBaDYv3+/PypDLRBAIJACCkCh7xJKcggoYFanTp3s\nxx9/tIcfftieffZZq1ixoo0YMcL27duXHAi0EgEEEEAAgZDAjBkzrFmzZm7Q/i+//GJvv/22LVy4\n0K688krLlSsXRghEVaBSpUoEoIiqKCtDAIGsCOhe7tatW61ChQpZeTvvQSBTAgrApH6Hn3/+2WUg\nfeutt1z/g861vv/++0yti4URQAABBBAIgoCSV2h+xbp16+zTTz+1atWqBaHa1DFAAiVKlHCBTdq3\nb29KkPLQQw8FqPZUFQEEEEAAgfgIKBDFrbfe6gJRPPDAAy45h4Kx6rlff/01PpVgKwgkgQABKJJg\nJ9NEBNITmDVrlrVr184qV65skyZNsgEDBtj69ettzJgxLhtWeu/jeQQQQAABBBDIPgFFZtQNjEcf\nfdTGjh3rLpaVTYmCQKwFypYta9OnT7cNGza44Ce7d++O9SZZPwIIIIAAAtkikJKS4rJIKOiSMnh9\n/PHHLlq2+kxGjx7NAJJs2StsVAK5c+c2TR6nIIAAAlkVUBAbAlBkVS+479M+v/nmm23VqlUuw7vu\nBVWtWtX1Kem8h4IAAggggEAiCugY995777mgE02bNjU9njZtms2ZM8cuvfRSAkom4k73SZsUgGLl\nypU+qQ3VQACBZBVQMioVAlAk6ycge9p9/PHHu0ke6n94/vnnbdGiRVazZk03vmXq1KnZUym2igAC\nCCCAQJQFtm/f7o5tGj83c+ZM19ce5U2wOgScQJ48eey5556zxx9/3CWrU8DxPXv2oIMAAggggAAC\nhwnkzZvXJWVXf5iCNr322muuT0yJ2hWUnIIAAkcnQACKo/Pj3QgETkCD1MePH+869xs1amSbNm1y\nB1cdaPv162eFChUKXJuoMAIIIIAAAskioOBRNWrUsLVr19pXX33lJg0kS9tppz8ENHBSQSg0eLJ1\n69a2d+9ef1SMWiCAAAIIIBAFAWWFGzlypAvKqeNceLLK8uXL7ZZbbrGCBQtGYSusAoGsC2gCsSaP\nUxBAAIGsCuj+gILZUJJTQOcyDz74oMvIrYm4Xbt2tXPOOcdNxk1OEVqNAAIIIJCIAgcOHHBBls48\n80xr27atFS9e3L7++mvXr63jHwWBWAsoAcyKFStivRnWjwACCGQooHGAOXLksHLlymW4HC8iEAsB\n9T1dddVVtmDBApsyZYq716KA3xrrMmHCBPv7779jsVnWiQACCCCAQMwFtm3bZs2aNXMTGRV8Qtd/\nFARiLdCnTx93TqXAquedd56tW7cu1ptk/QgggAACCARSQIEolJhD/WIPP/ywvf766y4QhcZ9Eogi\nkLuUSvtEgAAUPtkRVAOBWAso0MSQIUOsTJky1qNHD5fBc+7cufbFF19Yx44dLVeuXLGuAutHAAEE\nEEAAgSwKaPKjJghocGSDBg3s22+/dcGksrg63obAUQlUq1bNTU754YcfrF27drZv376jWh9vRgAB\nBBBAILsFli1bZv/+97/tlFNOsXvuucdlLFmyZIkpI5cCUeTMSRdqdu8jtv8/AQWg0ORxCgIIIJBV\nAQWx0XcJJbkFdM7z7LPP2sKFC61kyZLu3EcTQTQxhIIAAggggEBQBdRP/Z///McFlezWrZspAIWO\nde+++67VrVs3qM2i3gEUUCBvZX6nIIAAAtkpoIH2ut5T1mQKAtkp0KJFCze24LvvvnPjVa+99lo3\n+WPEiBG2a9eu7Kwa20YAAQQQQCBTAlu3bnVjNzdv3mxKIqZrPwoC8RJo0qSJffPNNy6QV61atWz2\n7Nnx2jTbQQABBBBAIHACxx13nCmAk/rphw0bZm+++abri9BzGzduDFx7qDAC2S3A6Ons3gNsH4EY\nC2jAoDruFXhi9OjRdv3119uaNWtc1o/atWvHeOusHgEEEEAAAQSOVmDLli128cUX2+DBg+2xxx6z\nt956i+zbR4vK+49a4IwzznCRtZU5TsHMyMR91KSsAAEEEEAgzgIK8DV58mRr1aqVnXrqqe73++67\nzzZs2GBjx451z8W5SmwOgYgCyhxHAIqITCyAAAIZCOg7hAAUGQAl2UunnXaaffDBB/bpp5+aMred\nffbZ1rVrV7JnJdnngOYigAACQRf4448/3L2TChUquMxWzZs3t+XLl7vxEKeffnrQm0f9AyigDLi7\nd+9mIGsA9x1VRiCRBFavXu0G1idSm2hLsAVq1qxpr7zyiq1cudLat29vgwYNcuNZ77rrLrKQBnvX\nUnsEEEAgKQQ0flMBABSEYubMmZxnJcVe918jy5cvb19++aU1bNjQmjVrZuPGjfNfJakRAggggAAC\nPhJQIIrevXu7QBTDhw+3t99+253HKVGZxohSEEDAmwABKLw5sRQCgRL4559/XCaPxo0bW40aNVzE\nwyeffNINGhw6dKiLcB6oBlFZBBBAAAEEklTgq6++Mt2IX7x4sX322Wdu8GSSUtBsHwqcc8459vHH\nH7uJKl26dLEDBw74sJZUCQEEEEAAgUMFdu7caaNGjbKqVau6IF9///2360NZsWKF9e3bl0Bfh3Lx\nyGcCmjRO4C+f7RSqg0DABBSAQsFsKAikFmjUqJHNmTPHTQTR4MUqVapYv379XFCK1MvxOwIIIIAA\nAn4SUPCkIUOGWNmyZd0Exs6dO5uyvT/11FNMBPHTjkrCuigAhYom2FIQQACB7BLQMVHBmSgI+E1A\n525PPPGEG8eqvocXXnjBypUr55KqLVmyxG/VpT4IIIAAAgjY77//7oJP7Nixw2bNmmUKAkBBILsE\nChQo4LK4DxgwwG666Sa74YYbGD+QXTuD7SKAAAIIBEYgT5487ripPvsRI0a4saIVK1Z0z61fvz4w\n7aCiCGSXAAEoskue7SIQA4Fdu3bZyJEjTTe027VrZ/ny5bOpU6faokWLrEePHpY3b94YbJVVIuBd\nQBN79uzZc/Dfvn373JtTP6fflYmWggACCCS7wOOPP24XXHCBnXnmmTZ//nyrW7duspPQfh8K1KtX\nzz788EOXNb5bt26mQGgUBBBAAAEE/Cig7Kd9+vSxUqVK2d13321NmzZ1Qb4++eQTu+SSSyxnTrpJ\n/bjfqNP/CaivJFeuXK5PRROtfvvtN9NNsLVr1/7fQvyGAAIIHCawbt06+/nnn913hjJzqe/1mGOO\nof/1MCcemuXIkcOuuOIK+/HHH+3RRx91E0A06EKZQML9+DghgAACCCDgB4FffvnFBUoqU6aMGxuh\nTFU659Exq2TJkn6oInVIcoESJUpY/vz5benSpS4IhQJ5K2HMwIED7c8//0xyHZqPAAKxEPj888/t\nwQcftFdffdUFF9y8ebMLykQAilhos85oCRQuXNjdq1mzZo2NGTPGZfM+/fTT3f2a2bNnR2szrAcB\nBBBAAIGjEti0aZMpGegff/zhgk8okBIFgewW0P0c9TFMmjTJBRZv0qSJ6bNKQQABBBJJIK35Zbpn\nnfp5zU2jIJAZAQWiuPHGG12/vYJjfvDBB6YxEXpO42ooCCCQtkCO0MBVZvmmbcOzCARGQFHLdcP6\nueeec5mnNfnv5ptvdlmqAtMIKpoUAqVLl3aTIyI1tmfPnjZu3LhIi/E6AgggkJACipZ9zTXX2Pvv\nv28PPPCA9e/f300CSMjG0qiEEZg2bZobDNKlSxd75plnjvjM6jy1YcOGLlBawjSahiCAAAII+F5A\n3Z5TpkyxUaNGmQb7K4uWskBcf/31VqhQId/Xnwomt8CCBQtcQDpNTtm/f3+Ggb4mT55srVq1Sm4w\nWo8AAkcIaAKKrsPSKwq+lDt3btNN9o8++sgaNGiQ3qI8n4QCO3futEceecRlJS1atKjro7rqqquO\nuN5PQhqajAACCCCQTQKrV692QZKef/55K1KkiN16662me8rK/EhBIDsFdM0+Y8YMU/DTFStWuMAT\nX331le3evftg4DedeyuAtwJJnnLKKdlZXbaNAAIJKNC3b1937aaJaOGhwApkq4A4NWvWtEqVKpmC\nUdSuXZukFwm4/xOlSfrsaozMsGHDTH1aderUcUHH2rdvTwDxRNnJtAMBBBDwqYCOP0peoaSfqYuS\nAWhivya7zpw50yW6SP06vyPgB4HFixfbpZdean/99Ze98847dvbZZ/uhWtQBAQQQOCqBO+64w10b\nRlqJxv4pgQ8FgawK6Pipe04PPfSQKfj5ddddZ3fddZcpADoFAQQOCkwmtd9BC35BIHgCs2bNsnbt\n2rmJfIpiOGDAAHfDWlGhq1SpErwGUeOEF6hevbqnAaqnnXZawlvQQAQQSE4BRcPW5HwNMkurfPfd\nd64TeM6cOW6w2p133unpezOtdfEcAvEUaNasmb355ps2YcIE69279yGbvv32291EXwVIoyCAAAII\nIBAPgV27drlAndWqVXOT8sM321euXGm33XYbwSfisRPYxlELKHOvrh80qCm96wdtRAPLzznnnKPe\nHitAAIHEEzjzzDPtmGOOSbdh+m7Rd4wCDZQqVSrd5XghOQVOOOEEGzp0qJtE2aJFC7v22mtdn9XU\nqVOTE4RWI4AAAghkm4AG0l999dVu/IOCTCorlYJRqN+Z4BPZtlvYcCqBDz/80C688EIXFOWpp56y\nTz75xF3PhyeBa1Gde2tANMEnUsHxKwIIRE1AfYOpg09oxQcOHHBjCDWhUuMI+/TpY5dffnnUtsmK\nEIi2gD7Dbdq0sc8++8wUyEl9VVdccYU7Bxw7dqzt3bs32ptkfQgggAACCNjs2bPd8UfXdMqoHi6/\n/vqrNW7c2CUJ0FwN7qGEZfjpNwHNt5g7d65VrVrVzjvvPHv11VfTrKKuC/r165fmazyJAAII+E3A\ny1wyXUOeeuqpfqs69QmYwLHHHms33HCDGxMxevRol+BMgVz13Nq1awPWGqqLQOwECEARO1vWjEBM\nBDRpYvz48S5CeaNGjWzTpk322muv2U8//eQuDMngGRN2Vholga5du0Zcky4GuOkZkYkFEEAgoALK\nPtKjRw83gP/wJowbN85lGy1fvrx9//33dv755x++CI8R8LXAxRdf7M5Ln376aTe5V4MrFYxixIgR\nrt7KqLtkyRJft4HKIYAAAggEW0BZJhXwSANAFMhLg0IWLVpk06ZNcwNHlG2SgkBQBIoVK2YXXXSR\nKVthekV9KPXr17eTTjopvUV4HgEEklhAAQSaN2+eYZZIHRsvuOACMjgk8eckUtMVEOm///2vLVy4\n0EqXLm0tW7Y0BaSYP39+pLe6ySHbt2+PuBwLIIAAAgggkJbAN99845JxnHHGGabg3cpCtXz5cuvZ\ns6flyZMnrbfwHALZItCqVSsrXry4/f33325yUnqVqFWrVnov8TwCCCBwVAJ16tSx1EFvDl+Zxhrq\n+l9BKCgIBEGgXr169tZbb9nSpUtNiTAUWFzZRwcPHmy///57EJpAHRFAAAEEAiIwaNAgdy9WwY90\nX1YBj5T9ulFofoYCes2cOZNAggHZl8lczSJFirgJs+oz69Kli/Xv3/+QBBe6v9OxY0cbPny4vf32\n28lMRdsRQCAgAkrSnTt37gxrq/FSXuamZbgSXkTg/wvo86b5PboHpSCYCjJduXJl+9e//mVr1qzB\nCYGkF2DUddJ/BADIToHPP//c3YT2UgcFmhgyZIjrTNeBrXr16i5i4RdffOEuCjMajO5l/SyDQDwE\nLr300gwvBnTDUxOEmDgRj73BNhBAIN4C06dPt2eeecZtVjcvZsyY4X5XVmN1/Gqivjp/lUmS78F4\n7x22Fy0Bdfy99NJL9vjjj7vMqOqICQ94UgfNo48+Gq1NsR4EEEAAgQQWUCAJZWT3UnScUQZUBUJS\nVof33nvP7r33XpfdTVknvURF97IdlkEgOwSuv/56N7gpvW2rH6Vz587pvczzCCCAQMRAvzqOdu/e\nHSkEIgronpTOs5TtbceOHaYMu8pGn1Hmj06dOrnMM+vXr4+4fhZAAAEEEEhsgd27d9utt95q69at\ni9jQTz/91AXR0mTaDRs22KRJk1xwyauuusqOOeaYiO9nAQTiLaCAKPfff79p0HN6RZnU9JmmIIAA\nArEQ0ID4/PnzZ7jqggULWq9evTJchhcR8JuAPtu6z6NzSH1+lY1UgShuuukmW7VqlafqvvHGG56X\n9bRCFkIAAQQQSBiBr7/+2gWYUKAJBRTUfAwF9VbSMF3fKfiEAjRTEAiCgOYRKUnYCy+8YCNHjrTW\nrVu7ezlbtmxxwVX0GdfnWudUGq9MQQABBPwsoEQbadAmagAAQABJREFUGgcYaY6kgutQEIimgOY5\naPyMAlEosazm/lSpUsU9t3r16gw3pQSdTZs29XQfLMMV8SICPhQgAIUPdwpVSg6B22+/3Ro2bGjP\nPfdchg1esGCBXXvtta7z/MknnzQNPFcEpZdfftlq166d4Xt5EQG/CRQoUMAUhCKjwUFEovPbXqM+\nCCAQDQF12nbr1u1g1lF15qrjQzcqlPFIWbk//vhjF2xKk8goCARZQJ9tZSXReWw4+ITas3//fpsw\nYYJt3LgxyM2j7ggggAACMRZQf8epp55qDz74YIZb0vnVmDFj3LIXXnih/fnnny5bgwYdqs+lcOHC\nGb6fFxEIgoAy7RQqVCjdqmpAlAKAURBAAIH0BNq0aZPeS+754447ztq3b5/hMryIQGoBDb6dM2eO\nTZw40TRAVwHAdO61devW1Iu5wboKWKHg6k2aNLFt27Yd8joPEEAAAQSSR0DBJ1q0aOGCFivhRlpF\n/cjvv/++1a9f3x03dK2jDFNz5861tm3bZjixP6318RwC8RbQmJ7SpUun+1n966+/XACveNeL7SGA\nQHIIaOyBxhykVzRhY8CAAZYvX770FuF5BHwtUKxYMbvvvvvcJA4lvPjoo4/cBBCNS9D5YnpFY2wV\nHLNu3bouoFl6y/E8AggggEByCiiBWOqx7Jqgrz5vXb8pAUaJEiWSE4ZWB1pAY5Rnz57txm1qnpHG\n0vz2228u6YX63xSQYuDAgYFuI5VHAIHkEFBAat0nSKtonkWzZs3sxBNPTOtlnkPgqAV0jqi5u8uW\nLbP//Oc/br6PAlHouZ9++inN9d9zzz0uOa3mCSu4OgWBRBJgdlsi7U3aEggBnQRdd911LsqgKjxs\n2LAj6v3PP//Yu+++a40bN7YaNWrYN998Ywo+8fPPP9vQoUOJqHmEGE8ESUAXA+qoS6vopicTJ9KS\n4TkEEAi6wB133OE6cnWMV9HPnTt32iWXXGJFixa177//3kXQDno7qT8COsZffvnlbjJK6uATYRkN\ngHriiSfCD/mJAAIIIIDAIQLKxBC+gaR+EA3uOLysXLnSbrnlFjvllFNM51gXXHCB/fDDDy7itAIe\nEszrcDEeB1lAkdWvueYa08/DS3hguf4WKAgggEB6AkWKFLFGjRqleXzUd0vnzp2ZgJIeHs9nKKBJ\nHsriMXz4cHvxxRetYsWK7n6XgoKp9O3b12WlUR+YsoG0bNnS9u7dm+E6eREBBBBAIPEEFDxSA0HD\nEwPHjx9v69evP9hQjZ149dVX7ayzznJJDDS58KuvvnKD9PQ+CgJBEdCA1EjBVM8+++ygNId6IoBA\nAAUaNGhgxx57bJo1V7Dmnj17pvkaTyIQJAEFUendu7etWLHCnUMqwISCS+g+0QcffHBIcgy1S1nA\nNRZx+/btdu6559p3330XpOZSVwQQQACBGAromDB16tQjxrKrn0ITBpX5et++fTGsAatGIHYCderU\nsXnz5rnxNvqsp56zod81LmfhwoWxqwBrRgABBKIgcPHFF6c7jkFj00l6HAVkVhFRQP3+Cj69dOlS\n++9//+uCPClBh+YEK0lauGjs6jvvvOMeKkmnglD8+uuv4Zf5iUDgBQhAEfhdSAOCJKCJExqUp4EV\n4Ql5mjihTgyVXbt2uYu6ypUru0n46jTXa4sWLbIePXpY3rx5g9Rc6opAmgKKplmgQIEjXtMNH10o\nnHDCCUe8xhMIIIBAkAVmzpxp48aNO6QjV+1RZ+6ePXvcRWbJkiWD3ETqjoAT0LmuAkkpkFo42Mrh\nNPrcK1v9jh07Dn+JxwgggAACSS5w7733usASYQYNCHzttdfcQ/WhqH+kdevWLquVOuyVsU2TVhRl\n+vTTTw+/jZ8IJJyAspTs37//iHapH0XZ2ygIIIBAJIErrrgizUzM+m7RzXIKAlkVUBATTfzQ4Ar9\nHDx4sDtXu//++11g9XBWGvUFzJ8/3y677LJ0M9VktQ68DwEEEEDAvwIa+6AgEhrwrmOBigLpPfbY\nY24AvAbraaDe1Vdf7a7rFyxYYO+9957Vq1fPv42iZghkIKDgbpUqVUoz+Nvxxx9v5cqVy+DdvIQA\nAggcnYCyG6cV0FkBm9X3zpjDo/Pl3f4SUN+4kmIoqdunn37qxiG2adPGTjvtNHvuuefc38K2bdvs\n6aefdn3r6p/YvXu3C1ShzPYUBBBAAAEE1JetCYVpFR03ZsyYYW3btk3z/Cqt9/AcAn4TmDx5sq1d\nuzbNMZy6RlAG9/BcJr/VnfoggAACEjjuuOPcveW0jte6R60kVRQE4iWgz+E1oQRSCkTx7LPP2uef\nf27VqlVzz2lO8KBBgw6eW+p+mJLPn3/++bZ58+Z4VZHtIBBTgRyhE8eUmG6BlSOAgBNQJ7aynM+e\nPfuQAXbqEFcU8nPOOcd1gKvjQgPLb775ZjdQDz4EElFA0WGVFe3wCRRvvvmmdejQIRGbTJsQQCBJ\nBXT8P/XUU11k7PQm5ItGHb6tWrVKUiWanSgCmmAycODAiM3R+a8ygSlrPQUBBBBAAAGdIyn72jPP\nPHPIDW7d9K5evbr16tXLnnzySdeBrwzuffr0MQ0k1PGEgkCyCGjgrLLMH16UUZ4JLIer8BgBBA4X\n2LRpk5188smHHGe1TJkyZdzgs8OX5zECWRX45ZdfXL/AlClT0uwL0/mdstE8//zzWd0E70MAAQQQ\nCIiAgk80bdrUBSAKB58IV12DQ4sUKWKaFKhxEf3797eKFSuGX+YnAoEWmDRpUprjHdSnpQmyFAQQ\nQCBWAgrWXLp06SNWX6xYMVu3bp2buHHEizyBQAIJLF682IYPH26vvPKKnXjiiVazZs0jMturX+LY\nY4+1jz/+2AWjSKDm0xQEEEAAgUwIKEP1mWee6ekdXbp0sZdfftnTsiyEgF8EvvrqK5cULxwkPK16\nKUiskr0oQS4FAQQQ8KuAklW1bNnykOopEIASJb7++uuHPM8DBOIpoGOs+h8eeOABUwCKtOYI6bOq\n5PQKVqF7YhQEAiwwOWeAK0/VEQiMgAZPXHDBBfbZZ58dEnxCDdCBR89PnDjxYPZOZYWuUqVKYNpH\nRRHIrIA65Q4PPpEvXz67+OKLM7sqlkcAAQR8LXDnnXeaBt+ndWEZrrg6c5W5WNEOKQgEWUCTh2+6\n6SYXxVODiNMrOv8dNmwYUeLTA+J5BBBAIIkElJFNmbAVGfrwGLk6f1q0aJH17dvX3RxfuHChG6iv\nm0gEn0iiDwlNdQIa+HH45/6MM84g+ASfDwQQ8CRw0kknuSDY6n8IF93sZlBZWIOf0RIoUaKEC7a+\nYcOGNPvCdH43fvx4u+eee6K1SdaDAAIIIOBDgZ07d1rjxo3TDD6h6ur6v1y5cvbTTz+5rNQEn/Dh\nTqRKWRZo3769m8ikCa7hoomuderUCT/kJwIIIBATgVKlSrlJ96lXru8iZWBU1lAKAokuoCDOCnip\noM2dO3d2mesPD4Smfgndl2rRooUpeCYFAQQQQCA5BYYMGXIwQ3V6AjqPKliwoMtcnd4yPI+AHwV+\n/fVXlzD38PE3h9dVr992221kZj8chscIIOArAQW5Lly48CF10nXeVVdddchzPEAg3gIaw3f11Ve7\nZFJKRq/xN4cXfVZXrFhhjULBqbdv3374yzxGIFAC/3fHK1DVprIIBEdAk07r169vCxYssMM7tcOt\n0AQ9Ze/s16+fFSpUKPw0PxFIWAGdRBUtWvRg+3TCpUlH3PQ8SMIvCCCQAAKzZ8+20aNHp3v8DzdR\nnbkakDlgwIDwU/xEIJACyqCjz/yaNWvcRCYd39PqVFHjtm7dahMmTAhkO6k0AggggEB0BJQNVYP8\n3nvvvTQnKGorOo60atXKTUjRZHsKAskqcOWVVx7SdP1taBAtBQEEEPAqoMCXqSfB6V5F165dvb6d\n5RDwJPDHH3+44BIZBWJVP9iDDz7o+g88rZSFEEAAAQQCJbBjxw4XfCKjsRE6D1HAyeOPPz5QbaOy\nCHgVeOSRRw7p61JiDg1CpSCAAAKxFqhXr56lDj6pe7fdu3eP9WZZPwK+EihZsqRVq1Yt3WQY6rPQ\nsbl169bu/pSvKk9lEEAAAQRiLrB06VKbNGlSmuM5dR6lf8WLF7fHHnvMNm7caDfccEPM68QGEIim\ngJLg6VxH5zzpjdsMb2/v3r0uCEX4MT8RQAABvwlokr/GS6VOiFigQAG78MIL/VZV6pOkAsuWLbN5\n8+aleW4pEt0P+/HHH61JkyZurlCSMtHsBBAgAEUC7ESa4F8BZe2oW7eurVq1Kt0DimqvC70XXnjB\ntm3b5t/GUDMEoiigwc6KPBe+GNCJ1eGTKaK4OVaFAAIIxF1gz549biJH6skdh1ci3MFbpUoVl3lE\n0bUpCCSCwCmnnGJjxoxx2UXC2brDn/dw+zThZOjQoUdkuw+/zk8EEEAAgcQW2Lx5szVs2NC++OIL\nO3DgQLqN1bXiBx984AZ3pLsQLyCQBAIaLK5gLLq5qqK/DQXypCCAAAJeBZSJOXzMVV/FBRdcYGXK\nlPH6dpZDwJOABuVq4rGX0qdPH3v99de9LMoyCCCAAAIBEVAGp8aNG9vChQszHBuh5vz55582bty4\ngLSMaiKQOQENgNY4ofA1vO6HnH322ZlbCUsjgAACWRBQAIrwOCxd+w8aNMjy5MmThTXxFgSCK6Dj\n7kMPPZThOAQto36ydu3a2cSJE4PbWGqOAAIIIJBpgQceeOCISfnh8Z1ly5a1//73v6YJ/Lfccovl\ny5cv0+vnDQhkt0Dt2rVN43EUaOXiiy92n3d9xsOf89T105iDl156yWbNmpX6aX5HAAEEfCXQpUsX\nN99SlVKfxxVXXGHHHnusr+pIZZJXQH1vh8+POFxDx9sffvjBmjVrZkroQUEgiAIEoAjiXqPOgRBQ\n1g7dVP7ll18iDrBQg3RQUccFBYFkEUh9MVC4cGFr2rRpsjSddiKAQBII3H333bZ+/fpDMhwpQnZ4\nsNlZZ51l999/vy1fvtwU/XDw4MFWrly5JJChickkUKpUKRs7dqytWbPGZdfR5z/c0aJBHQrW9v77\n7ycTCW1FAAEEEAgJrF271vWXLF682FN/ic6hmJTCRwcBs+uvv/7g5PGqVata5cqVYUEAAQQ8Cyj7\nowadqeh6jAyonulY0KOAsmk9+uij7vOV1kDGw1ejz6HuEcyYMePwl3iMAAIIIBBAAQWfaNSokRtE\np3EPkYom/Om4oUAUFAQSUeCRRx45eA2fP39+q1ixYiI2kzYhgIDPBOrUqWN//fWXq5Uyd6s/kYJA\nsgm89957LlGG+h0yKnpdfRmdO3e28ePHZ7QoryGAAAIIJIiAkom+8sorByexhsdxVq9e3QUk0us6\nfwoH9EqQZtOMJBTQxGwF2nrnnXdcMIqnnnrKjdERRXjsZphFfwe6Z6hkuhQEEEDAjwL169c3jXVQ\n0XeV7i9TEPCDwI8//mhvvfWWp2Oo7pvNnz/fFLxaSW4pCARNgAAUQdtj1DcQAl9//bU1aNDAtm3b\n5mkyhRqlQRZPPPFEINpHJRGIhoAGPIez7F155ZUHJ2VHY92sAwEEEMhOAWXyHjVqlDu2h6MHa+Kk\nAlMNHz7cTbr8/vvv7c4772TSWHbuKLYdNwEFotDE4dWrV7sbdbpxEb5ZN3To0LjVgw0hgAACCGS/\ngIJOaBCssoZ4mZCiGmu50aNHe14++1tJDRCIjYAylBQqVMitXINiKQgggEBmBTp16uTectxxx1n7\n9u0z+3aWRyBDAfWBaYDFwIED3edLgZJSD2TUgMfDA1Nookfr1q3dYIsMV86LCCCAAAK+FtCYiAsu\nuMAiBZrUsSB1ZrKtW7fat99+6+u2UTkEsiqgv4nGjRu7t9eoUcN0n5CCAAIIxFqgVq1aBzehBBip\nj7sHX+AXBBJc4Nlnn3Ut1Oc/PCYhoyYrEMU111xjmphJQQABBBBIbAGNUdP3frjfWmPYJ0+e7IJp\nXn755Uf0Xye2Bq1LFgGNL+jRo4d9+eWXLonYkCFDrFKlSq75OlfS/KWVK1e6cc3JYkI7EUAgeALd\nunVzlS5atKgLhB28FlDjRBTYuHGjFSlS5JCm6TxT/RFp3Q/QGNg5c+aYxv8RnP0QNh4EQCBH6ELq\niFCvvXv3tk2bNgWg+lQRAf8JKLvH9OnTXYTk8EEjjT8z14GhA4v+acBnnjx57IQTTrBq1ar5r1Ee\na1S4cGGX5TocFdTj2zK1GN9PmeLy/cKLFi0yRf5q0qSJnXjiib6vLxX0JtCyZcuYZlJYsWKF3Xvv\nve571luNWAqB+AnomP/RRx/Z7t273UaLFStmpUuXtlNOOcUd7+NXk8TZEucXibMvwy1R9M4lS5a4\nmxr6m2natOkRnTDhZfmJQLQFNOFpwIABdvrpp0d71W59a9assbvuuutgdruYbISVIhBQgT/++MM+\n+eQTF0gio/4SNU+d8brZrT4T9ZcUKFDAatas6atBH5os2bVr15jtjZtvvtl++eWXmK2fFQdTQIHs\ndE3cokULK1iwYDAbQa1jKqD+tTFjxsTs+/K1116zSZMmxbQNrDx2Auqr0GDKcuXKmQZWUoIncNFF\nF7lJEbGqebTvv+iaX+eAO3fudP927Nhh+qfnFHwiXHTOp2wfOu+jIHC0ArG+PxHtv5OjbS/vRyC7\nBfRdP23aNNMYibSKvtvz5s1r+fPnt3z58rnfU//U70EvfO8EfQ/Grv4KsqKxQ1WqVLGzzjordhti\nzdkuEOvvAcZHZPsuDlQFPvjgAzexUoPZDw8CGKiGUNmoCMT6+8mP10fqg9iyZYubzKEJHfqn8Qn6\nuW/fviPu4ep+lc5pVdRfpn4zCgLJJhDLcVk//fST3XPPPUf87SWbMe3NfoG9e/fahx9+6L7zixcv\nbtWrVzdNYqXEX0DnqIMGDbJTTz01Jhvn+skbqwLKrl271v3766+/3LWD7kGpH4+CQKwFYj1+U/V/\n+eWX7d133411U1h/nAR0f3nq1Kku6aeC/VISQyCW1yESitf4JgVz0lgc9T3oZ/jfrl273HP79+8/\nYoeVLFnSzj333COe5wkEslsgnXGHk48IQKETSN0E1gdZH2gKAghkTkAHieXLl7uJEvpbCk+W0M/U\nv4cnW2Ru7f5dWkFrZs2aZb///nvMAgnw/eTf/Z/VmqlTb9WqVTGbAJjVevG+rAsoU5FuxmkwTayK\nOgU00atDhw6x2gTrRSDLAroxreA6xx9/vDuX1rGfknUBzi+ybheEd6qTRTeby5cv7yYWB6HO1DH4\nArqxMHLkSOvZs2dMGqOMv5dddpn7l2jXfDEBY6VJJaBOdgUgDEd6DveT6Gc42ET4d7///cydO9dO\nO+00N0glFjtREzIV3LN+/fpWqlSpWGyCdQZUQOdPGgiiQVEUBA4X+PXXX+2zzz5zk7sV6DgWRec5\n+g6sV69eLFbPOuMgsHTpUhckU/0WlGAJzJs3zw2qmTJlSkwqHs/7L+o/0zEtHJhC9wkUJNBLZtKY\nNJ6VJoxArO9PxPPvJGF2Cg1JCoGFCxe6doYDS2iguv4pCYffr++PdgfxvXO0gon/fo0d0uQmgkgm\n7r6O9feA5Bgfkbifn1i0TH2HOgbru4eS3AKx/n4K6vWRJoaEA1OEfyowhX7XePmTTz45uT84tD7p\nBGI9LmvixInWqVMn69ixY9LZ0mB/Cei4pbEKZcuWtUKFCvmrcklWm7ffftvGjRtn3bt3j0nLuX7K\nHKvu1/z222/un5LoEig8c34snTWBWI/fVK0uvfRSU4KXunXrZq2SvMt3Akp6qOO4gl1Tgi8Q6+sQ\nCfllfFM4QIXGR4SDVOh4W7Vq1eDvSFqQUAIZjDucfEx6Lb3jjjusTZs26b3M8wgggMAhAjNmzHDZ\nqw95MkYP+H6KESyrRSAKAr169XJBeKKwqgxXoUlrr7/+eobL8CICCARfgPOL4O9DWoCA3wTilcFA\nAynILOW3vU99EIiewDXXXGObN2+O3grTWdNtt91G4L10bHgaAQSOFFDGB2U1jHVp0KCByxQQ6+2w\nfgQQOFRAgzF//vnnQ5+MwSPuv8QAlVXGTSBe9yf4O4nbLmVDCPhegO8d3+8iKohAzAXi9T3A+IiY\n70o2gEDCCcTr+4nro4T76NCgJBOIx7gsBSZknGeSfbBoLgIZCMQjQCPXTxnsAF5CwAcC8Rq/2bBh\nQ5swYYIPWkwVEEDgcIF4XIdom4xvOlyexwikL5DRuMOc6b+NVxBAAAEEEEAAAQQQQAABBBBAAAEE\nEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBA\nAAEEkkGAABTJsJdpIwIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCA\nAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJCBAAEoMsDhJQQQQAABBBBAAAEEEEAA\nAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE\nEEAAAQQQQCAZBAhAkQx7mTYigAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAII\nIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACGQgQgCIDHF5CAAEEEEAAAQQQ\nQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQ+H/sfQv8VcP6/ijp\nLpIiuUSllEg4Lh0kyaU6EYoiCsftdHCEcNz98DnkkvOnEg4h13IoJOVWrrnLXck1kVwSucx/nvme\nWd+1115r5l17r7W/a+/9zuez91pr1qy5PDPzrHfemXkXI8AIMAKMACPACDACjAAjwAgwAowAI8AI\nMAKMACPACDAC1YAAG6CohlrmMjICjAAjwAgwAowAI8AIMAKMACPACDACjAAjwAgwAowAI8AIMAKM\nACPACDACjAAjwAgwAowAI8AIMAKMACPACDACjAAjwAgwAowAI8AIMAKMACPACDACjAAjwAgwAowA\nI8AIMAKMACPACDACjAAjYEFgTcs9vpUhBMaNGycaNWokTjjhhFi5+uijj8TFF18sLrzwQtGuXbtY\nz8YJ/Msvv4gnn3xSvPrqq6JXr15ip512EvXq0eybzJgxQ3z//fdecp988ok46aSTRJMmTTw/c/LA\nAw+Ifv36aSyMnzn++OOP4u677xaLFy/W6fft21c0aNDA3OYjI1DVCFQyh5iKfe2118RTTz0l1lpr\nLbH//vvncd6XX34p3nnnHbHHHnuYR3KOzz//vOax+vXri8GDB4vNNtss5z4umGfyIGGPCkSgGvji\nm2++ERMnThRjx471avDFF18UH3zwgXftP4Fc0759e89ryZIlYt68ed71b7/9Jpo3by4GDRrk+eEk\njoyT8yBfMAIVhEAlc0qcPm4bx/irO0qeWbFihZg8ebIA/0DO6dOnj4DMwo4RqCYEmE9qanvVqlUC\nnPL555+LTp06if79+4c2gzB5BwF5TBMKF3syAnkIFKNTLZSv8jLh8Fi0aJF45JFHROPGjcV+++0n\nWrdu7Xii5jZ1PGMiK1Q+AV9Nnz7dRJNzbNq0qRg4cGCOH18wApWMQKG8UAwXxcGzmPkdk04UV+A+\nRe/KYx6DJB+TQKAa+lyx8j5FjuCxQxKtkeMoFoFq6M9R71BXH4wjb7viKrae+HlGIIsIVDN/oD4o\nMripN9c6CoSjznGYOPnICFQaAswp7vVUFN0Cj/0rrWdweZJCoBgdYKH8FDfvFD2CLU7b/KaLG+Ks\n55o/f76YNWuWXjeO9eM77rijLVt8jxGoOASqmU+oXEHVkcQZU1VcQ+ICVSUC1cwfqHDMuUD3gbUU\n3bt3F3vvvbdo1qxZZFuI0unigbjrMSIT4RuMQEYQKHTMUQyvxCk6RR/hii+qT8flBqSDPa3Yh8Zj\nERfqfD9tBKq57waxjeqXcfiDMo8STLeirmXAKfCkKqBUAlTgDl/WJQJdu3aVf/rTn2Jn4Z577tH1\nOXPmzNjPUh9YunSpVJsy5aRJk+SyZcvkmDFjpNoUJX///XdnFG+//bZcY401dB7R7vAbOnRo3nMP\nPfSQ7Nmzp76/fPnyvPtqU7ns0KGDVJvA5A8//CDvuOMOuckmm0hlFCMvLHukg8Djjz+u6+frr79O\nJwEVK/NT4dBWKocAEfDOqFGj5L777is//vjjPJC++uor+Y9//EOqDRly9OjReffhccopp8hhw4ZJ\nZQBHLly4UB588MHyoIMOkn/88YcXnnnGg8J6ctxxx8k999zTGqbYm1OmTJHK0Eix0fDzEQhUMl+Y\nIitDEbJNmzbmUvf1LbbYIkceMXIJjgsWLPDC4gSyiv8+ZBnINH5HlXH8z/B5PgIsX+RjUm4+lcop\n1D7uGseY+rTJM0qJKcFRhx9+uH7HKkN/UiknzaN8jInAeuutJ6+//vqYT9GD33vvvfodQRkP02Pl\nkECg2vkEGEybNk2qiU550003OXUuQXkHz/OYBigk40aMGCHVhv9kIguJBRwCeROcwq5uEChGp1oo\nX8Up6WWXXSaVgU357rvvyqefflp26dJFKqOcpCgo4xlEVKx8cuutt+aMm/xjqAEDBpDyyoHiIfDo\no49qzL/77rt4D8YIrYy2yiFDhsR4goMCgUJ5oRguoiJfzPwO0rBxBe5T9K485gFSbgcduFrw5g5Y\nYIhKmn+p5D5nqrcYeZ8iR5Tr2CHt+YlK6iemLWX9WMn92fYOpfRBqrxNiSvr7SDL+WPeyW7tVCt/\noEYoMjjCUdZRUOc4EF+1urR5ALjy+oi6b13MKfb1VBTdAo/9S9+O0+YnHh8lV6fF6AAL5ac4uafo\nEWzx2eY3XdyAtZvU9VxYF9qiRQu9bhzzEVjLdfnll9uyxvcUAmmvy5o6daquCwa7NAhUK59QuYKq\nI6GOqUpTq5WXytprr633HKVVMh4/FYZstfIH0HrllVdkt27d5LPPPitXrlyp5QeszVIfBsoD06bT\nNYGp6zFM+Go8pr1+E5iqD6LovUHViG/SZS50zFEMr1DLQNFH2OKy9ek43GDSUAaxpPqIeqrrk01a\n5X5MexwCfKp9fVO19t1g34jql1T+oMyjBNMs12vLusMZIlgoVgwGEcnGtbK4KH/66aeCMoOXYloO\nC+J79eqlBTSThvoKuNx0003lGWecYbwij8ccc4ycO3eu3jSOjePK4ptU1m5zwsMfv0MPPVQvoA0z\nQIGN51h853fYDPDnP//Z78XnKSJQCgGA+anwCqxUDlHWtWWrVq3k8OHDI8F54YUXpLJKp/kjzACF\nslSr74F/jFMW97TiG+3aOOYZg4T9mPYEJlJnBaG9Doq9W6l8YXCZOHGi7NixY44BCmX9XhuoAafg\nXWN+8FdWKM2j+rh48WI9IDXyCY7Kol1OGFxQZJy8h9gjDwGWL/IgKTuPSuUUSh83PGEbx6BCXfIM\njCVg4YVxF154oZZdnnnmGePFxxgIpD2BwQYoYlRGzKDVzCeA6rTTTtNG9V5//XUncmHyDh7iMY0T\nOnIANkBBhqqsAxaqUy2GryiAPfzwwxIGqV5++WUvOAwD4x0Hw5o2Rx3PJCGfHHjggXLOnDnaWLAZ\nY+EIfe0tt9xiyybfKxABy0RQgTHmP1btE7T5iNB8iuGFQrmIkrNi53dcXEHVu/KYh1JbUs+BsQEK\nGlaV2udM6YuR96lyRLmOHdKen4Asg00s/CEP0xrTP1Zqf3a9Qyl9kCpvU+JKvyYrNwXmnezWbbXy\nB1UGR8251lFQ5ziy2wpKk7O0eQCl4PURpalLWyrMKdHrqai6BR7721pYOvfS5iceHyVbb4XqAIvh\nJ0oJqHqEqLhc85subqCu57rvvvvkySefLLF2HRvRZ8+eLVu2bCnXXHNN+eGHH0Zlj/0VAmmvy2ID\nFKVvZtXIJ1SuoOhI4oypSl+7lZEiG6DIbj1WI39gPLPNNtvI008/Padi8HGwvn375vi5dLoITF2P\nkRNxFV6kvX4TkLIBiuQaVjFjjkJ5hZJ7qj4iKi5bn47DDSZ+4IQPuWMeEeMcdnYE0h6HIPVqX99U\njX032Oqi+mUc/nDNowTTLOdry7rDGfUUubErAwSaNm0qGjduXFBO1ebsgp6jPKS+rCfUxiehNmB5\nwevXry/UQnxx3XXXCWUFzvMPnqjNmkJtnBAdOnQQm2yyif5tvPHGolGjRjlBzT21ATTH33/xxRdf\niLfeesvvJRo2bCiUojvHjy8YgWpFoBI5ZPXq1eKQQw4RarJA3HDDDZFVu8MOO4jOnTtH3lcWKvW9\nhQsXemHAH3B+DmGe8eDhkwpHoBL5wlTZe++9J5RFStG/f3/jpY/NmjUTV111lYCssdZaa3k/tZBY\nqMFnTliE22effUTr1q09+aVNmzY5YagyTs5DfMEIVCgClcgp1D5OGce45Bnc79evn5Z3TBM54ogj\n9KmakDNefGQEqgKBauaT6dOniyuuuEJcc801Yuutt7bWd5S8g4d4TGOFjm8yAnkIFKpTLYav8jIR\n4qG+NiZ69Oihf+a2Mswp1KSJmDx5svEKPVLGM0nIJ4jjzDPPFL179xYYb5lx1rfffivUxIxQk/2h\n+WNPRqBSESiGFwrlIgqWxczvuLgC6VP0rjzmodQUh4mLQCX2OYNBsfI+VY7gsYNBnI91jUAl9mfK\nO9TVB+PI26646rqOOX1GIC0EqpU/KDK4wdy1joIyx2Hi4iMjUOkIMKdEr6ei6BZ47F/pPYTLlwQC\nheoAi+EnSr6peoSwuFzzmxRuoK7nUl8s13OpWLu+xhpriD59+oghQ4YIZZBCqK+dhmWP/RiBikWg\nGvmEyhUUHUmcMVXFNiIuWNUiUI388dxzzwn1kdOctRdoAMoAhXjsscfEggULdHug6HQRkLIeQ0fI\nf4xAGSFQzJijUF6hwEPRR0TF4+rTVG7wxz927Fhx9tln+734nBGoUwSqse8GAY/ql3H4wzWPEkyz\nUq/ZAEVGanb+/Pni4osvFhdddJFQFkOE+sJtTs6++uorcdNNN+X4qS/a6c0HymKrePPNN8Ull1wi\nbrvtNoFr43A+d+7c1JRo06ZN00kFN0B069ZNG5+YOXOmyUrecfz48UJZihQwOrH55psL9eU7oSy9\n5IWjeKgvfAi85JXVdx0cC66RN2XVlvI4h2EEyhoBtHdlJU3g5QieAB8oi0w5ZQpyCJTrGBgry2Hi\np59+EnfddZdQX9MWWLzod1nmEAjomCBQVicFhKNCnfpqnN4Mce6554rly5fraMCl4DVslDCOecYg\nwcdyRqBa+QJ19uuvv4pzzjlHXH755XlVuPPOOwv1BeEcf/Df/fffL9D3jcNmKWzoguGtddZZRwwd\nOlQsWbLE3PaOSco4XqR8wghkFAEexxQ3jnHJM9is2b59+5zahxE/GNIJjsFyAvEFI1CGCDCfhPPJ\nZ599Jo466iix6aabilGjRllr1ibv4EEe01jh45tVhoCLc8L0IRRdLGAM6mCShPbrr78WTz/9dJ4c\nAIO+W2yxhbj77rsjk6OOZ5KQTyDDYAIm6DDG2m233cS6664bvMXXjEBZI+DilDBeoHBKGBclCVQx\n8zsurkA+KXpXHvMkWaPVERfrN8P1m6h9l7wfR45wxVUdrY1LmTYC1dqfKe9QVx+MI2+74kq7njl+\nRiAtBFgGD18fQZHB06oTjpcRKGcEmFMK5xSKboHH/uXcOzjvSSDg4pgwHSBFd4i8hekdk8gz4oij\nRwimSZnfpHADdT0X1o/C+ITfmY8T8XyEHxU+L3cEmE/C10tQuYKiI+ExVbn3Es5/FALMH+H88e67\n72rIgnvYzFoHfKgZjqLTpa7H0BHyHyOQEQR4niZ8HxqVG0w1QjfSqVMn0bVrV+PFR0YgdQRc7/Yw\nfQFF1xCmo0iyMBRdYlR6lPexedbWL4vJg4m/2o5rVluBs1hebFKcNWuWuPfee7URBQxesZkaltNg\nkOKtt94So0ePFk2aNBEjR47URXjwwQf1xoNly5Zpow3YhIRzbKz89NNP9Ub0hQsXivPOO0/Hi83p\nRhAOYgBrjR999FHQO+caVmF33XXXHD9cvP/++9pvww03zLmHr4LDBTez+wNhsTE2R8D6LAxRYEPF\n7bffLh555JE8ZaD/ubDzY489Vj97+OGHi5dfflljNmHCBHHAAQeEBWc/RqBiEMBgdaeddhI33nij\nwNew0QewKQn9HX0WX8mFMQU/h+CZE044QUydOlUMGzZMG61Yf/319fUNN9ygDVi0bNlSUDkEfTho\n8CIIMDZLwdhM0BXDIXfeeadYc801xRtvvCH23HNP/QXN7bbbTlx99dUCR6oDt4JrTznlFI3bYYcd\nJhYtWiTmzJkjsIHDOOYZgwQfyxWBauYL1BmM7MAwVfPmzUlVOG/ePG0VHxMUxkFugcEv8B7uw3gP\nZDLIcPvuu68JpjdUJSXjeJHyCSOQQQR4HFP8OCaOPIOJjnvuuUdccMEF2mhhBpsEZ4kRKBgB5pNo\nPnn44YfFihUrxPbbby8wVsHGc4yDMP6DEb0GDRp4uLvkHR7TeFDxSZUjYOOc//u//9O6gKBOlaKL\nhW4kqIOJgrpQXQp0uJjoCepikQ70sZhcgswAXW7QUcczaconGDsdcsghwazxNSNQ1gjYOKWS53co\nXEHVu5oGwGMegwQfoxBg/aZdv+mS9+PIEa64ouqI/RkBKgLV3J8p79BC+2CYvF1oXNS65HCMQF0g\nwDJ49PqIuDJ4XdQfp8kIZA0B5pTiOCXuui8e+2etB3B+0kbAxjGVPB8RZ34TdRCHG8LWc2Hta9Bh\nYw2MT2BtLTtGoBIQYD5xr5fw13MYV1B0JDym8qPI55WCAPNHNH80btxYV/NLL70kDj30UK/K8fEP\nOPOBQopOl7oew0uETxiBOkaA52mi96FRuQFViP24+BgP1ot9//33dVyrnHy1IGB7t1f7OiW0AVe/\njKvPrJZ2ZS2nUtzkuF9++UWqB+QDDzyQ488X6SDw3XffSbXBWd58881eAgMGDJDqq9pSLSb2/JTV\nRdmmTRvvGidnnnmmrqvZs2d7/mrTtezZs6d3rQxT6DDKAIXnFzwZN26cDoN6j/qpDQ3Bx/Q10lOW\nY/PuvfDCCzquE088Me9emMerr74qO3furJ+59NJLw4LIsWPH6vvLly8Pva+s80gl7OswarOo/PLL\nL0PDsWc6CDz++OMae2X5OJ0EVKzMT/nQol8o4w7ejQULFuh6uOqqqzw/nAQ5ZNWqVTpc7969pRrw\n6rD//e9/tZ/aVOE9S+GQtddeWz8XxR/wVxu2vTj9J4VyiDK0o9Pcdttt5TfffKOjVJbmpNqAIZs1\nayZx3+9M21GGOPzeOedXXnmljlNt5pKTJ0/OuWcumGcMEtHH4447TiqDINEBErgzZcoUqaygJxBT\ndUVRrXyBWn7iiSfk+eef71W4MjiTJ1d5N/938re//U3a5Bhw51lnnSXr1asnN9hgA6kUMcEo9DVF\nxgl9kD01AixfZLch8Dimpm4ofTxqHBNHnlGWhuUxxxwj1USnllcwXsSYi118BNZbbz1pGx/HjzH3\nCbXQX9eR2oSce4OvIhFgPqmBJopPjj76aN2mzBjl559/1jIIxlmQaYyjyjs8pjGIFXccMWKE3G+/\n/YqLxPI0OAR1DE5hlywCVM4J04dQdLHIbVAHE1aCQnUpRnejDM7kRYs2iXajjBTn3Qt6RI1n0pRP\nli5dqsfyrLMN1kZy148++qhuA2jnabnBgwfLIUOGpBV92cVL5ZQwXqBwShgXBUGqi/mdOFyB/FL0\nrjzmCdZs/rUyPC2VAfv8Gwn5GB16lueHWb/p1m/a5P24coQtroSaXeLRpD0/UQ79JHFQU4qwWvtz\nnHdo3D5ok7fjxpVStVdktMw7pa9WlsFp6yMoMjhqz7zbbOsoouY4Sl/72UwxbR5AqXl9RHp1z5xS\nPKfEWffFY//02nJYzGnzk3mHZFmPEIZLKf2oHBOmA6ToDlGWML1jsIx1MR9Bnd9EXuNyg2s9lyk/\n1sWqD5mZSz5GIJD2uiz1kTypjKZHpM7eVASYT4S3pjtqvUQQyyiuoOpIqGOqYLp87UYA76VJkya5\nAxYYgsdPucAxf9j5QxmY0GsYsP/Ov3dvxowZet792muv1XtSsA6DumcFNRC1HiO3dqr3Ku31m0B2\n4MCBUn2ot3pBJpSc52midSIUbgDE4A1lvMbbuwrOBV+kuT6ZULVlESTtcQhAqNT1TdR3e5i+gKJr\nCNNRBBtVltcpUfplHH0mym50YLZ5lCBG5XhtWXc4o54iN3Z1iMBnn30m1GBYqMUGXi522WUX/XVL\npVjz/Bo2bOidmxNjVUkZbjBeYquttvIsrcEz7Dkv8P9O1CBb/PTTT9afIqjgY/pabfQO9ccX/+DU\nhszQ+0HPbbbZRqiN86Jdu3YCFuIKcWozhth9993FyJEj9ZfJ//SnP+VgUUic/AwjkHUEPvzwQ6E2\nFojVq1frrKIvNW3aVMCCs98FuUAZvtFfw4SFRnw9Fw78AWesNeI8+Bz8gk5tHLDyB/jl9NNPDz6m\nrwvlkJdfflk/P2jQINGyZUt93qlTJ6EEGQHuVEJ7aHpRnvjy13333ScmTJggYBFbLebVXxcPhmee\nCSLC1+WEQLXyBb4Yft1114mzzz6bXF1K4NecoAaekc+AO5VxHaEmKwV4cO7cuaFhk5BxQiNmT0ag\njhHgcUxNBRTTx+PIM5DvJk6cKH744QehDI3p4wknnFDHrYCTZwSSQYD5pAbHKD4BVyijoOKII47Q\nATFGg5XiLl26CFgyVsYFtQ6JKu/wmCaZdsuxlC8CaXMOkElTl2L0KGqxXl4lQB+LtPFFL5eLGs+k\nKZ9MmzZNf2lMGVl2ZY/vMwJlg0DanELhk7qY34nDFVS9K495yqbZ12lGWb/p1m/a5P24coQtrjpt\nCJx4RSBQrf05zjs0bh+0ydtx46qIRsaFqFgEWAZ3r4+gyuAV20i4YIxADASYU4rnFDPOCMIetnaU\nx/5BlPi60hFIm2OAH0V/WOjaTtO/C5mPoMxvmvqPww2U9VyIVxlGEepDZuLvf/+7SYaPjEBZI8B8\nYl8vEaxcG1dQdCQ8pgoiytfljADzh50/Nt54Y3HxxRfrfWxHHXWUmDlzplAGaMR5552nqx1rueLo\ndE1biVqPYe7zkRHIAgI8TxOtE6FwA+oQa7mVAQrB66Cy0KKrJw9pv9speoYsr1Oi9Euj7wi2mjB9\nZjBMtV6zAYo6rnkYj4Cia9asWV5O1Ncp9GLc5s2be37Uk/r16wsMnOM4CLgwZuH6hcWJFys6mLLm\nknMbG6PgzIb2nJsRF+prvuIvf/mLeP/99yNCRHvffPPN4q677tKbx6EcwA+kqr5cHv0Q32EEKgAB\nZalZG3945plndGm+/fZbbYyib9++sUsH/oCLyyEu7sB98EyYK5RDWrRooaNr1apVTrQ777yzvn7n\nnXdy/G0XKG+fPn3EqaeeKo499lihvjysOfj8888XL730kvco84wHBZ+UKQLVyhfqy+Bihx12EOoL\nf+L+++/XP8gaMACG6zlz5uTV6Lx58zSX7rbbbnn3gh7qy6+iXr16VvmlGBknmB5fMwJZQYDHMbU1\nUWgfL0SeAd+cfPLJQlkmFa+88kreOKw2V3zGCJQPAswntXUVxifgCvz8YypwAYxu/vbbbwKTQVR5\nh8c0tVjzWfUikAXOAfqF6lKgR4FbuXKlPvr/oI+FcU6j3/HfizoPjmfSlE/uueceYTPyF5VH9mcE\nsoxAFjilLuZ3qFxB1bv665jHPH40+DyIAOs37fpNl7wfR45wxRWsG75mBOIiUK39mfoOLaQPRsnb\nhcQVtz45PCNQSgRYBrevjyhEBi9l/XFajEDWEGBOKZ5TCln3xWP/rPUEzk9aCGSBY1C2upiPwNgH\nP9v8ZhB3CjdQ1nNhTdhNN92kf8E0+JoRKFcEmE/i8UkUV1B0JDymKtdewvmOQoD5w80fY8aMEU88\n8YTYaKONBPbjYA/OZpttpmWZHj166CPwLWTPSnA9RlQ9sT8jUBcI8DyNXSfi4ob33ntP3HvvveLX\nX3/19qdgrwoc1nZjj8oXX3xRF1XLaVY4All4t2d1nRK1Xxaiz6zwZuUsXviOYOdjHCApBGAd9qGH\nHhIHHXSQwAuqZ8+e4oMPPhC33357Ukk443nxxRfF7NmzreGwcPn000/PC4MvbsJ98sknokOHDt79\nr7/+Wp/HMUCBB0CEWCgd1/3nP/8R++67r6ewHDlypN44DkMU+PL5OuusEzdKDs8IlAUCRx99tOaM\n448/XltgnDt3rrj00kvFPvvsU7L8jxs3zrn5cffddxe77LJLXp4K5RDDEwsWLMiJc5NNNtFfB45j\nwOfJJ58Un376qYdZ69attcDfrl07gcVa22+/vU6DeSYHar4oQwSqlS+WLVsmHnvssZwa++6777Tx\nntGjR4uuXbuKPffcM+c+FAIwikXZuLX++uuLli1bOuWXQmWcnIzxBSOQIQR4HJNbGYX08WLkmb32\n2ktA7qNYGs3NKV8xAtlDgPkkt06CfAKuQH9fsmSJwHjHuC222EKfYuxDlXd4TGPQ42M1I5AFzgH+\nhepSMAGCr4FBFxt00MdiAUQcFxzPpCWfIG/Qv2BhFztGoJIQyAKn1MX8DpUrqHrXsDbBY54wVNiP\n9Zu1bSBMv+mS9+PIEa64eN61ti74rDAEqrU/U9+hcfugTd6OG1dhNcpPMQKlQ4BlcPv6iGJk8NLV\nIqfECGQHAeaU4jml0HVfaAU89s9OX+CcpINAFjgGJauL+QjK/GYU6jZucK3nwlpxfHTs1ltv5bUU\nUQCzf1kiwHxiXy8RrNQorqDoSHhMFUSTr8sdAeYPGn9gnwt+cIsWLdIfPPzXv/4lsCaLqtMNayvB\n9RhhYdiPEagrBHiexq4TQb3YuAHrNLCeE3tRjIMhK7i7775bzJgxQ39YHR+sZ8cIJIlAFt7tWV2n\nhH2hlH5ZjD4zybosp7jYAEUGagtfuDzuuOP0RkdYfR06dGhJc2UsvNgShXWaMAMUo0aNEhdddJGA\ntUi/AQpsCt922209gdsWt//etGnTNA5+P8r566+/LoLGLrBx9PrrrxdLly5lAxQUEDlMWSKAvgmh\nFFabYVlx4MCBJVeeT58+PfTLm35A27RpE2qAolAO2WCDDUS/fv3Ec889509GwII1rMjtuuuuOf62\nizfeeEP88ccfAl8KxSYOOGC64447auHDPMs8Y5DgY7kiUK18AUNfQQeZBpONGGQEHQb/mISYNGlS\n8FboNSzegkN69eoVet94FirjmOf5yAhkEQEex9TWSiF9vBh55q233hIDBgyozQCfMQJljgDzSW0F\nBvlkxIgRYsKECXrs4zdAsXDhQgGjefCjyjs8pqnFmc+qG4G65hygX6guBcanoEvBRCXGIfgiGNz3\n33+vdSIwShrHBcczackn4LbttttOYOMrO0ag0hCoa06pi/kdKldQ9a5hbYLHPGGosB/rN2vbQJh+\n0yXvb7nllmQ5whUXG6CorQs+KwyBau3P1Hdo3D5ok7fjxlVYjfJTjEBpEWAZvBbv4PqIYmTw2lj5\njBGoLgSYU2rruxBOKXTdF1LlsX8t9nxWuQjUNccA2bqYj6DMb0bVehQ3uNZz/fTTT3qN+zXXXON9\nqRxp4KvDWBdqNo9Gpcv+jEDWEWA+eS7ngx3+9RL+urNxBUVHwmMqP5p8XikIMH/Q+AP1vXr1ajFk\nyBCB+ZQTTjhBNwGqTjesvQTXY4SFYT9GoK4Q4Hka+j60MG7Ax0+D+1AwJsF+NKzdwh5hdoxAWgjU\n9bs9q+uUqP1ym222SXQvfFr1nKV4a1aoZilHVZYXvIj23ntv/ZKBkuvbb7/VLyFj+cjA8csvvwh8\nzea3334zXnphMS4Qh3H4ugXCmudxDgf/KDds2DABgxG23/PPPx/6OATqk046ScDCm0nz559/Fg8+\n+KC21mQWQePhN998U/Tu3VvMnz9fgGxOPvlk8corr3jxQnG4cuVKcc4553h+/hNgA4f4g27QoEEC\nCyuw8No4bEzv3r276Nixo/HiIyNQcQjAyAo2SsPoArgA1prAJUEX5JAff/xR99kgf+C5VatWeY9T\nOOSpp56y8ge4ZeTIkV6c/pM4HIIFlbC0Z9yVV16pv/gJTjEOXwaGNaojjzzSeOmjjT/AwWuttZbm\nEPMQuAicddBBBxkvwTzjQcEnZYpANfNFnCp79tlnBTiyT58+eY9dccUV4oYbbhBQEMBB9sH1xIkT\ntREg+BUi4+A5doxAuSHA45hkxjEueQZy2SWXXKLlEtNGvvnmGz2Ouuqqq4wXHxmBskaA+cTOJzvv\nvLPAIq1bbrnF07tAN/T000+Lyy67TMCiMdXxmIaKFIerZATicA5w8OtUYeQBLqhL8eticT+og4Ff\n0BWjSzn11FO1Dvm+++7zor3rrru03uLAAw/0/HDi16VQxjN4Jg355J577hGDBw9G9OwYgYpCIA6n\nVNL8DirRxRUIQ9G78pgHSLGjIsD6TTtSFHmfKkdQ4rLnhu8yAnYEqrk/U96hcfugTd6OG5e95vgu\nI1D3CLAM/olec2VqIrg+giKDm2dxtK2jMOEoYUxYPjIC5YYAc0rxnEJZ98Vj/3LrGZzfpBCIwzFI\ns5LmIyjzm3G5wbaeC2tnsc4TH3CbOnWquO666/TvwgsvFIcffrho3759UtXK8TACdYIA8wl9vYSN\nKyg6krhjqjppEJwoIxADAeYPOn9g78gxxxyj5YbZs2cLbM43jqLTpa7HMHHykRGoawR4nsauEzH1\nY+MGE4aPjEApEYjzbq/GdUqUuqDoM/3x8ByJQkNtnMtxaoGshPcDDzyQ488X6SCgFF9yt91205gD\nd/Nr0aKFnDx5slQbHOW1114r11tvPX1PLRqWS5culU888YTcfPPNtZ/akC2VlVZ55513yrXXXlv7\nnX/++VJZTJNKqaavu3XrJtUXMVMphDL6IM844wzZv39/ndexY8dK9VXxvLSUYk/nZfz48VJtSJco\nI8qrjFLo5y+//HJd3uCDX375pVSbq2Tr1q11+COOOELOmjUrJ5h6qUtlUVuinFdffbUEJgMHDpQf\nffRRTji+SA+Bxx9/XNePUoSnlgjzUz60yvCKVFbSNPaGP3Dca6+9NC+EcQj6xejRo/Uz6sUplcEY\n+dlnn8kDDjhA+ylrTvKll16SyohLpjikc+fOmgfUZisPiNdee02qTeLy3HPPlWpzpuahzz//3LuP\nk5kzZ0pljVKXDTwyadIkjY0/0COPPCK7du0qleEKzTfgJXCv3zHP+NGIPlfW+qSyHBYdIIE7U6ZM\nkcpoSAIxVVcU1c4X/toeM2aMbNOmjd/LO1cGsuTw4cO9a/+JmpTUXNKyZUupDHDJU045RXOlP0wc\nGcf/HJ+HI8DyRTguWfDlcUwy4xjUpU2eUQZxZI8ePaTaYC532GEH+c9//lOqL3ZIZXAsC82gLPOA\nsbVSnqeWd2UcTr8rfv/999TSqLSImU/cfIIxEPRBGNdAp3LwwQfLCRMmWJtCmLzDYxorZLFuKqMg\ncr/99ov1TJzA4BCM7cEp7JJFwMU5SC1MH0LRxSoDFaF63GRLUBObMpopd999d61THTdunMQ4Bvrh\noPPrUijjGfN8kvIJdIVqcYb84IMPTPR8TAmBRx99VHOHmkBMKQUplSER/T5KLYEyi9jFKWG62UqY\n3zHVZOMKE8ald+Uxj0HKfcQcmFr86g5YYIhymH9h/WZt5RYj71PkiHIdO6Q9P1EO/aS2lWT7rNr7\ns+sdGqcPuuTtOOZWgJwAAEAASURBVHFlu9VkM3fMO6WvF5bB3esjXDK4qTXXOgrKWi0TVzUf0+YB\nYMvrI9JrYcwpyXCKa+0oj/3Ta8O2mNPmJx4f2dCvuefiGISq1PkIlM01vxmXG2zruYYOHap14/71\ns+Ycc6zsohFIe10W9g1gvQu74hBgPqGvl7BxBVVHQh1TFVer1fs09jphHX9ajsdPucgyf7j5A/pV\n7NvbZZdd5P33358LoO/KpdONsx7DF21Vnqa9fhOgYi+h+lB3VeJLLTTP09h1IlRu8OMNWQPjkDTX\nJ/vTK+fztMchwKZS1ze53u28Tim3Z0T1S5c+08Timkcx4SrhaFl3OEOP6hXBeQ6WUBo2bCiUAQqh\nXrqeP5+kg4BSxIpzzjlHnHjiiQJfssWX9GDZVU3kCVhfff/990WDBg3SSTzhWNXieG2FV23ojIz5\nk08+ERtvvLG+j7IvWbJENGnSRGy00UaRz8S5oYhSfPzxxwLWaNZdd904j3LYIhGYM2eO/lq8ErSE\nGhQUGVv448xP+bg89thjQhmPEL169dK8gT6gXpBCbVIRW2+9tTjzzDPzH8qoj4tD1KSDUMJSaN9W\nRidE48aNQ+9Ri6te+BpLcNNmm20m6tevH/oo80woLJ7n8ccfL9577z2hBgWeX9Int99+uxg5cqT+\nqmzScVdyfMwXtNpdtGiRUEruyHfZV199pWU2WMdv1KhRaKRpyDihCVWBJ8sX2a1kHsckO45BTdvk\nmRUrVghlfEmPnbLbKsojZ/jqycUXXyzUoqtUMoyv0ePrKpBt69Wrl0oalRYp8wmdTzAmhh5FGSQt\nqn3xmKb4XqSMF4ply5aJGTNmFB9ZSAxKwa3HpBjbq8mQkBDsVSgClcQ5wAB6OGXkN1J/HNSlUMYz\nfmyTkE+gp4K+dquttvJHzecpIKCMNot+/foJWLDHuDYNBzkHX3vBV+TYCa2bqtb5HX/927gC4Sh6\nVx7z+BENP1eG1wXm2NSkb3iAIn3LYf6F9Zu0SqbK+y45AqlR46LlLP1Qac9PlEM/SR/lZFLg/lyD\no+sdSumDVHmbElcytVtdsTDvlL6+K2lc71ofAXT9a6z8aLv4gyKD++Pj88IRSJsHkDNeH1F4/bie\nZE6pQSgpTnHxGo/9XS0y2ftp8xOPj9z1VUkcg9K69AjB+QiDkGt+k8oNrvVcJj0+xkMg7XVZd911\nlzj00EMF5j7ZFY4A80kNdi4+QSgKV1B0JDymKry9up7E3PaVV14pMOeRhuPxUy6qzB81eNj4Y/r0\n6aJ79+56LVYueuFXtvFT3PUY4SlUvm/a6zeB4F/+8hfRvHlzoYzSVD6gBZaQ52lqgIvq03G5ocBq\nqNrH0h6HANhKXd9USe92ly4R9VjoHAmepThKHijxVEIYy7rDmWtWQgHLuQzK0pnYeeed9WZnbHj2\nu+XLl+vFnH6/LJ9js7bN+ATyboxP4ByGTjp27IjTxByMWXTp0iWx+DgiRiDLCCxYsEBg0ws2IKH/\ndejQwctu7969xd133+1dl8OJi0OaNWsWWYy2bdtG3qPeUJaWRbt27ZzBmWecEHGADCLAfEGvFBiW\nsLnWrVsL/GwuDRnHlh7fYwTqAgEexyQ7jkEd2uSZddZZpy6qmdNkBEqCAPMJnU9giMY/7iu0gnhM\nUyhy/FwlIFBJnIP6wMS8zQV1KZTxjD++JOSTpk2bsvEJP6h8XlEIVBKnuHSzqDj//I6/Im1cgXAU\nvSuPefyI8nkYAqzfDEMl3I8q77vkCMROjSs8J+zLCIQjwP25FhfXO5TSB6nyNiWu2pzxGSOQXQRY\nBq+pGxd/UGTw7NYy54wRKB0CzCk1WCfFKS7dAo/9S9e2OaVsIFBJHANEXXqE4HyEqQXX/CaVG1zr\nuUx6fGQEKhEB5pOaWnXxCUJRuIKiI+ExVSX2pOosE/NHTb3b+GPQoEGxGodt/BR3PUashDkwI5Ag\nAjxPUwtmVJ+Oyw21MfIZI5AuApX0bnfpEoFkoeuUqLVAyQM1rkoOxwYo6rh2n3/+efHFF19oIxSd\nO3fWBifwMp8/f77Ycsst9cK8Os4iJ88IMAIZReD111/X/HHjjTeKvfbaS2y66aZi8eLF4oUXXhC4\nN3bs2IzmnLPFCDACpUaA+aLUiHN6jEDlI8DjmMqvYy4hI1AqBJhPSoU0p8MIMAJAgDmH2wEjwAgk\niQBzSpJoclyMgB0B1m/a8eG7jEA5IcD9uZxqi/PKCGQPAZbBs1cnnCNGoJwRYE4p59rjvDMC2UeA\nOSb7dcQ5ZATKBQHmk3KpKc4nI5A9BJg/slcnnCNGIAsI8DxNFmqB88AIFIYAv9sLw42fKg6BesU9\nzk8Xi8CMGTNEx44dxdChQ0XLli1Fly5dxB133CEGDBggDjzwwGKj5+cZAUagghE48sgjxRVXXCGm\nTp0qunbtKmANGtasfvzxR3HhhReKFi1aVHDpuWiMACMQBwHmizhocVhGgBGgIMDjGApKHIYRYAQo\nCDCfUFDiMIwAI5AUAsw5SSHJ8TACjAAQYE7hdsAIlA4B1m+WDmtOiRFIGwHuz2kjzPEzApWNAMvg\nlV2/XDpGoNQIMKeUGnFOjxGoLgSYY6qrvrm0jECaCDCfpIkux80IVDYCzB+VXb9cOkagUAR4nqZQ\n5Pg5RqDuEeB3e93XQTXmYM1qLHSWytytWzdx00036SytXr1arLXWWlnKHueFEWAEMozAGmusIU49\n9VT9+/XXX0WDBg0ynFvOGiPACNQlAswXdYk+p80IVCYCPI6pzHrlUjECdYEA80ldoM5pMgLViwBz\nTvXWPZecEUgDAeaUNFDlOBmBcARYvxmOC/syAuWIAPfncqw1zjMjkB0EWAbPTl1wThiBSkCAOaUS\napHLwAhkFwHmmOzWDeeMESg3BJhPyq3GOL+MQHYQYP7ITl1wThiBLCHA8zRZqg3OCyMQDwF+t8fD\ni0MngwAboEgGx0RiScr4BDaiP/XUU+Khhx4Sffv2Ffvtt18i+UszkgceeED069dPNGrUKC+ZX375\nRTz55JPi1VdfFb169RI77bSTqFevXl44eHz55ZfinXfeEXvssUfofeO5atUqgTQ///xz0alTJ9G/\nf39zK+f42muvaSxRN/vvv79o165dzn2+YASygkAWjE8sWbJEf/VvwYIF4sYbb8wKNHn5+Oabb3T/\nR36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MWVBlmdKUilNhBApHwNVHmXeisU1SL0iJixImOrd8hxFIHwHmk8Ixpqy/QuyUOUhq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"text/plain": [ "" ] }, "execution_count": 91, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Image(filename='dt.png')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Too big! Need to depth limit the tree." ] }, { "cell_type": "code", "execution_count": 92, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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Q5uRcg/akcltwlLakuBIuvXry/S84t0TN4h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\nU0eNRbM/1cvP+al+bkXhJbfccovr/3rvK5xB39u77rrLW2XRH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mTbK5c+eG+zRq1MjatWsXft4cC2rnvv/++66t2759e2vbtm3GM5zRPtoc3xjnRAABBBBAAAEE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\nGIxlM2fOtHnz5plmBd5hhx2sXLl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y8uijj5qXvXwfiPu///s/0wmi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\nAoo8efKI9kEGTtoPGW5AMC3v+/ykDiAwb948v2r++usvOXbsmNx7772iCfN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3b5ZGjRq5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IvuX6ZMGXn66aelX79+0qtXL/XCm0XFZ1FJgARIgARIgARI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\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GvI/4M8oT7mVLlixxqlWr5tSrV88xiyb0/N577+2sXr3aTfPUU0/FXG/zwbZbt26a7p9/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ZSUoz0f9XoOGbkm/1vCyzlbPM97vJ7P6NpF/Q/pnY96dYrm+agXS6lHqnt430U6347mfolUJ6+e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\nR36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MWVBlmdKUilNhBApHwNVHmXeisU1SL0iJixImOrd8hxFIHwHmk8Ixpqy/QuyUOUhq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"text/plain": [ "" ] }, "execution_count": 92, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dt = DecisionTreeClassifier(max_depth = 4)\n", "dt.fit(X.values, Y)\n", "with open(\"dt.dot\", 'w') as f:\n", " export_graphviz(dt, out_file=f, feature_names=X.columns)\n", "os.system('dot -Tpng dt.dot -o dt.png')\n", "Image(filename='dt.png')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## How good is the tree? Let's try cross validation." ] }, { "cell_type": "code", "execution_count": 93, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/usr/local/anaconda3/lib/python3.5/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n", " \"This module will be removed in 0.20.\", DeprecationWarning)\n" ] } ], "source": [ "from sklearn import cross_validation" ] }, { "cell_type": "code", "execution_count": 94, "metadata": { "collapsed": true }, "outputs": [], "source": [ "scores = cross_validation.cross_val_score(dt, X, Y, cv = 10)" ] }, { "cell_type": "code", "execution_count": 95, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 0.55516556, 0.53703054, 0.57891658, 0.53749854, 0.56370656,\n", " 0.5525392 , 0.53850655, 0.56537516, 0.54512466, 0.56584338])" ] }, "execution_count": 95, "metadata": {}, "output_type": "execute_result" } ], "source": [ "scores" ] }, { "cell_type": "code", "execution_count": 96, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.55 (+/- 0.03)\n" ] } ], "source": [ "print(\"Accuracy: %0.2f (+/- %0.2f)\" % (scores.mean(), scores.std() * 2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Again, the question is \"how good is that\"? What would you get by random guessing?" ] }, { "cell_type": "code", "execution_count": 97, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "1 46415\n", "0 17356\n", "3 12766\n", "2 8917\n", "dtype: int64" ] }, "execution_count": 97, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.value_counts(Y)" ] }, { "cell_type": "code", "execution_count": 98, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "0.5431577222833337" ] }, "execution_count": 98, "metadata": {}, "output_type": "execute_result" } ], "source": [ "46415. / len(Y)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The answer is that we're doing no better than random guessing! Maybe try a deeper tree." ] }, { "cell_type": "code", "execution_count": 99, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 0.55 (+/- 0.02)\n" ] } ], "source": [ "dt = DecisionTreeClassifier(min_samples_split = 100)\n", "scores = cross_validation.cross_val_score(dt, X, Y, cv = 10)\n", "print(\"Accuracy: %0.2f (+/- %0.2f)\" % (scores.mean(), scores.std() * 2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Ugh!" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## What is that called?" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [conda env:anaconda3]", "language": "python", "name": "conda-env-anaconda3-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 0 }