diff --git a/Level 1/Intermediate/women_representation_in_sanfrancisco/dataset/WomenRepresentaionInCityProperty-SanFrancisco.csv b/Level 1/Intermediate/women_representation_in_sanfrancisco/dataset/WomenRepresentaionInCityProperty-SanFrancisco.csv new file mode 100644 index 0000000..4655e6f --- /dev/null +++ b/Level 1/Intermediate/women_representation_in_sanfrancisco/dataset/WomenRepresentaionInCityProperty-SanFrancisco.csv @@ -0,0 +1,83 @@ +Department/Source,Name,Person,Gender,Reference,Comments,Current Police Districts,Current Supervisor Districts,Analysis Neighborhoods,Neighborhoods,SF Find Neighborhoods +Administrator,MOSCONE CENTER (South),George R. Moscone,M,City Administrator,,4,10,36,21,21 +Administrator,Maxine Hall Health Center,,F,Public Health,,4,10,36,21,21 +REC AND PARKS,Moscone Recreation Center,George R. Moscone,M,,park,4,10,36,21,21 +REC AND PARKS,"Helen Crocker Russell Library of Horticulture, Golden Gate Park",Helen Crocker,F,,facilities and other amenities,4,10,36,21,21 +REC AND PARKS,"Sharon Building, Golden Gate Park",Sharon Building,M,,facilities and other amenities,4,10,36,21,21 +Administrator,Priscilla Chan and Mark Zuckerberg San Francisco General Hospital and Trauma Center,Priscilla Chan and Mark Zuckerberg,F & M,Public Health,,4,10,36,21,21 +Administrator,Fay Park Garage,Mary Fay Berrigan,F,Municipal Transportation Agency,,4,10,36,21,21 +REC AND PARKS,Minnie & Lovie Ward Recreation Center,Minnie & Lovie Ward,F & M,,park,4,10,36,21,21 +Administrator,Stanford Chlorine Plant,"Leland Stanford, Jr.",M,Public Utilities Commission,,4,10,36,21,21 +AIRPORT,Berman Reflection Room,Henry Berman,M,Airport Commission President,,4,10,36,21,21 +REC AND PARKS,"De Young Museum, Golden Gate Park",M. H. de Young,M,Newspaper,facilities and other amenities,4,10,36,21,21 +REC AND PARKS,"Lou Spadia Clubhouse, Jackson Playground",Lou Spadia,M,,facilities and other amenities,4,10,36,21,21 +REC AND PARKS,Betty Ann Ong Chinese Recreation Center,Betty Ann Ong,F,,park,4,10,36,21,21 +Administrator,Curtis E. Green LRV Facility Geneva Site,Curtis E. Green,M,Municipal Transportation Agency,,4,10,36,21,21 +Administrator,Wattis Founders Room,Phyllis C. Wattis,F,Davies Symphony Hall,,4,10,36,21,21 +PUC,O’Shaughnessy CONF ROOM,Michael O’Shaughnessy,M,,"Civil Engineer, Developed Hetch-Hetchy Water System",4,10,36,21,21 +Administrator,Eureka Valley Branch Library/ Harvey Milk Memorial Branch Library,Harvey Milk,M,Public Library,,4,10,36,21,21 +LIBRARY,Richmond/Senator Milton Marks Branch Library,Senator Milton Marks,M,,Library,4,10,36,21,21 +REC AND PARKS,"Elsa Strait Room, Eureka Valley Recreation Center",Elsa Strait,F,,facilities and other amenities,4,10,36,21,21 +Administrator,Elizabeth Murray Performers' Lounge,Elizabeth Murray,F,Veterans Building,,4,10,36,21,21 +Administrator,H. WELTON FLYNN DIV.,H. Welton Flynn,M,Municipal Transportation Agency,,4,10,36,21,21 +REC AND PARKS,"Mary Margaret Casey Recreation Building, Sunnyside Playground",Mary Margaret,F,,facilities and other amenities,4,10,36,21,21 +Administrator,Flynn Tire Shop,H. Welton Flynn,M,Municipal Transportation Agency,,4,10,36,21,21 +SFMTA,Scott Garage,William H. Scott,M,General Manager of San Francisco's Municipal Railway in its most difficult period,Different name in SF Data,4,10,36,21,21 +Administrator,Tom Waddell Health Clinic,Tom Waddell,M,Public Health,,4,10,36,21,21 +Administrator,SFO International Terminal Departure Hall - Mayor Edwin M. Lee,Edwin M. Lee,M,Airport (Sfo),Mayor,4,10,36,21,21 +Administrator,Charlotte and George Shultz Horseshoe Drive,Charlotte and George Shultz,F & M,War Memorial Opera House,,4,10,36,21,21 +Port,James R. Herman Cruise Terminal at Pier 27,James R. Herman,M,Port,,4,10,36,21,21 +RED,The Board of Supervisors Committee Room 263,John L. Taylor,M,Clerk to the Board of Supervisors,,4,10,36,21,21 +RED,Grand Staircase in the Rotunda,"Charlotte Maillard Shultz,",F,,2010 - Chief of Protocol for the City and County of San Francisco (and the State of California),4,10,36,21,21 +Administrator,Walter and Elise Haas Grand Lounge,Walter and Elise Hass,M & F,Davies Symphony Hall,,4,10,36,21,21 +REC AND PARKS,"Harvey Milk Center for Recreational Arts, Duboce Park",Harvey Milk,M,,facilities and other amenities,4,10,36,21,21 +Administrator,Anna E. Waden Branch Library (Bayview)- Bayview Linda Brooks-Burton Branch Library,Anna E. Waden,F,Public Library,,4,10,36,21,21 +Administrator,JASON G. YUEN ARCHITECTURE & ENGINEERING BUILDING - 676,Jason G. Yuen,M,Airport (Sfo),,4,10,36,21,21 +LIBRARY,Syncip Family Conference Room,Syncip Family,F & M,,4th floor,4,10,36,21,21 +Administrator,Harry Tracy Water Filtration,Harry Tracy,M,Public Utilities Commission,,4,10,36,21,21 +REC AND PARKS,Gene Friend Recreation Center,Gene Friend,M,,park,4,10,36,21,21 +Administrator,John M. Bryan Education Studio,John M. Bryan,M,Veterans Building,,4,10,36,21,21 +Administrator,Harvey Milk Terminal - Terminal 1,Harvey Milk,M,Airport (Sfo),,4,10,36,21,21 +Administrator,Harold L. Zellerbach Rehearsal Hall,Harold L. Zellerbach,M,Zellerbach Rehearsal Hall,,4,10,36,21,21 +Administrator,Ella Hill Hutch Community Center,Ella Hill Hutch,F,City Administrator,,4,10,36,21,21 +LIBRARY,Mary Louise Strong Conference Room,Mary Louise Strong,F,,1st floor main library,4,10,36,21,21 +Administrator,Moscone West,George R. Moscone,M,City Administrator,,4,10,36,21,21 +REC AND PARKS,Frank Tatum Clubhouse,Frank Tatum,M,Harding Golf Course,facilities and other amenities,4,10,36,21,21 +Administrator,J. Woods Cable Car Carpentry Shop,J. M. Woods,M,Municipal Transportation Agency,,4,10,36,21,21 +Administrator,Balboa Reservoir,Vasco Nύnez de Balboa,M,Public Utilities Commission,,4,10,36,21,21 +Administrator,Moscone Esplanade Ballroom,George R. Moscone,M,City Administrator,,4,10,36,21,21 +REC AND PARKS,"McLaren Lodge, Golden Gate Park",McLaren Lodge,M,,facilities and other amenities,4,10,36,21,21 +Administrator,Bayview Opera House Ruth Williams Memorial Theater,Ruth Williams,F,Arts Commission,,4,10,36,21,21 +Port,Pier 52 Boat Launch - Corrine Woods,Corrine Woods,F,Port,,4,10,36,21,21 +Administrator,J.M. Woods Div-Wash/Warehouse,J. M. Woods,M,Municipal Transportation Agency,,4,10,36,21,21 +Administrator,Curry Senior Center,"Francis J. Curry, M.D.",M,Public Health,,4,10,36,21,21 +Administrator,De Young Museum,M. H. de Young,M,Fine Arts Museums,,4,10,36,21,21 +LIBRARY,Chinatown/Him Mark Lai Branch Library,Him Mark Lai,M,,Library,4,10,36,21,21 +Administrator,Flynn Pumping Station,Bruce Flynn,M,Public Utilities Commission,,4,10,36,21,21 +SFMTA,Richard Gamble open space at the west end of the Sunset Tunnel,Richard Gamble,M,,Not in SF Data,4,10,36,21,21 +LIBRARY,Koret Auditorium,Koret (Family?),F & M,,Family,4,10,36,21,21 +SFMTA,Cameron Beach Yard,"Cameron Beach, Transit board member",M,,Not in SF Data,4,10,36,21,21 +Administrator,Veterans Building - Herbst Theater,Herman and Maurice Herbst,M & M,Veterans Building,,4,10,36,21,21 +REC AND PARKS,Joseph Lee Recreation Center,Joseph Lee,M,,park,4,10,36,21,21 +REC AND PARKS,"Mark Bingham Gym, Eureka Recreation Center",Mark Bingham,M,,facilities and other amenities,4,10,36,21,21 +Administrator,Jeannik Mequet Littlefield Intermezzo Lounge,Jeannik Mequet Littlefield,F,War Memorial Opera House,,4,10,36,21,21 +Administrator,Thomas J. Cahill Hall of Justice,Thomas J. Cahill,M,City Administrator,,4,10,36,21,21 +Administrator,M. L. King Childcare Center,Martin Luther King,M,Public Works,,4,10,36,21,21 +LIBRARY,Fulton Conference Room,Fulton (family?),F & M,,Family,4,10,36,21,21 +Administrator,Dianne and Tab Taube Atrium Theatre,Dianne and Tab Taube,F & M,Veterans Building,,4,10,36,21,21 +REC AND PARKS,"Thelma and Henry Doelger Primate Discovery Center, SF Zoo",Thelma and Henry Doelger,F & M,,facilities and other amenities,4,10,36,21,21 +Administrator,Louis M. Davies Symphony Hall,Louis M. Davies,M,Davies Symphony Hall,,4,10,36,21,21 +LIBRARY,Martin Paley Conference Room,Martin Paley,M,,main library 3rd Floor,4,10,36,21,21 +Administrator,Sojourner Truth Child Center,Sojourner Truth,F,Public Works,,4,10,36,21,21 +Administrator,J.M. Woods Div-Operators,J. M. Woods,M,Municipal Transportation Agency,,4,10,36,21,21 +REC AND PARKS,(Josephine Dow) Randall Museum,Josephine Dow,F,,park,4,10,36,21,21 +Administrator,Diane B. Wilsey Center for Opera,Diane B. Wilsey,F,Veterans Building,,4,10,36,21,21 +Administrator,Brooks Hall,Thomas A. Brooks,M,City Administrator,,4,10,36,21,21 +LIBRARY,Noe Valley / Sally Brunn Branch Library,Sally Brunn,F,,Library,4,10,36,21,21 +Administrator,Fire Chief's Residence,Dennis T. Sullivan,M,Fire Department,,4,10,36,21,21 +Administrator,MOSCONE NORTH,George R. Moscone,M,City Administrator,,4,10,36,21,21 +Administrator,MOSCONE CENTER Parking Garage,George R. Moscone,M,Municipal Transportation Agency,,4,10,36,21,21 +RED,"City Hall, 2nd Floor, Buck Delventhal Rotunda",Buck Delventhal,M,Longtime Deputy City Attorney,,4,10,36,21,21 +PUC,Alex Pitcher Community Room,"Alex Pitcher, Jr.",M,,Civil Rights Attorney,4,10,36,21,21 +Administrator,Curtis E. Green LRV Facility Annex Bldg,Curtis E. Green,M,Municipal Transportation Agency,,4,10,36,21,21 +Administrator,Bill Graham Civic Auditorium,Bill Graham,M,City Administrator,,4,10,36,21,21 diff --git a/Level 1/Intermediate/women_representation_in_sanfrancisco/women_representation_in_san_francisco.ipynb b/Level 1/Intermediate/women_representation_in_sanfrancisco/women_representation_in_san_francisco.ipynb new file mode 100644 index 0000000..19b3f20 --- /dev/null +++ b/Level 1/Intermediate/women_representation_in_sanfrancisco/women_representation_in_san_francisco.ipynb @@ -0,0 +1,1200 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exploratory Data Analysis(EDA) on the proportion of women to men representation in City-Owned Buildings in San Francisco" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In October of 2018, the Board of Supervisors passed and Mayor London N. Breed signed, the Ordinance 243-18 (http://bit.ly/2LSqS3U) to expand the extent to which women are represented in the public sphere, including within artwork, statues, street names, facilities, parks, and more. The representation of women in City-owned buildings includes buildings, conference rooms, clubhouses, museums, recreation centers, community rooms, auditoriums, terminals, departure halls, 7 staircases, rooms, and other places open to the public. The City Administrator's office was responsible for compiling a list of all city owned buildings named after a man or woman. You can read the accompanying report on the representation of women in city property here: http://bit.ly/2YIDCz7\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "#importing relevant libraries\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "#reading the csv file into a dataframe\n", + "data = pd.read_csv('dataset\\WomenRepresentaionInCityProperty-SanFrancisco.csv')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Department/SourceNamePersonGenderReferenceCommentsCurrent Police DistrictsCurrent Supervisor DistrictsAnalysis NeighborhoodsNeighborhoodsSF Find Neighborhoods
0AdministratorMOSCONE CENTER (South)George R. MosconeMCity AdministratorNaN410362121
1AdministratorMaxine Hall Health CenterNaNFPublic HealthNaN410362121
2REC AND PARKSMoscone Recreation CenterGeorge R. MosconeMNaNpark410362121
3REC AND PARKSHelen Crocker Russell Library of Horticulture,...Helen CrockerFNaNfacilities and other amenities410362121
4REC AND PARKSSharon Building, Golden Gate ParkSharon BuildingMNaNfacilities and other amenities410362121
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" + ], + "text/plain": [ + " Department/Source Name \\\n", + "0 Administrator MOSCONE CENTER (South) \n", + "1 Administrator Maxine Hall Health Center \n", + "2 REC AND PARKS Moscone Recreation Center \n", + "3 REC AND PARKS Helen Crocker Russell Library of Horticulture,... \n", + "4 REC AND PARKS Sharon Building, Golden Gate Park \n", + "\n", + " Person Gender Reference \\\n", + "0 George R. Moscone M City Administrator \n", + "1 NaN F Public Health \n", + "2 George R. Moscone M NaN \n", + "3 Helen Crocker F NaN \n", + "4 Sharon Building M NaN \n", + "\n", + " Comments Current Police Districts \\\n", + "0 NaN 4 \n", + "1 NaN 4 \n", + "2 park 4 \n", + "3 facilities and other amenities 4 \n", + "4 facilities and other amenities 4 \n", + "\n", + " Current Supervisor Districts Analysis Neighborhoods Neighborhoods \\\n", + "0 10 36 21 \n", + "1 10 36 21 \n", + "2 10 36 21 \n", + "3 10 36 21 \n", + "4 10 36 21 \n", + "\n", + " SF Find Neighborhoods \n", + "0 21 \n", + "1 21 \n", + "2 21 \n", + "3 21 \n", + "4 21 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#printing the first five rows\n", + "data.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 82 entries, 0 to 81\n", + "Data columns (total 11 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Department/Source 82 non-null object\n", + " 1 Name 82 non-null object\n", + " 2 Person 81 non-null object\n", + " 3 Gender 82 non-null object\n", + " 4 Reference 54 non-null object\n", + " 5 Comments 32 non-null object\n", + " 6 Current Police Districts 82 non-null int64 \n", + " 7 Current Supervisor Districts 82 non-null int64 \n", + " 8 Analysis Neighborhoods 82 non-null int64 \n", + " 9 Neighborhoods 82 non-null int64 \n", + " 10 SF Find Neighborhoods 82 non-null int64 \n", + "dtypes: int64(5), object(6)\n", + "memory usage: 7.2+ KB\n" + ] + } + ], + "source": [ + "#information on the data\n", + "data.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The Reference and Comments columns contain a lot of missing data but cannot be dropped, as we have a small dataset. We can not also perform imputation because these are actual places and we might distort facts about these places." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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count82828182543282.082.082.082.082.0
unique8826952113NaNNaNNaNNaNNaN
topAdministratorJ. Woods Cable Car Carpentry ShopGeorge R. MosconeMMunicipal Transportation Agencyfacilities and other amenitiesNaNNaNNaNNaNNaN
freq461653911NaNNaNNaNNaNNaN
meanNaNNaNNaNNaNNaNNaN4.010.036.021.021.0
stdNaNNaNNaNNaNNaNNaN0.00.00.00.00.0
minNaNNaNNaNNaNNaNNaN4.010.036.021.021.0
25%NaNNaNNaNNaNNaNNaN4.010.036.021.021.0
50%NaNNaNNaNNaNNaNNaN4.010.036.021.021.0
75%NaNNaNNaNNaNNaNNaN4.010.036.021.021.0
maxNaNNaNNaNNaNNaNNaN4.010.036.021.021.0
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" + ], + "text/plain": [ + " Department/Source Name \\\n", + "count 82 82 \n", + "unique 8 82 \n", + "top Administrator J. Woods Cable Car Carpentry Shop \n", + "freq 46 1 \n", + "mean NaN NaN \n", + "std NaN NaN \n", + "min NaN NaN \n", + "25% NaN NaN \n", + "50% NaN NaN \n", + "75% NaN NaN \n", + "max NaN NaN \n", + "\n", + " Person Gender Reference \\\n", + "count 81 82 54 \n", + "unique 69 5 21 \n", + "top George R. Moscone M Municipal Transportation Agency \n", + "freq 6 53 9 \n", + "mean NaN NaN NaN \n", + "std NaN NaN NaN \n", + "min NaN NaN NaN \n", + "25% NaN NaN NaN \n", + "50% NaN NaN NaN \n", + "75% NaN NaN NaN \n", + "max NaN NaN NaN \n", + "\n", + " Comments Current Police Districts \\\n", + "count 32 82.0 \n", + "unique 13 NaN \n", + "top facilities and other amenities NaN \n", + "freq 11 NaN \n", + "mean NaN 4.0 \n", + "std NaN 0.0 \n", + "min NaN 4.0 \n", + "25% NaN 4.0 \n", + "50% NaN 4.0 \n", + "75% NaN 4.0 \n", + "max NaN 4.0 \n", + "\n", + " Current Supervisor Districts Analysis Neighborhoods Neighborhoods \\\n", + "count 82.0 82.0 82.0 \n", + "unique NaN NaN NaN \n", + "top NaN NaN NaN \n", + "freq NaN NaN NaN \n", + "mean 10.0 36.0 21.0 \n", + "std 0.0 0.0 0.0 \n", + "min 10.0 36.0 21.0 \n", + "25% 10.0 36.0 21.0 \n", + "50% 10.0 36.0 21.0 \n", + "75% 10.0 36.0 21.0 \n", + "max 10.0 36.0 21.0 \n", + "\n", + " SF Find Neighborhoods \n", + "count 82.0 \n", + "unique NaN \n", + "top NaN \n", + "freq NaN \n", + "mean 21.0 \n", + "std 0.0 \n", + "min 21.0 \n", + "25% 21.0 \n", + "50% 21.0 \n", + "75% 21.0 \n", + "max 21.0 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#summary statistics\n", + "data.describe(include=\"all\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "M 53\n", + "F 19\n", + "F & M 8\n", + "M & F 1\n", + "M & M 1\n", + "Name: Gender, dtype: int64" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#counting the number of buildings owned by each gender\n", + "data['Gender'].value_counts()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Some buildings are co-owned by both male and female(F & M), (M & F), there is a building co-owned by both males (M & M).\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Department/SourceNamePersonGenderReferenceCommentsCurrent Police DistrictsCurrent Supervisor DistrictsAnalysis NeighborhoodsNeighborhoodsSF Find Neighborhoods
5AdministratorPriscilla Chan and Mark Zuckerberg San Francis...Priscilla Chan and Mark ZuckerbergF & MPublic HealthNaN410362121
7REC AND PARKSMinnie & Lovie Ward Recreation CenterMinnie & Lovie WardF & MNaNpark410362121
26AdministratorCharlotte and George Shultz Horseshoe DriveCharlotte and George ShultzF & MWar Memorial Opera HouseNaN410362121
30AdministratorWalter and Elise Haas Grand LoungeWalter and Elise HassM & FDavies Symphony HallNaN410362121
34LIBRARYSyncip Family Conference RoomSyncip FamilyF & MNaN4th floor410362121
56LIBRARYKoret AuditoriumKoret (Family?)F & MNaNFamily410362121
64LIBRARYFulton Conference RoomFulton (family?)F & MNaNFamily410362121
65AdministratorDianne and Tab Taube Atrium TheatreDianne and Tab TaubeF & MVeterans BuildingNaN410362121
66REC AND PARKSThelma and Henry Doelger Primate Discovery Cen...Thelma and Henry DoelgerF & MNaNfacilities and other amenities410362121
\n", + "
" + ], + "text/plain": [ + " Department/Source Name \\\n", + "5 Administrator Priscilla Chan and Mark Zuckerberg San Francis... \n", + "7 REC AND PARKS Minnie & Lovie Ward Recreation Center \n", + "26 Administrator Charlotte and George Shultz Horseshoe Drive \n", + "30 Administrator Walter and Elise Haas Grand Lounge \n", + "34 LIBRARY Syncip Family Conference Room \n", + "56 LIBRARY Koret Auditorium \n", + "64 LIBRARY Fulton Conference Room \n", + "65 Administrator Dianne and Tab Taube Atrium Theatre \n", + "66 REC AND PARKS Thelma and Henry Doelger Primate Discovery Cen... \n", + "\n", + " Person Gender Reference \\\n", + "5 Priscilla Chan and Mark Zuckerberg F & M Public Health \n", + "7 Minnie & Lovie Ward F & M NaN \n", + "26 Charlotte and George Shultz F & M War Memorial Opera House \n", + "30 Walter and Elise Hass M & F Davies Symphony Hall \n", + "34 Syncip Family F & M NaN \n", + "56 Koret (Family?) F & M NaN \n", + "64 Fulton (family?) F & M NaN \n", + "65 Dianne and Tab Taube F & M Veterans Building \n", + "66 Thelma and Henry Doelger F & M NaN \n", + "\n", + " Comments Current Police Districts \\\n", + "5 NaN 4 \n", + "7 park 4 \n", + "26 NaN 4 \n", + "30 NaN 4 \n", + "34 4th floor 4 \n", + "56 Family 4 \n", + "64 Family 4 \n", + "65 NaN 4 \n", + "66 facilities and other amenities 4 \n", + "\n", + " Current Supervisor Districts Analysis Neighborhoods Neighborhoods \\\n", + "5 10 36 21 \n", + "7 10 36 21 \n", + "26 10 36 21 \n", + "30 10 36 21 \n", + "34 10 36 21 \n", + "56 10 36 21 \n", + "64 10 36 21 \n", + "65 10 36 21 \n", + "66 10 36 21 \n", + "\n", + " SF Find Neighborhoods \n", + "5 21 \n", + "7 21 \n", + "26 21 \n", + "30 21 \n", + "34 21 \n", + "56 21 \n", + "64 21 \n", + "65 21 \n", + "66 21 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#the buildings owned by both male and female\n", + "data[(data['Gender'] == 'F & M') | (data['Gender'] == 'M & F')] " + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "M 0.646341\n", + "F 0.231707\n", + "F & M 0.097561\n", + "M & F 0.012195\n", + "M & M 0.012195\n", + "Name: Gender, dtype: float64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#counting the number of buildings owned by each gender\n", + "data['Gender'].value_counts(normalize=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These nine buildings form 10% of our dataset and will be dropped as they do not distinctly represent male or female. Most of the buildings represent families or husband and wife. The M & M building will be taken to represent male gender M." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "data = data[(data['Gender'] == 'F') | (data['Gender'] == 'M')]\n", + "data['Gender'] = data['Gender'].replace('M & M', 'M')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "M 53\n", + "F 19\n", + "Name: Gender, dtype: int64" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data['Gender'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#plotting a pie chart to show the distribution between male and female\n", + "plt.figure(figsize=(12,8))\n", + "plt.pie(data['Gender'].value_counts(), labels=['Male', 'Female'], autopct=\"%0.1f%%\")\n", + "plt.title(\"Distribution of Male and Female\")\n", + "plt.show()\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "74% of the buildings are named after males and only 26% named after females. This doesnt portray a great representation of females." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Departments and Female-Named Buildings" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Department/Source Gender\n", + "AIRPORT M 1\n", + "Administrator F 10\n", + " M 31\n", + "LIBRARY F 2\n", + " M 3\n", + "PUC M 2\n", + "Port F 1\n", + " M 1\n", + "REC AND PARKS F 5\n", + " M 10\n", + "RED F 1\n", + " M 2\n", + "SFMTA M 3\n", + "Name: Name, dtype: int64" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rep_in_departments = data.groupby(['Department/Source', 'Gender']).Name.count()\n", + "rep_in_departments" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "sns.catplot(data=data, x='Department/Source', col='Gender', hue='Gender', kind='count', aspect=2)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Departments such as AIRPORT, PUC, SFMTA do not have buildings named after females. The Administrator Departments boasts the highest female named buildings with 10. REC AND PARKS has 5, LIBRARY 2, Port and RED with one each. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Referenced by and Female-Named Buildings" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Municipal Transportation Agency 9\n", + "City Administrator 8\n", + "Public Utilities Commission 4\n", + "Veterans Building 3\n", + "Public Health 3\n", + "Airport (Sfo) 3\n", + "Public Works 2\n", + "Public Library 2\n", + "Davies Symphony Hall 2\n", + "Port 2\n", + "Harding Golf Course 1\n", + "Fine Arts Museums 1\n", + "Clerk to the Board of Supervisors 1\n", + "Airport Commission President 1\n", + "Longtime Deputy City Attorney 1\n", + "Newspaper 1\n", + "Fire Department 1\n", + "Arts Commission 1\n", + "War Memorial Opera House 1\n", + "General Manager of San Francisco's Municipal Railway in its most difficult period 1\n", + "Zellerbach Rehearsal Hall 1\n", + "Name: Reference, dtype: int64" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data['Reference'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Veterans Building 2\n", + "War Memorial Opera House 1\n", + "Municipal Transportation Agency 1\n", + "Arts Commission 1\n", + "Davies Symphony Hall 1\n", + "Public Health 1\n", + "Public Library 1\n", + "Public Works 1\n", + "City Administrator 1\n", + "Port 1\n", + "Name: Reference, dtype: int64" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_female = data[data['Gender'] == 'F']\n", + "data_female['Reference'].value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Of the 21 References, only 10 references were female named buildings. " + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12,8))\n", + "sns.countplot(y='Reference', hue='Gender', data=data)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Comments and Female-Named Buildings" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "facilities and other amenities 3\n", + "park 2\n", + "2010 - Chief of Protocol for the City and County of San Francisco (and the State of California) 1\n", + "1st floor main library 1\n", + "Library 1\n", + "Name: Comments, dtype: int64" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_female['Comments'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "facilities and other amenities 10\n", + "park 5\n", + "Library 3\n", + "Not in SF Data 2\n", + "Different name in SF Data 1\n", + "1st floor main library 1\n", + "Civil Rights Attorney 1\n", + "Civil Engineer, Developed Hetch-Hetchy Water System 1\n", + "main library 3rd Floor 1\n", + "2010 - Chief of Protocol for the City and County of San Francisco (and the State of California) 1\n", + "Mayor 1\n", + "Name: Comments, dtype: int64" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data['Comments'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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S5ZIKkiTNdNtvulad9apHTHcYku6lXERbkjSMJAur6q8+HRqsQJIkSZIkSdIETCBJkiRJkiSplwkkSZIkSZIk9TKBJEmSJEmSpF4mkCRJkiRJktTLBJIkSZIkSZJ6mUCSJEmSJElSLxNIkiRJkiRJ6mUCSZIkSZIkSb1MIEmSJEmSJKnXatMdgCRJmtgaG2/D7MMXTHcYkiRJWkVZgSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkiRJkiRJUi8TSJIkSZIkSeplAkmSJEmSJEm9TCBJkiRJkiSp12rTHYAkSZrYVUtvYKfDTpjuMFYJC488YLpDkCRJmnGsQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkiRJkiRJUi8TSJIkSZIkSeplAkmSJEmSJEm9TCBJkyzJ3yQ5OcmPk1yZ5L+TPDLJJklOneDYZyV5U9s+IsmhY/Q5IsnPkywa+NpgOWN9dZIDlufYyZDk+CTXJLksyQ+TnJBk0yk4z/wk8yZ73FHnuHGY9iQHJvnIBGPtmeSxE/SZk+Ty5YltOmIY49hHJ1k08Hq/JH9Ksnp7vV2SxT3Hz03ytOU596hx3pLkiiSL28/SY5ZjjAOTbHJPY5EkSZJmstWmOwBpZZIkwBnAp6vqha1tLvDgqvohsE/f8VV1JnDmEKf6YFW9/x6GS1UddU/H6NPuR6rqjp5uh1XVqa3v64HzkmxbVX+eythmuD2BG4HvrsQxLAEemmTdqvoj8Fjg+8AOwEXt9fk9x88F5gH/PewJk6xWVbcNvN4VeAawY1XdmmRDYI1lvRDgQOBy4BfLcawkSZJ0r2AFkjS5ngD8ZTAxU1WLqurbg9UaSS5Mss1In1Yhs9MwlSHjaceenuSrSX6U5H0D+/6hVfjMT/LJkXMMVjm1fe9NclHr+7jWPivJkUkublUarxoY97CB9ne0tjlJrkryMeAS4CHDxF+dDwL/Bzy1jfWkJBckuSTJKUnWSfLUJF8YiGHPJF8er/8Y92m/JEuSXJ7kvQPtNyb5j3bsN5Js1Nof3u7pwiTfTrJVa9+8neviJO8a7l36q1g2SnJaG+PiJLslmQO8GjikVcQ8LsmDk5yRrlLrsoHKoFnt/bwiyTlJ1poJMbR7dsnAObZIsnDwvC2peDEwUvGzE/BRusQR7ft3k+yS5LtJLm3ft0yyBvBOYN8W375J1k5ybLuGS5M8u537wPYsfBk4Z9TlbwxcX1W3tpiur6pfJPm7JGcMxP/E9rM1K13V3OXtGTokyT50iawTWyxrpftZ/mZ7Zs5OsnEbZ36SDyb5VvsZ2bmN+6Mk/7qs750kSZK0IplAkibXtsDCCXvBycALANofl5tU1TDHjRj5w35RkvMG2ucC+wLb0f1x/ZB0U2veBvwt8ERgq55xV6uqXegqgd7e2v4B+H1V7QzsDLyyJU+eBGwB7NLOu1OSPdoxWwInVNUOVfWTZbgu6JJOW6WrBnkrsHdV7QgsAN4AfA342yRrt/77Ap/v6X+ndi/eC+zVYt45yXPa7rWBS9qx3xy4/qOB11bVTsChwMda+38BH2/35f96rmetgfdqEV3iY8R/0VWT7Qw8Dzimqq4Fjmrtc6vq28CHgG9W1aOBHYEr2vFbAB+tqm2A37Uxpj2Gqvox8Pt01XcALwOOHyOu7wKPbe/lHcB87p5AOp+uKmmPqtoBOBz4t1addjjw+Rbf54G3AOe263gCcOTAM7Ir8NKq2mvU+c8BHpIuYfqxJI9v7ecCjxpJIrb4j6N7Zjatqm2rajvguKo6le5Z27+q5gK3AR8G9mnPzLHAuwfO+eeq2qPd3y8Br6H7vXFgkgeOcY8kSZKkGcEpbNL0+AJdIuTtdImkU5bx+PGmsH2jqn4PkORK4KHAhnR/+P+mtZ8CPHKccU9v3xcCc9r2k4DtW6UFwPp0SYMnta9LW/s6rf2nwE+q6nvLeE0j0r7/LbA1cH4S6KYWXVBVtyX5KvDMdGtKPR14I/D4sfqPGntnYH5V/RogyYnAHsAX6RIYn2/9Pgucnq6C6bHAKW1MgPu277txV8LmM3SJqbHc3BILtHMeSFexArA3sPXA2OslWXeMMfYCDgCoqtvpkjP3B66pqkWtz+B7NhNiOAZ4WZI30CX5dhljzPOB/wd8G7i4qn6c5BEtcbNOVV2d5CHAp5NsARSw+jjX+CTgWblr3bA1gdlt+2sjz/+gqroxyU7A4+iSTp9P8qaqOj7JZ4AXJzmOLgF1ALAu8LAkHwa+wl9XNEGXPN0W+Fq7p7OAXw7sH5miugS4oqp+CZDkarpqvRsGB0tyEHAQwOzZs1l45LQtWSZJkqRVnAkkaXJdwQTrHAFU1c+T3JBke7o/rl810TFDunVg+3a6n/GM07fv+JFjace/tqrOHuyY5MnAv1fVJ0a1zwFuWoZzjrYD8I123q9V1X5j9Pk8XeXGb+gSD39M99f6eP3vDG8Z4ii6Ks3fDSZfxuhzT9wH2LWqbh5sHEjmTGT0+71WS7h8ubUdNcQ6V5MeQ9s+jS5Bei6wsKpuGH0g8D26pN7u3JXsWwq8kLvWXnoXcF5VPbc9W/PHiSN01U8/GHUdj6HneWzJsPnA/CRLgJfSVUsdR3cfbwFOaWsn/TbJo4En0z1/LwBePkYcV1TVruOccuR+3cHd790djPHf5Ko6mq4Kjnnz5t3T502SJElabk5hkybXucB9k7xypKGtc/L4MfqeTFc5s35VLZnCmC4CHp/k/klWY/xpTuM5G/jH3PXpWI9sU4POBl7eqnRIsmmSB401QLpPVxurAmWwT5IcTLcuzVfpkgu7JXlE23+/JCOVU/PpplG9kruqhvr6j7iQ7l5smGQWsB/ddDXofh+OJP9eBHynqv4AXJPk+QMxPrr1OZ8u0QGwf9+19TgH+OeBezC3bf6RrtplxDeAf2x9ZiVZb7wBq+pnbVrX3CEXSZ/0GFoct9A9Ix+nS8aM1eePwM/oFqEeSSBdQDeFciSBtD7w87Z94MDho+M7G3htSySSZIe++FqfLVtl04i5wE9abL+gWxT7rbTpd22a5H2q6jS6aaE7jhHLD4CN0i3QTZLVM7DemSRJknRvZQJJmkRVVcBzgScm+XGSK4AjGPvTmU6lS0B8YYx9EzlkcE2bVpkxXkw/B/6NLnnydeBK4PfLcK5j2jGXpFsE/BN0ayWdA3wOuKBVbpzK3f+gH7Q9d5/GM+jIJJcBP6SrRnlCVf25TTM7EDgp3ce5f4+2flOrGjmLbrHts1rbuP0H7sUvgX8BzgMuo1vz6Ett903ANukWe96Lu9YJ2h/4hxbjFcCzW/vrgNckuZguybE8DgbmpVuE/Eq6hauhq3x5bntvH9fO9YR2nxcCk5mQmMoYTqSr0hprqteI84H7VtXP2usLgIdxVwLpfcC/JzmfbjrYiPPopt4tSrIvXaXS6sDi9pwOs7D5OnTT465sz8zWdD+vg/H/rKqubK83patUWkSXVPqX1n48cFRrn0WXiHxve2YWcde6TpIkSdK9Vrq/dyWtzJKs09Z7WQ04Azi2qs6Y6LhJOvd6wKeq6vkr4nzLK8mNVfVXn9qm5dfWI1q/qt423bEsj3SfVnhpVX1qumOBbgrbggULpjsMSZIkrcSSLKyqeWPtcw0kadVwRJK96RYWPodu0egVok0Dm9HJI02+JGcAD6er5rrXaZVoN9Et8i1JkiSt8kwgSauAqjp04l6rNquPJldVPXe6Y7gnqmqn6Y5BkiRJmklcA0mSJEmSJEm9TCBJkiRJkiSplwkkSZIkSZIk9TKBJEmSJEmSpF4mkCRJkiRJktTLBJIkSZIkSZJ6mUCSJEmSJElSLxNIkiRJkiRJ6mUCSZIkSZIkSb1MIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqtdp0ByBJkiZ21dIb2OmwE6Y7DGlSLTzygOkOQZIkDckKJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkiRJkiRJUi8TSJIkSZIkSeplAkmSJEmSJEm9TCBJkiRJkiSplwkkSZIkSZIk9TKBJEmSJEmSpF4mkCRJkiRJktTLBJIkSZIkSZJ6mUCSJK3yktw4RturkxzQtucnmbfiI5MkSZJmhtWmOwBJkmaiqjpqWfonWa2qbhui36yqun35I5MkSZJWPCuQJEkaQ5Ijkhw60PTiJN9NcnmSXQb6HJ3kHOCEJHOSfDvJJe3rsa3fnknOS/I5YEmSdyV53cC53p3k4BV6gZIkSdIysAJJkqThrF1Vj02yB3AssG1r3wnYvapuTnI/4IlVdUuSLYCTgJGpb7sA21bVNUnmAKcD/5XkPsAL2/67SXIQcBDApuuvzhnrHjmFl6cRsw9fMt0hSJIkzTgmkCRJGs5JAFX1rSTrJdmgtZ9ZVTe37dWBjySZC9wOPHLg+Iuq6po2xrVJbkiyA/Bg4NKqumH0CavqaOBogO03Xaum4JokSZKkoZhAkiRpOKMTOCOvbxpoOwT4FfBoumnitwzsG+wHcAxwIPA3dBVNkiRJ0ozlGkiSJA1nX4AkuwO/r6rfj9FnfeCXVXUH8BJgVs94ZwBPAXYGzp7kWCVJkqRJZQWSJElwvyRLB15/YIw+v03yXWA94OXjjPMx4LQkzwfO46+rju5UVX9Och7wOz+VTZIkSTOdCSRJ0iqvqnorcqtqz3Hajxj1+kfA9gNN/9La5wPzB/u2xbP/Fnj+MoYrSZIkrXBOYZMkaQVLsjXwv8A3WtJJkiRJmtGsQJIkaQWrqiuBh013HJIkSdKwrECSJEmSJElSLxNIkiRJkiRJ6mUCSZIkSZIkSb1MIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqtNt0BSJKkia2x8TbMPnzBdIchSZKkVZQVSJIkSZIkSeplAkmSJEmSJEm9TCBJkiRJkiSplwkkSZIkSZIk9TKBJEmSJEmSpF4mkCRJkiRJktTLBJIkSZIkSZJ6rTbdAUiSpIldtfQGdjrshOkOY5Ww8MgDpjsESZKkGccKJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkiRJkiRJUi8TSJIkSZIkSeplAkmSJEmSJEm9TCBJkiRJkiSplwkkSZIkSZIk9TKBJEmSJEmSpF4mkCRJkiRJktTLBJIkzQBJbk+yKMkVSS5L8oYk92n75iX5UNu+b5Kvt777JnlcO2ZRkrWmML4Dk2wyVeMvr8F7swzHvDzJkiSLk1ye5Nmt/fgk17R7uSjJwWMcOz/JD9qx30/ykSQbDHHONy9LjJIkSdJMs9p0ByBJAuDmqpoLkORBwOeA9YG3V9UCYEHrtwOw+kDfo4D3V9Vxw5wkSYBU1R3LGN+BwOXAL5bxuCk16t5MKMlmwFuAHavq90nWATYa6HJYVZ06wTD7V9WCJGsA/w58CXj8BMe8Gfi3YeOUJEmSZhorkCRphqmq64CDgH9OZ88kZ7XE0meBua1C5lXAC4DDk5wIkOSwJBe3Cpl3tLY5Sa5K8jHgEuAhE/T7ZKtqOifJWkn2AeYBJ45V6dSqct6b5KIkP0zyuIHxvp3kkvb12Na+Z5JvJvlC6/+eJPu345ckeXjrt1GS01qcFyfZbfS9Grk3bfuIJMe2eK4eq4IIeBDwR+DGdq9vrKprlvN9+jPwRmB2kke3GL6YZGG7fwe1tvcAa7V7d+J4/SRJkqSZzASSJM1AVXU13e/oBw20XQe8Avh2Vc2tqk8AZ9JVzeyf5EnAFsAuwFxgpyR7tMO3BE6oqh3a9nj9tgA+WlXbAL8DntcqchbQVd7Mraqbxwh5taraBXg98PbWdh3wxKraEdgXGJxq9mjgdcB2wEuAR7bjjwFe2/r8F/DBqtoZeF7bN5GtgCe3a3t7ktVH7b8M+BVwTZLjkjxz1P4jB6awbTfRyarq9jbmVq3p5VW1E13C7eAkD6yqN9EqzKpq//H6DXFtkiRJ0rRxCpskzVxZxv5Pal+Xttfr0CWEfgr8pKq+N0S/a6pqUWtfCMwZ8tynj3HM6sBHkswFbgceOdD/4qr6JUCSHwPntPYlwBPa9t7A1t2sOwDWS7JuVf2xJ46vVNWtwK1JrgMeDCwd2VlVtyd5CrAz8HfAB5PsVFVHtC7DTGEbbfB9OjjJc9v2Q+ju6w1jHDNUv1addBDA7NmzWXjkAcsYmiRJkjQ5TCBJ0gyU5GF0SZfrgEcNexjw760yaXCsOcBNQ/a7daDpdmDYhblHjrudu/7bcghdtc+j6aqpbhmjP8AdA6/vGDj+PsCu41Q8TRTH6FjuVFUFXARclORrwHHAEctwjjslmUVXRXVVkj3pkl67VtWfkswH1hzjmKH6tViPBo4GmDdvXi1PjJIkSdJkcAqbJM0wSTYCjgI+0pIdwzobeHlbGJokm7Z1k5a336A/AusuQyzQLQL+y7Zg90uAWct4/DnAP4+8aJVM90iSTZLsONA0F/jJco61Ot0i2j+rqsV01/vblhTaCvjbge5/GZhO19dPkiRJmpGsQJKkmWGtJIvopn3dBnwG+MCyDFBV5yR5FHBBm/Z1I/BiukqcZe43yvHAUUluZviqoI8BpyV5PnAed6+CGsbBwEeTLKb779W3gFcv4xijrQ68P8kmdBVRv16OMU9McitwX+DrwLNb+1eBV7d4fwB8b+CYo4HFSS4BXt7TT5IkSZqRsmz/uC1JkqbDvHnzasGCBdMdhiRJklZiSRZW1byx9jmFTZIkSZIkSb1MIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqdcyJ5CS3D/J9lMRjCRJkiRJkmaeoRJISeYnWS/JA4DLgOOSfGBqQ5MkSZIkSdJMMGwF0vpV9Qfg74HjqmonYO+pC0uSJEmSJEkzxbAJpNWSbAy8ADhrCuORJEmSJEnSDDNsAukdwNnA/1bVxUkeBvxo6sKSJEmSJEnSTLHakP1+WVV3LpxdVVe7BpIkSZIkSdKqYdgKpA8P2SZJkiRJkqSVTG8FUpJdgccCGyV5w8Cu9YBZUxmYJEmSJEmSZoaJprCtAazT+q070P4HYJ+pCkqSJEmSJEkzR6pq4k7JQ6vqJysgHkmSNIa1/2bz2uol75juMFYJC488YLpDkCRJmhZJFlbVvLH2DbuI9n2THA3MGTymqva65+FJkiRJkiRpJhs2gXQKcBRwDHD71IUjSZIkSZKkmWbYBNJtVfXxKY1EkiRJkiRJM9J9huz35ST/lGTjJA8Y+ZrSyCRJkiRJkjQjDFuB9NL2/bCBtgIeNrnhSJIkSZIkaaYZKoFUVZtPdSCSJEmSJEmamYaawpbkfkne2j6JjSRbJHnG1IYmSZIkSZKkmWDYNZCOA/4MPLa9Xgr865REJEmSJEmSpBll2ATSw6vqfcBfAKrqZiBTFpUkSZIkSZJmjGETSH9OshbdwtkkeThw65RFJUmSJEmSpBlj2E9hezvwVeAhSU4EdgMOnKqgJEmSJEmSNHMMVYFUVV8D/p4uaXQSMK+q5k9dWJIkTZ8kleQzA69XS/LrJGdNZ1ySJEnSdBl2ChvApsAsYA1gjyR/PzUhSZI07W4Ctm3TtwGeCPx8Kk+YZNiqYEmSJGmFGyqBlORY4FjgecAz29czpjAuSZKm2/8AT2/b+9FV4AKQZJck301yafu+ZWv/dpK5A/3OT7J9kgck+WKSxUm+l2T7tv+IJEcnOQc4YYVdmSRJkrSMhv3Xzr+tqq2nNBJJkmaWk4HD27S17en+IeVxbd/3gT2q6rYkewP/RvePLMfQTfd+fZJHAvetqsVJPgxcWlXPSbIXXbJobhtrJ2D39gmnd5PkIOAggNmzZ7PwyAOm5kolSZKkCQw7he2CJCaQJEmrjKpaDMyhqz7671G71wdOSXI58EFgm9Z+CvCMJKsDLweOb+27A59p454LPDDJ+m3fmWMlj1rfo6tqXlXN22ijjSbluiRJkqTlMWwF0qfpkkj/B9wKBKiq2n7KIpMkafqdCbwf2BN44ED7u4Dzquq5SeYA8wGq6k9JvgY8G3gBMK/1zxhjV/t+06RHLUmSJE2yYRNIxwIvAZYAd0xdOJIkzSjHAr+vqiVJ9hxoX5+7FtU+cNQxxwBfBr5dVb9pbd8C9gfe1ca5vqr+kIyVV5IkSZJmnmETSD+tqjOnNBJJkmaYqloK/NcYu94HfDrJG4BzRx2zMMkfgOMGmo8AjkuyGPgT8NKpiViSJEmaGqmqiTslHwM2oPsX1VtH2qvq9CmLTJKke6Ekm9BNaduqqiatanfevHm1YMGCyRpOkiRJ+itJFlbVvLH2DVuBtBZd4uhJA20FmECSJKlJcgDwbuANk5k8kiRJkqbbUAmkqnrZVAciSdK9XVWdAJww3XFIkiRJk22oBFKSzYHX0n2c8Z3HVNWzpiYsSZIkSZIkzRTDTmH7IvApujWQLMmXJEmSJElahQybQLqlqj40pZFIkiRJkiRpRho2gfRfSd4OnMPdP4XtkimJSpIkSZIkSTPGsAmk7YCXAHtx1xS2aq8lSZIkSZK0Ehs2gfRc4GFV9eepDEaSJEmSJEkzz32G7HcZsMEUxiFJkiRJkqQZatgKpAcD309yMXdfA+lZUxKVJEmSJEmSZoxhE0hvn9IoJEmSJEmSNGMNlUCqqm8meTCwc2u6qKqum7qwJEmSJEmSNFMMtQZSkhcAFwHPB14AXJhkn6kMTJIkSZIkSTPDsFPY3gLsPFJ1lGQj4OvAqVMVmCRJkiRJkmaGYT+F7T6jpqzdsAzHSpIkSZIk6V5s2AqkryY5Gzipvd4X+O+pCUmSJEmSJEkzSW8CKckjgAdX1WFJ/h7YHQhwAXDiCohPkiRJkiRJ02yiaWj/CfwRoKpOr6o3VNUhdNVH/zm1oUmSJEmSJGkmmCiBNKeqFo9urKoFwJwpiUiSJEmSJEkzykQJpDV79q01mYFIkiRJkiRpZpoogXRxkleObkzyD8DCqQlJkiRJkiRJM8lEn8L2euCMJPtzV8JoHrAG8NwpjEuSJEmSJEkzRG8Cqap+BTw2yROAbVvzV6rq3CmPTJIkSZIkSTPCRBVIAFTVecB5UxyLJEmSJEmSZqCJ1kCSJEmSJEnSKs4EkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqdeUJJCSPCTJeUmuSnJFktcN7HtAkq8l+VH7fv/W/sB2zI1JPjJqvJ2SLEnyv0k+lCTLEdOhSb6f5PIklyU5oLVfm2TDMfo/K8mbJhjzvkm+nmRRkn2HjGOr1v/SJA8fte/adp2XJTknyd8sw/XNSfKiYfsvw7jzk8wbo/1x7b1dlGSt5Rz7zQPbc5Jcfg9jfWqSBe25+36S97f2Vw+83wcm2eSenGc54hrvHq6e5D3tZ+HyJBcleeokn3tSn4skJyVZnOSQUe1btutc1O7/0ZN0vuOTXNPGXZTk4MkYd5xz3fmcTNH4pyZ52CSNNd7vrUn7mUry4CRntd9HVyb574FxJ3ympuDZO7g9WyeOsW+XJN9K8oP2s39Mkvv1jLVnkrPa9p2/65NslOTC9vv5cZMQ84TPVJJ/TvKye3ouSZIkaapNVQXSbcD/q6pHAX8LvCbJ1m3fm4BvVNUWwDfaa4BbgLcBh44x3seBg4At2tdTliWYJK8GngjsUlXbAnsAvUmoqjqzqt4zwdA7AKtX1dyq+vyQ4TwH+FJV7VBVPx5j/xOq6tHAAuDNgzvSGe89mwNMegKpx/7A+9u13zxR5ySzxmh+8xhtyyXJtsBHgBe3525b4GqAqjqqqk5oXQ8EVmgCqce7gI2Bbdtz+Uxg3Uk+xxwm6bloCc3HVtX2VfXBUbs/BHywPQ+PAj48GedsDmvjzq2qD42KabXJOsmo52RSJdkGmFVVV0/F+AMm7WcKeCfwtap6dFVtzV2/q+cw3DM1bL9h/RPwtKraf7AxyYOBU4D/r6q2BB4FfJUhf5ZG/a7/O+D77ffzt4c5fpzfbSNjD/NMHQtMWWJUkiRJmixTkkCqql9W1SVt+4/AVcCmbfezgU+37U/TJVSoqpuq6jt0iaQ7JdkYWK+qLqiqAk4YOWYZvBn4p6r6QzvX76vq0wP7X5vkklb9s1U774FplVDtX6VPS3Jx+9otyYOAzwJzW2XE6GqiuUm+16o1zkhy/yRPA14PvCLJeRPE/C3gEe1f8a9K8jHgEuAhSY5sFStLclfl03uAx7VYDkmyZpLjWp9LkzyhxTUryftb++Ikr23tf9f6LUlybJL7jhdYklcALwAOT3JiS2z9VUztX/nPS/I5YMmoMd4DrNXiHakomJXkk+kqm85Jq2xK8vAkX02yMMm3R96jUd4IvLuqvg9QVbdV1cfa8Uekq0DbB5gHnNjO+/QkZwzE9MQkp49xvYe39/3yJEcnXQVcuoqb96arHPrhSMVCkrWSnNzu7+eBv6rQatURrwReW1W3tph/VVVfaPv3a/fy8iTvHTjuxoHtfZIc37aPT1ed990kV7drhb9+Lr6dZO7AGOcn2X5UbGM+O8A5wIPaWKOrMzYGlo68qKolbaw57ZyXtK/HtvY92/07NV3FyIkj93Ui7bh/S/JN4HVJnpm7qka+ni6hMPK+H9v6X52B6qUkB7T357Iknxnof2jbPjhd1c3iJCe3tnUG7sviJM/re69G2R/40sD5P56uWu6KJO8YaL82yTvy17+PHth+Ji5N8gnGSIBPwc/U6Pd0cdsc/UyN+R6P0W9Wut8TF7f796qxblSSN7R7eXmS17e2o4CHAWdmVPUb8Brg01V1QYuzqurUqvpVusqk77b79t0kW45xvgOTfKT9XLwPeFqLea3x3tt0lbLvTHIhsGt7/e72PH1v1DM48ky9sl37Zen+e3K/Fu+fgGuT7DLW/ZAkSZJmjKqa0i+6f4X+KV0SCOB3o/b/dtTrA4GPDLyeB3x94PXjgLOW4fzrjj7HqP3X0v0RD92/cB8zOg7gc8DubXs2cFXb3nO8WIDFwOPb9juB/2zbRwCH9sSyYdv+CPDedv/uAP62tT8P+BowC3hwu7cbj44F+H/AcW17q9ZvTeAfgdOA1dq+B7T2nwGPbG0nAK9v2/OBeWPEejywzxAx3QRsPs713jjqObkNmNtef4Gumgi6SrUt2vZjgHPHGOsS4NHjnOfOez54PXR/hH8f2GjgfX7mGMc/YGD7MyN92lj/0bafRntOgTcAx7bt7dt1zRs15vbApePEu0m7hxsBqwHnAs8Z457tAxw/8H6cQpcU3hr437GeUeCl3PUsPhJYMMb5x3t25gCXjxPzy4DfA/8DHAJs0NrvB6zZtrcYOV+L6/fAZi3mC2g/Y2M8Z9cAi9rXdu2+f2ygz/2BtO1XDLwnRwDfBe4LbAjcAKwObAP8gLt+1h4wxnPyC+C+bXvkWt47cu8GzjvuezXqOr4JbDf6maL7mZkPbD/B76MPAYe37acDNRL/FP5MPRn4HXAe8BZgk3Geqb73eLDfQcBb2/Z96aosNx91zp3oks1rA+sAVwA7DNybsa75dODZ4zyX63HX77q9gdNGx8bdf9cPbvf9HBbwgoHzFHf9XnjfwHUewV3P1AMH+v/ryPvcXr+Frmq3979nO+20U0mSJElTiTH+Rhz5mrTpH2NJsg5dsuL11ap/lmeYMdpqGY+fqP9I1clC4O/H2L83sPVAgcR6ScadHpFkfbo/Or/Zmj5N98f9MM5LcjtdAuqtwAbAT6rqe23/7sBJVXU78KtWhbEzMPr+7k6bRlRV30/yE7qEwd7AUVV1W9v3mySPBq6pqh8OxPsa4D+HjLkvpouq6pohx7mmqha17YXAnPYMPRY4ZeD+j1sdtSyqqlr1yYuTHAfsCoy1XskTkryR7g/lB9D9Ufvltm/w2ZnTtveg+4OfqlqcZDHLZmdgflX9GqBVk+wBfHGC475YVXcAV45UQIzhFOBtSQ4DXk6XoBltvGdn3J/hqjouydl000ufDbyqPVerAyPVHbe3cUZcVFVL2zUuort/3xlj+MOq6tSRF+05GJwyuhnw+XTVimvQJZxGfKW6Cq9bk1xHl+DcCzi1qq5vsf9mjHMupqtU+yJ33fe9gRcOXPNvk+zBcO/VxsCvB16/IMlBdImJjemSfiPPyVi/j/YY2a6qryT57Rgxj2W5f6aq6ux0azY9BXgqcGm6qaKj9b3Hg54EbJ+7quPWp0s4Db5fuwNnVNVNAOkqAh8HXDrxpY5pfeDTSbag++/A6stwbN/P4e10/20b8WfgrLa9kG7K9GjbJvlXut/p6wBnD+y7ji5Z+1fac3IQwKbrr85P37ndMlyCltfsw5dM3EmSJGkVM2UJpCSr0/0P9olVNTgt6FdJNq6qX7Y/+K6bYKildH8gjtiMrjpg9PnOpvvjcEFVvWKkvar+kOSmJA+r8dcfubV9v52x78l9gF1r1Fo/Wfa1vIfxhJE/bNs5NqCr4rmzachxxus3VkLtnl5I3/E39ewb7daB7dvppn7dh65qbe4Ex15BV71w2TKcD+A4umTQLcApI4m1EUnWBD5GV0H0syRH0FXjjI559LMzUdLyf4HZSdatbprn3U7bc9zguGuO2jd4/8Yco6r+lORrdEmeF9BV+I22XM9DVf2Cbj2XY9Mt3jyyrtOvgEfTvZeDU1RHv9/L8vto8Ln6MPCBqjozyZ50VR995xgmqfx0umTBs+gSbtuMc9yw9+pm2vuVZHO6td52bkmo45mcZ2os9+RnaiS59jngc+kWnd6DrpJr0CGM/x4PCl3Vzdnj7B/ps6xGfva/NMa+dwHnVdVzk8yhq/YaVl8st7SE+Yi/tH+tgfGf5ePpKpguS3IgXRXUiDXpnpG/UlVHA0cDbL/pWsvzDEiSJEmTYqo+hS3Ap+imen1g1O4z6abR0L6P9T/9d6qqXwJ/TPK3bdwDxjqmqp5c3SK7r/irQeDfgY8mWa/Ft177V91hnQP888iLDKwhM07Mvwd+m7vWiXkJ3RSWyfAtYN+2nshGdH/QXQT8kbsvGvstunVXSPJIuql3P6C7llenLT6c5AF007jmJHnEcsY7XkwT+UtLNI6rVa5dk+T5Ld60ypbRjgTe3K6VJPdJ8oYx+t3tPrWkxy/oqr2OH6P/yB/217fKjX3G6DPa4L3flm662ujr+hPdz8iHkqzR+m6c5MXAhcDjk2yYboHe/bjr/fhVkkelW0z9uUPEMvq5ADiGrkLq4nGqb8Z7dsaV5Ckj72W6xbYfCPycrgLkl60y6iV0U7Ym2/rtXHDX75Y+36CrAHog3PkzcKd2bx9SVefRra21AV3FyOjfA/en/70adBUw8vO1Hl0C7PetUmyYT94bfE+eSjd9biyT9jOVZK+RdXpaxeXD6aZ0jX6mxnuPR/c7G/jHgefkkUnWHuM6n5Pkfm3fc4GJFrP+CPDSJI8ZiP3F7TkcfDYOnGCc0YZ9b4e1LvDLdv37j9r3SOAefQqlJEmSNNWm6lPYdqP7Q2Kv3PXx209r+94DPDHJj+jK/O/8pLMk1wIfAA5MsjR3fXLbP9L90fu/wI/p1llZFh+nW8fj4lYZ8U3gT8tw/MHAvHQLv14JvHqIY14KHJlu+tJcunWQJsMZdFNdLqNbk+ONVfV/re22dAu0HkJXNTMryRK66T4Htqk8x9D9Ebg4yWXAi6rqFro1bE5p/e8AjpqEmCZydIvjrz6We5T9gX9o8V5BVz1zN9Ut8Pt64KQkV9H9MbbxGGMdDxzVnsmRxa1PBH5WVVeOMe7vgE/SrcvyReDiCa+qe97Wae/9Gxk/mfZWumlNV7bn8ovAr1vS9F/ontnLgEuqaiRp+ia6qTLnAr8cIpbRzwVVtZBuOtpx4xwz3rPT50nA5e09Optu2tn/tbFemuR7dH8kL0tF2rCOoHt2vw1cP0FfquoK4N3AN1u8o5Pcs4DPtuu/lO7T5X5Ht27N/dMtqHwZXbVg33s16Cu0ipOquqyNewVdxdb5Q1zjO4A9klxCd69/Ok6/SfuZoqvqWdCe4wvo1mO6mLF/14z1Ho/udwxwJXBJe94/wahKneo+fOF4up+ZC9s5e6evVdWv6KYWvj/JD9rP/+PonvH3Af+e5HyWMXm5DO/tsN5Gd01fo0vaD9oN+Po9GFuSJEmaciMLz0qrrHSftndpVX1qumNZEZJsQjeVZ6tWNaIp1pKV5wG7jZr6pFVckh2AN1TVSybqu/2ma9VZr3rERN00CVwDSZIkraqSLKyqsZY6mbIKJOleIclCuilmn53uWFaEJAfQVUG8xeTRitPWT3s7sOl0x6IZZ0O66iRJkiRpRpvST2GTZrqq2mm6Y1iRquoE4ITpjmNVNMHi0VpFVdXXpjsGSZIkaRhWIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqddq0x2AJEma2Bobb8PswxdMdxiSJElaRVmBJEmSJEmSpF4mkCRJkiRJktTLBJIkSZIkSZJ6mUCSJEmSJElSLxNIkiRJkiRJ6mUCSZIkSZIkSb1MIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkqRVSJJjk1yX5PIh+u6Z5LHj7Ltvkq8nWZRk3yTzk8yb/IjvmST/nWSDZeh/RJJD2/Y7k+zdtq9NsuEUhSlJkiTNeCaQJGnVcjzwlCH77gmMmUACdgBWr6q5VfX5SYgLgCSzJmssgKp6WlX9bjmPPbyqvj5s/ySrTWY/SZIkaSYxgSRJq5Cq+hbwm9HtSQ5OcmWSxUlOTjIHeDVwSKsyetxA3wcBnwXmtn0PHzXWfkmWJLk8yXuHaL+xVftcCOw6aqz5ST6Y5FtJrkqyc5LTk/woyb8O9PtikoVJrkhy0ED7tUk2TDKnHf/J1uecJGv13askxyfZZ6DpsCQXta9HDPT5QJLzgPcm2SXJd5Nc2r5v2fodmOSUJF8GzknymSTPHjjXiUme1RePJEmSNJ38V1BJEsCbgM2r6tYkG1TV75IcBdxYVe8f7FhV1yV5BXBoVT0DIAnt+ybAe4GdgN/SJUueA1w0VntVfRFYG7i8qg4fJ7Y/V9UeSV4HfKmN8Rvgx0k+WFU3AC+vqt+0pNDFSU5r7YO2AParqlcm+QLwPLpE2LD+UFW7JDkA+E/gGa39kcDeVXV7kvWAParqtjb97d/aeaBLjm3f4nw8cAjwpSTr01V6vXT0CVsy7CCATddfnZ++c7tlCFfLa/bhS6Y7BEmSpBnHCiRJEsBi4MQkLwZuuwfj7AzMr6pfV9VtwInAHj3tALcDp/WMeWb7vgS4oqp+WVW3AlcDD2n7Dk5yGfC91rbFGONcU1WL2vZCYM4yXttJA98HK6VOqarb2/b6wCltjakPAtsM9PtaVf0GoKq+CTyiVXPtB5zW7svdVNXRVTWvquY9YO1Jnd0nSZIkLRMTSJIkgKcDH6Wr7ll4D9bpyTK2A9wykIAZy63t+x0D2yOvV0uyJ7A3sGtVPRq4FFizZxzoklbLeo01zvZNA9vvAs6rqm2BZ46KY7AfwGeA/YGXAcctYyySJEnSCmUCSZJWcUnuAzykqs4D3ghsAKwD/BFYdxmHuxB4fFt3aBZddc03e9onw/rAb6vqT0m2Av52ksYdbd+B7xf0xPLztn3gBOMdD7weoKquuGehSZIkSVPLBJIkrUKSnESX/NgyydIk/wDMAj6bZAld9c4H2yeXfRl47uhFtPtU1S+BfwHOAy4DLqmqL43XPkmX9VW6SqTFdBVA35ukcUe7b1vo+3V06xeN5X3Avyc5n+6+jquqfgVchdVHkiRJuhdIVU3cS5IkTaok96Nb12nHqvr9RP2333StOutVj5j6wOQi2pIkaZWVZGFVzRtrnxVIkiStYO0T2r4PfHiY5JEkSZI03ZZ3kVRJkrScqurrwOzpjkOSJEkalhVIkiRJkiRJ6mUCSZIkSZIkSb1MIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVKv1aY7AEmSNLE1Nt6G2YcvmO4wJEmStIqyAkmSJEmSJEm9TCBJkiRJkiSplwkkSZIkSZIk9TKBJEmSJEmSpF4mkCRJkiRJktTLBJIkSZIkSZJ6mUCSJEmSJElSr9WmOwBJkjSxq5bewE6HnTDdYUiTauGRB0x3CJIkaUhWIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSStUkkryHwOvD01yxATHPCfJ1uPse3WSA5bh/PdJ8qEklydZkuTiJJu3fde2tkXt67FjHH9723dFksuSvCFJ739Pk8xJ8qJhY5QkSZJmmtWmOwBJ0irnVuDvk/x7VV0/5DHPAc4Crhy9o6qOWsbz7wtsAmxfVXck2Qy4aWD/EyaI6+aqmguQ5EHA54D1gbf3HDMHeFHrK0mSJN3rWIEkSVrRbgOOBg4ZvSPJQ5N8I8ni9n12qwJ6FnBkq/x5+KhjjkhyaNuen+S9SS5K8sMkjxvj/BsDv6yqOwCqamlV/XZ5LqSqrgMOAv45nTlJvp3kkvY1UsH0HuBxLf5DevpJkiRJM5IVSJKk6fBRYHGS941q/whwQlV9OsnLgQ9V1XOSnAmcVVWnDjH2alW1S5Kn0VUF7T1q/xeA77Tk0jeAz1bVpQP7z0tyO3BrVT1mopNV1dVtCtuDgOuAJ1bVLUm2AE4C5gFvAg6tqmcAJLnfOP0kSZKkGckEkiRphauqPyQ5ATgYuHlg167A37ftzwCjE0zDOL19X0g3dWz0uZcm2RLYq319I8nzq+obrctEU9jGkvZ9deAjSeYCtwOPHKf/UP2SHERX4cTs2bNZeOTQSz1JkiRJk8oEkiRpuvwncAlwXE+fWo5xb23fb2ec/85V1a3A/wD/k+RXdGssfWOsvhNJ8rB2ruvoKp5+BTyabpr4LeMcdsgw/arqaLrpfsybN2957oUkSZI0KVwDSZI0LarqN3TTyf5hoPm7wAvb9v7Ad9r2H4F1J+O8SXZMsknbvg+wPfCT5RxrI+Ao4CNVVXSLaY+sr/QSYFbrOjr+8fpJkiRJM5IJJEnSdPoPYMOB1wcDL0uymC6x8rrWfjJwWJJLRy+ivRweBHw5yeXAYrpFvT+yDMev1RbDvgL4OnAO8I6272PAS5N8j25a2sinuy0GbktyWZJDevpJkiRJM1K6fzCVJEkz2bx582rBggXTHYYkSZJWYkkWVtWYH+5iBZIkSZIkSZJ6mUCSJEmSJElSLxNIkiRJkiRJ6mUCSZIkSZIkSb1MIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkiRJkiRJUi8TSJIkSZIkSeq12nQHIEmSJnbV0hvY6bATpjuMVcLCIw+Y7hAkSZJmHCuQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkiRJkiRJUi8TSJKkMSWZl+RDy3jMtUk2bNvfbd/3THLWVMQ4QSyvTrIkyaIk30my9ZDHHZ9kn3Har2njLUpycGu/85olSZKkldVq0x2AJGlmqqoFwIJ7cPxjl6V/kllVdfsQ/VarqtuGGPJzVXVUO+ZZwAeApyzPOQccVlWnLkP/oSQJkKq6Y7LHliRJkiaDFUiStJJKMifJ95Mck+TyJCcm2TvJ+Ul+lGSX1m+XJN9Ncmn7vmVrv7NyKMkRSY5NMj/J1SPVNxOc/8aBl+slOSPJlUmOSnKfkT5J3pnkQmDXJIcnubjFe3RLrNDO+29Jvgm8pVUCrd72rdeqgFYfPH9V/WHg5dpADVzXeUk+ByxJ5yMttq8AD1quG96N/YYW++VJXt/X3t6fq5J8DLgEeMjynleSJEmaalYgSdLK7RHA84GDgIuBFwG7A88C3gw8B/g+sEdV3ZZkb+DfgOeNMdZWwBOAdYEfJPl4Vf1lyDh2AbYGfgJ8Ffh74FS6xM7lVXU4QJIrq+qdbfszwDOAL7cxNqiqx7d9c4CnA18EXgicNlYsSV4DvAFYA9hrVDzbVtU1Sf4e2BLYDngwcCVw7DjXcWSSt7btl1TVkoFz7QS8DHgMEODClvC6zzjtv23nfVlV/dNYJ0tyEN17x+zZs1l45AHjhCVJkiRNLSuQJGnldk1VLWlTo64AvlFVBSwB5rQ+6wOnJLkc+CCwzThjfaWqbq2q64Hr6JItw7qoqq5u08VOoktiAdwOnDbQ7wlJLkyyhC7hMxjL5we2j6FLytC+HzfWSavqo1X1cOD/A946sOuiqrqmbe8BnFRVt1fVL4Bze67jsKqa276WjNq3O3BGVd1UVTcCpwOP62kH+ElVfW+8k1XV0VU1r6rmbbTRRj1hSZIkSVPLBJIkrdxuHdi+Y+D1HdxVhfou4Lyq2hZ4JrDmEGPdzrJVsdY4r28ZWYMoyZrAx4B9qmo74JOjYrnpzoOrzgfmJHk8MKuqLp/g/CfTVVv91VjjxLc8soztY8UhSZIkzUgmkCRJ6wM/b9sHTtE5dkmyeVv7aF/gO2P0GUkWXZ9kHeCvPgltlBPoqpnGrD5KssXAy6cDPxpnnG8BL0wyK8nGdNP0lse3gOckuV+StYHnAt/uaZckSZLuNVwDSZL0PuDTSd5A//Ste+IC4D106wx9CzhjdIeq+l2ST9JNr7uWbs2mPicC/0qXRBrLP7c1nf5Ct97QS8fpdwbddLklwA+Bb05w3jFV1SVJjgcuak3HVNWlAGO1t3WcJEmSpHuFdEthSJJ075JkH+DZVfWS6Y5lRZg3b14tWLBgusOQJEnSSizJwqqaN9Y+K5AkSfc6ST4MPBV42nTHIkmSJK0KTCBJku51quq10x2DJEmStCpxEW1JkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkiRJkiRJUi8TSJIkSZIkSeplAkmSJEmSJEm9TCBJkiRJkiSp12rTHYAkSZrYVUtvYKfDTpjuMFYJC488YLpDkCRJmnGsQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeplAkiRJkiRJUi8TSJIkSZIkSeplAkmSJEmSJEm9TCBJ0iooyd8kOTnJj5NcmeS/kzwyySZJTp3g2GcleVPbPiLJoWP0OSLJz5MsauPvN7DvnUn2nuAc4427QZJ/Gv5K7zxuoyR/SfKq8cZKMifJi5Z1bEmSJGlVYAJJklYxSQKcAcyvqodX1dbAm4EHV9UvqmqfvuOr6syqes8Qp/pgVc0Fng18Isnq7fjDq+rryxn+BsAyJ5CA5wPfA/YbaBs91hxgmRJISVZbjlgkSZKkex0TSJK06nkC8JeqOmqkoaoWVdW3WxXO5QBJLkyyzUifJPOT7JTkwCQfGfZkVfUj4E/A/ds4xyfZp20/Lcn3k3wnyYeSnDVw6NbtnFcnObi1vQd4eKtsOjLJxkm+1V5fnuRx44SxH/D/gM2SbDrWWO3149rrQ5KsmeS4JEuSXJrkCS3mA5OckuTLwDnt9elJvprkR0neN3DPnpTkgiSXtGPWSfJ3Sc4Y6PPEJKcPez8lSZKk6WACSZJWPdsCC4fodzLwAoAkGwObVNUwx91Nkh2BH1XVdaPa1wQ+ATy1qnYHNhp16FbAk4FdgLe3CqY3AT+uqrlVdRhdxdDZrdLp0cCiMc7/EOBvquoi4AvAvm3X6LHeBHy7vf4g8BqAqtqOLgH16RYzwK7AS6tqr/Z6bht3O2DfJA9JsiHwVmDvqtoRWAC8ATgXeFSSket9GXDcELdSkiRJmjaW3kuSxvMF4GvA2+kSSacs4/GHJHkl8DDgKWPs3wq4uqquaa9PAg4a2P+VqroVuDXJdcCDxxjjYuDYllz6YlUtGqPPC9u1QJcU+xTwgSHi3x34MEBVfT/JT4BHtn1fq6rfDPT9RlX9HiDJlcBD6abIbQ2c380aZA3ggqqqJJ8BXpzkOLpk1AFjBZDkINo9mT17NguPHLObJEmSNOWsQJKkVc8VwE4TdaqqnwM3JNmerrrm5GU8zwerast27AkD1TsjMsHxtw5s384Y/+hRVd8C9gB+DnwmyVgZlv2AA5NcC5wJPDrJFkPE3xffTUPEGrpE09z2tXVV/UPrcxzw4hbbKVV121gnqaqjq2peVc3baKPRBVqSJEnSimMCSZJWPecC923VQQAk2TnJ48foezLwRmD9qlqyPCerqtPppm+9dNSu7wMPSzKnvd6Xif0RWHfkRZKHAtdV1SfpKot2HOycZEtg7aratKrmVNUc4N/pqpLuNtYYr78F7N/GeSQwG/jBEDGO+B6wW5JHtDHu18ahqn4B/IJuitvxyzCmJEmSNC1MIEnSKqaqCngu8MQkP05yBXAEXUJjtFO5+xSw5fVO4A1J7vzvTlXdTPcpaF9N8h3gV8DvJ4j9BropYZe3ha/3BBYluRR4HvBfow7Zj+4T5wadBuw3xliLgduSXJbkEOBjwKwkS4DPAwe2KXVDqapfAwcCJyVZTJdQ2mqgy4nAz6rqymHHlCRJkqZLur8jJEla8ZKsU1U3plsk6KN0i21/cLrjWhHaJ9ldWlWfGqb/vHnzasGCBVMclSRJklZlSRZW1byx9lmBJEmaTq9MsohuXab16T6VbaWXZCGwPfDZ6Y5FkiRJGoafwiZJmjat2miVqDgaVFUTLmIuSZIkzSRWIEmSJEmSJKmXCSRJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLUywSSJEmSJEmSeqWqpjsGSZI0gSR/BH4w3XGsIjYErp/uIFYR3usVx3u94nivVxzv9YrjvV5xpvteP7SqNhprx2orOhJJkrRcflBV86Y7iFVBkgXe6xXDe73ieK9XHO/1iuO9XnG81yvOTL7XTmGTJEmSJElSLxNIkiRJkiRJ6mUCSZKke4ejpzuAVYj3esXxXq843usVx3u94nivVxzv9YozY++1i2hLkiRJkiSplxVIkiRJkiRJ6mUCSZKkGSzJU5L8IMn/JnnTdMezMktybJLrklw+3bGszJI8JMl5Sa5KckWS1013TCurJGsmuSjJZe1ev2O6Y1rZJZmV5NIkZ013LCu7JNcmWZJkUZIF0x3PyizJBklOTfL99rt71+mOaWWUZMv2PI98/SHJ66c7rkFOYZMkaYZKMgv4IfBEYClwMbBfVV05rYGtpJLsAdwInFBV2053PCurJBsDG1fVJUnWBRYCz/G5nnxJAqxdVTcmWR34DvC6qvreNIe20kryBmAesF5VPWO641mZJbkWmFdV1093LCu7JJ8Gvl1VxyRZA7hfVf1umsNaqbX/B/w58Jiq+sl0xzPCCiRJkmauXYD/raqrq+rPwMnAs6c5ppVWVX0L+M10x7Gyq6pfVtUlbfuPwFXAptMb1cqpOje2l6u3L//1eIok2Qx4OnDMdMciTZYk6wF7AJ8CqKo/mzxaIf4O+PFMSh6BCSRJkmayTYGfDbxein9oayWSZA6wA3DhNIey0mpTqhYB1wFfqyrv9dT5T+CNwB3THMeqooBzkixMctB0B7MSexjwa+C4Nj3zmCRrT3dQq4AXAidNdxCjmUCSJGnmyhhtVg9opZBkHeA04PVV9YfpjmdlVVW3V9VcYDNglyROz5wCSZ4BXFdVC6c7llXIblW1I/BU4DVtGrIm32rAjsDHq2oH4CbANRmnUJsm+CzglOmOZTQTSJIkzVxLgYcMvN4M+MU0xSJNmrYez2nAiVV1+nTHsypoU07mA0+Z3khWWrsBz2rr8pwM7JXks9Mb0sqtqn7Rvl8HnEE37VuTbymwdKB68VS6hJKmzlOBS6rqV9MdyGgmkCRJmrkuBrZIsnn716gXAmdOc0zSPdIWdv4UcFVVfWC641mZJdkoyQZtey1gb+D70xrUSqqq/qWqNquqOXS/q8+tqhdPc1grrSRrt0X4adOpngT4CZpToKr+D/hZki1b098BfujB1NqPGTh9DbpyNEmSNANV1W1J/hk4G5gFHFtVV0xzWCutJCcBewIbJlkKvL2qPjW9Ua2UdgNeAixpa/MAvLmq/nv6QlppbQx8un2az32AL1SVHy+vlcGDgTO6fDSrAZ+rqq9Ob0grtdcCJ7Z/zLoaeNk0x7PSSnI/uk/ffdV0xzKWVLmUgiRJkiRJksbnFDZJkiRJkiT1MoEkSZIkSZKkXiaQJEmSJEmS1MsEkiRJkiRJknqZQJIkSZIkSVIvE0iSJEmSVmlJXt8+PluSNI5U1XTHIEmSJEnTJsm1wLyqun66Y5GkmcoKJEmSJEkzXpIDkixOclmSzyR5aJJvtLZvJJnd+h2fZJ+B425s3/dMMj/JqUm+n+TEdA4GNgHOS3Le9FydJM18q013AJIkSZLUJ8k2wFuA3arq+iQPAD4NnFBVn07ycuBDwHMmGGoHYBvgF8D5bbwPJXkD8AQrkCRpfFYgSZIkSZrp9gJOHUnwVNVvgF2Bz7X9nwF2H2Kci6pqaVXdASwC5kx+qJK0cjKBJEmSJGmmCzDR4q0j+2+j/Z2TJMAaA31uHdi+HWdkSNLQTCBJkiRJmum+AbwgyQMB2hS27wIvbPv3B77Ttq8FdmrbzwZWH2L8PwLrTlawkrQyMuMuSZIkaUarqiuSvBv4ZpLbgUuBg4FjkxwG/Bp4Wev+SeBLSS6iSzzdNMQpjgb+J8kvq+oJk38FknTvl6qJKkElSZIkSZK0KnMKmyRJkiRJknqZQJIkSZIkSVIvE0iSJEmSJEnqZQJJkiRJkiRJvUwgSZIkSZIkqZcJJEmSJEmSJPUygSRJkiRJkqReJpAkSZIkSZLU6/8H7h/iKxYVJ6MAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12,8))\n", + "sns.countplot(y='Comments', hue='Gender', data=data)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The comments on female-named buildings are mostly facilities and other amenities or park. We can not really point out so much about where female-named buildings due to the small size of comments gotten. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Conclusions" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- Most buildings in San Franciso are named after men. \n", + "- The females are not well represented at all." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Level 2/Intermediate/Accommodation Assessment Form.csv b/Level 2/Intermediate/Accommodation Assessment Form.csv new file mode 100644 index 0000000..0f6b78c --- /dev/null +++ b/Level 2/Intermediate/Accommodation Assessment Form.csv @@ -0,0 +1,122 @@ +"Timestamp","Age","Gender","Maximum Level of Education","Country","State/Province","Based on your answer above, how industrious is your State of residence?","Currency","Monthly Salary in the currency you mentioned above","Career Industry","Years of working experience","Do you foot your accommodation bills?","If you selected ""Not completely"", what fraction of the rent do you pay?","Accommodation Rented","Location of accommodation","Cost of your accommodation per month","Do you think accommodation prices are generally high in your State of residence for young adults?" +"2021/01/20 7:57:57 AM GMT+1","24","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Industrious","Naira","150000","Accounting & Tech","1","Yes","","Full Flat","Mid-class area","80000","Yes" +"2021/01/20 9:02:40 AM GMT+1","27","Female","Bachelor's Degree/Equivalent","Kenya","Nairobi","Most industrious in the country","Kenyan Shillings","150000","Software Engineer","3","Yes","","Shared Flat","Mid-class area","35000","Yes" +"2021/01/20 9:07:23 AM GMT+1","25","Female","High/Secondary School","South Africa","Cape Town","Non-Industrious","Rand","2000","Hospitality","5","Yes","","Shared Flat","Mid-class area","R3500","Yes" +"2021/01/20 9:27:25 AM GMT+1","28","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","0","IT","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 9:27:53 AM GMT+1","24","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Industrious","Naira ","70000","Tech","1","Not completely","1/4","Neither. I do not pay rents","Low brow area"," N/A","Yes" +"2021/01/20 10:22:51 AM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria ","Abia state ","Industrious","Naira","30000","Tech","0","No","","Neither. I do not pay rents","Mid-class area","N/A","No" +"2021/01/20 10:39:11 AM GMT+1","20","Female","High/Secondary School","Nigeria ","Lagos","Industrious","Naira","0","Tech","0","No","","Neither. I do not pay rents","High brow area","N/A","Yes" +"2021/01/20 10:50:18 AM GMT+1","28","Female","Master's Degree","Nigeria","Rivers State","Industrious","Naira","0","Engineering","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 11:00:07 AM GMT+1","20","Female","Undergraduate","Nigeria","Rivers State","Industrious","Naira","15000","Tech","1","Not completely","1/2","Self-contained","Mid-class area","140000","Yes" +"2021/01/20 11:00:31 AM GMT+1","27","Male","Bachelor's Degree/Equivalent","Nigeria ","Delta","Industrious","Naira","145000","Engineering ","3","Yes","","Full Flat","Low brow area","20000","Yes" +"2021/01/20 11:43:35 AM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Ekiti","Non-Industrious","Naira","0","0","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","No" +"2021/01/20 11:55:57 AM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","200000","Tech","1","Not completely","1/3","Shared Flat","Mid-class area","40000","Yes" +"2021/01/20 12:07:17 PM GMT+1","21","Male","High/Secondary School","Nigeria","Osun","Unknown","Naira","40000","Tech","1","No","","Self-contained","Mid-class area","10830","Yes" +"2021/01/20 12:26:41 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Ekiti","Non-Industrious","Naira","18000","Teaching","1","Not completely","1/4","Full Flat","Mid-class area","10000","Indifferent" +"2021/01/20 12:45:30 PM GMT+1","23","Male","Bachelor's Degree/Equivalent","NIGERIA","OSUN","Non-Industrious","NAIRA","50000","AGRICULTURE","2","Yes","","Shared Flat","Low brow area","6500","Yes" +"2021/01/20 12:48:38 PM GMT+1","28","Female","Master's Degree","Nigeria","FCT","Industrious","Naira","500000","Consulting ","2","Yes","","Studio apartment","Mid-class area","55,000","Yes" +"2021/01/20 12:48:55 PM GMT+1","29","Male","Bachelor's Degree/Equivalent","Nigeria ","Lagos","Most industrious in the country","Naira","80000","Development","3","Yes","","Self-contained","Low brow area","15000","Yes" +"2021/01/20 12:53:20 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Ondo","Non-Industrious","Naira","20000","Tech","1","No","","Neither. I do not pay rents","I do not pay rents","N/A","No" +"2021/01/20 1:08:47 PM GMT+1","24","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos State","Most industrious in the country","Naira","60000","Finance","0.25","No","","Self-contained","High brow area","N/A","Yes" +"2021/01/20 1:17:01 PM GMT+1","29","Male","Bachelor's Degree/Equivalent","Nigeria","Oyo state","Industrious","Naira","450000","Management ","4","Yes","","Shared Duplex","Mid-class area","25000","No" +"2021/01/20 1:45:46 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","140000","Tech","1","No","","Neither. I do not pay rents","Mid-class area","N/A","Yes" +"2021/01/20 1:50:41 PM GMT+1","21","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos ","Most industrious in the country","Naira ","150000","Accounting ","1","Yes","","Self-contained","Mid-class area","700,000","Yes" +"2021/01/20 2:10:45 PM GMT+1","21","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","50000","Finance ","1","No","","Neither. I do not pay rents","Mid-class area","N/A","Yes" +"2021/01/20 2:13:03 PM GMT+1","29","Female","Bachelor's Degree/Equivalent","Nigeria","Rivers State","Industrious","Naira","80000","Accounting","4","Yes","","Self-contained","Mid-class area","15000","Yes" +"2021/01/20 2:37:12 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Nigeria","Non-Industrious","Naira","0","Tailoring","0","No","","Neither. I do not pay rents","I do not pay rents","0","Yes" +"2021/01/20 2:41:41 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","75000","Education ","1.5","No","","Full Flat","I do not pay rents","N/A","Yes" +"2021/01/20 2:46:11 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","NIGERIA","OYO","","NAIRA","15000","Teaching","0","No","","Mini Flat","Mid-class area","N/A","No" +"2021/01/20 3:26:07 PM GMT+1","19","Female","Bachelor's Degree/Equivalent","NIGERIA","ONDO","Non-Industrious","NAIRA","0","Student","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 3:48:54 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria ","Ekiti","Industrious","Naira","0","Media","0","No","","Neither. I do not pay rents","Mid-class area","N/A","No" +"2021/01/20 5:10:29 PM GMT+1","22","Male","Bachelor's Degree/Equivalent","NIGERIA","LAGOS","Most industrious in the country","NAIRA","0","Media","2","No","","Neither. I do not pay rents","Mid-class area","25000","Yes" +"2021/01/20 5:45:49 PM GMT+1","22","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","190000","Technology","2","Yes","","Self-contained","Low brow area","25000","Yes" +"2021/01/20 7:01:43 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigerian","Osun State","Industrious","Naira","5000","Crafts","1","Not completely","1/4","Self-contained","Mid-class area","10000","Yes" +"2021/01/20 7:26:45 PM GMT+1","19","Female","Bachelor's Degree/Equivalent","Nigeria ","Cross River","Industrious","Naira ","0","Tech","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 7:29:07 PM GMT+1","24","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","200000","Tech","2","Yes","","Mini Flat","Mid-class area","23000","Yes" +"2021/01/20 7:29:51 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Ogun State","Industrious","Naira","33000","Science.","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","No" +"2021/01/20 7:50:50 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Rivers State","Industrious","Naira","0","Tech","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 7:51:57 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria ","Ogun State","Industrious","Naira","50000","Tech","2","Yes","","Self-contained","Mid-class area","120,000","Yes" +"2021/01/20 7:53:21 PM GMT+1","27","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Industrious","Naira ","200000","Music ","6","Yes","","Shared Flat","Mid-class area","17,000","No" +"2021/01/20 8:15:08 PM GMT+1","25","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos State","Most industrious in the country","Naira","0","Agriculture","0","No","","Self-contained","Low brow area","15,000","Yes" +"2021/01/20 8:22:59 PM GMT+1","24","Male","Bachelor's Degree/Equivalent","NIGERIAN","OYO","Industrious","NAIRA","80000","INFORMATION TECHNOLOGY","3","Yes","","Self-contained","High brow area","2500","Yes" +"2021/01/20 8:28:17 PM GMT+1","21","Male","High/Secondary School","Nigeria","Ilorin, Kwara state","Industrious","Naira","17000","Tech","2.5","Not completely","1/4","Self-contained","Mid-class area","7000","Yes" +"2021/01/20 8:37:36 PM GMT+1","21","Female","Bachelor's Degree/Equivalent","Nigeria ","Lagos ","Industrious","Naira","0","Tech","0.3","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 8:39:12 PM GMT+1","25","Male","Bachelor's Degree/Equivalent","Adamawa","Niger state","Non-Industrious","Naira","0","Mechanic","2","Not completely","1/2","Studio apartment","Low brow area","5000","Yes" +"2021/01/20 9:38:52 PM GMT+1","20","Female","Bachelor's Degree/Equivalent","Nigeria","Delta State","Unknown","Naira","0","Tech ","0.2","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 9:55:14 PM GMT+1","20","Male","Undergraduate","Nigeria","Ogun","Non-Industrious","Naira","0","I.T","0","No","0","Self-contained","Mid-class area","N/A","Yes" +"2021/01/20 10:31:21 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","NIGERIA","ANAMBRA STATE, NIGERIA","Industrious","NAIRA","0","TECH","0","Not completely","1/2","Self-contained","Mid-class area","#10,000","Yes" +"2021/01/20 10:53:57 PM GMT+1","19","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","","Naira","0","Tech","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 11:18:30 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","F.C.T. - Abuja","Industrious","Naira","0","Tech","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/20 11:30:59 PM GMT+1","27","Female","Bachelor's Degree/Equivalent","Nigeria ","Lagos State/ Ikorodu","Most industrious in the country","Naira","40000","Fashion designing ","4","Not completely","1/4","Mini Flat","Mid-class area","3000","Yes" +"2021/01/21 12:04:44 AM GMT+1","21","Male","Bachelor's Degree/Equivalent","NIGERIA","BORNO ","Non-Industrious","Naira","0","Tech","0","Yes","","Self-contained","Mid-class area","#5000","Yes" +"2021/01/21 12:23:23 AM GMT+1","23","Male","Master's Degree","Nigeria","Lagos","Most industrious in the country","Naira","50000","Construction ","2","Not completely","1/2","Self-contained","Mid-class area","12,500","Yes" +"2021/01/21 12:23:51 AM GMT+1","20","Female","Bachelor's Degree/Equivalent","Nigeria","Enugu","Unknown","Naira","10000","Tech","0","No","","Self-contained","Low brow area","5000","Yes" +"2021/01/21 2:14:16 AM GMT+1","20","Female","High/Secondary School","Nigeria","Lagos","Most industrious in the country","Naira","50000","Tech","1","No","","Mini Flat","High brow area","N/A","Yes" +"2021/01/21 4:21:58 AM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Enugu","Industrious","Naira","20000","Engineering","1","No","","Self-contained","I do not pay rents","180,000","Yes" +"2021/01/21 6:15:04 AM GMT+1","28","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","200000","Utility","3","Yes","","Self-contained","Low brow area","15","Yes" +"2021/01/21 6:28:59 AM GMT+1","19","Female","High/Secondary School","Nigeria","Kwara","","Naira","0","Tech","0","No","","Self-contained","Mid-class area","13,200","Indifferent" +"2021/01/21 6:51:16 AM GMT+1","24","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","30000","Clothing","3","Yes","","Self-contained","Mid-class area","5000","Yes" +"2021/01/21 6:55:45 AM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria ","Lagos","Most industrious in the country","Naira","100000","Architecture ","0","Yes","","Self-contained","Mid-class area","40, 000","Yes" +"2021/01/21 7:16:06 AM GMT+1","25","Male","Master's Degree","Nigeria","lagos","Industrious","Naira","4000","Tech","1","Yes","","Studio apartment","Mid-class area","5000","Yes" +"2021/01/21 7:57:44 AM GMT+1","21","Female","Bachelor's Degree/Equivalent","NIGERIA","ENUGU","Industrious","NAIRA","0","Tech","0","No","","Mini Flat","Mid-class area","150,000","No" +"2021/01/21 8:06:10 AM GMT+1","18","Female","Bachelor's Degree/Equivalent","Nigeria","Ekiti state","Industrious","Naira","0","Tech","1","No","","Hostel","Mid-class area","N/A","No" +"2021/01/21 8:47:17 AM GMT+1","19","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","0","Tech ","1","No","","Neither. I do not pay rents","I do not pay rents","N/A","Indifferent" +"2021/01/21 8:55:42 AM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria ","Lagos, Lagos","Most industrious in the country","Naira","0","Tech","1","No","","Neither. I do not pay rents","Mid-class area","None","Yes" +"2021/01/21 8:58:17 AM GMT+1","23","Female","High/Secondary School","NIGERIA ","FEDERAL CAPITAL TERRITORY.","Industrious","NAIRA","25000","Education ","0.4","No","","Neither. I do not pay rents","Mid-class area","100000","Yes" +"2021/01/21 9:19:40 AM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Industrious","Naira","500000","Tech","3","Yes","","Full Flat","Mid-class area","167000","Yes" +"2021/01/21 10:06:46 AM GMT+1","27","Male","Bachelor's Degree/Equivalent","Nigeria","FCT Abuja","Industrious","Naira","100000","Education","2","Yes","","Single room","Mid-class area","3333","Yes" +"2021/01/21 10:14:53 AM GMT+1","25","Male","Bachelor's Degree/Equivalent","Nigeria","Rivers","Industrious","Naira","30000","Tech","2","Yes","","Self-contained","Mid-class area","180000","Yes" +"2021/01/21 10:38:31 AM GMT+1","25","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","170000","FinTech","2","Not completely","1/3","Mini Flat","Low brow area","25000","Yes" +"2021/01/21 11:19:32 AM GMT+1","24","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira, Dollars","800000","Tech","2","Yes","2/3","Mini Flat","Mid-class area","45","Yes" +"2021/01/21 11:21:11 AM GMT+1","22","Male","Bachelor's Degree/Equivalent","Nigeria","Abuja","Industrious","Naira","33000","Tech","0","No","0","Neither. I do not pay rents","Mid-class area","N/A","Yes" +"2021/01/21 12:44:55 PM GMT+1","25","Female","Bachelor's Degree/Equivalent","Nigeria","Oyo","Industrious","Naira","0","Tech","0","No","","Self-contained","Mid-class area","11600","Yes" +"2021/01/21 12:56:31 PM GMT+1","20","Male","Bachelor's Degree/Equivalent","Nigeria","Ogun State","Industrious","Naira","0","Student","0","No","","Self-contained","Mid-class area","10,000","Yes" +"2021/01/21 1:02:15 PM GMT+1","22","Male","Bachelor's Degree/Equivalent","Nigeria","Akwa Ibom","Unknown","Naira","0","Tech","0","Not completely","1/3","Self-contained","Mid-class area","1500","Indifferent" +"2021/01/21 1:14:32 PM GMT+1","22","Male","Bachelor's Degree/Equivalent","Nigeria","Cross river","Industrious","Naira ","0","Tech ","0","No","","Self-contained","Mid-class area","10000","Yes" +"2021/01/21 1:21:16 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","0","Tech","1","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/21 2:04:58 PM GMT+1","22","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","150000","Tech","2","Not completely","1/3","Shared Flat","Mid-class area","83000","Yes" +"2021/01/21 2:28:47 PM GMT+1","28","Female","Master's Degree","Nigeria","Federal Capital Territory","Industrious","Naira","300000","Tech","5","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/21 3:08:29 PM GMT+1","25","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","20000","Tech","0.5","Yes","","Self-contained","Mid-class area","60000","Yes" +"2021/01/21 3:36:20 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria ","Lagos ","Most industrious in the country","Naira ","0","Geoscience ","0","Yes","","Shared Flat","Mid-class area","30000 naira","Yes" +"2021/01/21 3:49:31 PM GMT+1","20","Male","Bachelor's Degree/Equivalent","Nigeria","Abia State","Industrious","Naira","20000","Tech","2","No","I do pay for my accommodation","1 room face me I face you ","Low brow area","7000","Yes" +"2021/01/21 4:02:25 PM GMT+1","21","Female","Bachelor's Degree/Equivalent","NIGERIA","LAGOS","Industrious","NAIRA","0","Tech","0","No","","Shared Duplex","Mid-class area","16,666 NAIRA","Yes" +"2021/01/21 4:04:50 PM GMT+1","25","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos and Osun","Industrious","Naira","0","Health","0","No","","Self-contained","Mid-class area","25000","Yes" +"2021/01/21 4:43:06 PM GMT+1","21","Female","Bachelor's Degree/Equivalent","Nigeria","Kwara","Unknown","Naira","0","Tech","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/21 4:49:03 PM GMT+1","19","Female","High/Secondary School","Nigeria","Oyo State","Non-Industrious","Dollars","100","Law","2","No","","Self-contained","Mid-class area","12500","Yes" +"2021/01/21 4:56:55 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","NIGERIA ","STATE ","Industrious","NAIRA ","20000","AUDIT FIRM ","0","Not completely","1/2","Self-contained","Mid-class area","5000","Yes" +"2021/01/21 5:03:48 PM GMT+1","29","Male","Bachelor's Degree/Equivalent","NIGERIA","FEDERAL CAPITAL TERRITORY, ABUJA","Industrious","Naira","62000","Education/Teaching","1","Yes","","Shared Flat","Low brow area","6250","Yes" +"2021/01/21 7:07:41 PM GMT+1","26","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","90000","Tech","1","Not completely","1/3","Self-contained","High brow area","12500","Yes" +"2021/01/21 7:17:46 PM GMT+1","22","Male","Bachelor's Degree/Equivalent","NIGERIA","Oyo","Non-Industrious","Naira","0","Media","2","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/21 7:49:00 PM GMT+1","25","Female","Bachelor's Degree/Equivalent","NIGERIA","LAGOS STATE","Industrious","NARIA","0","Real Estate","1","No","","I do not have an accomodation","I do not pay rents","N/A","Yes" +"2021/01/21 8:54:18 PM GMT+1","24","Female","Bachelor's Degree/Equivalent","Nigeria","Kwara","Non-Industrious","Naira","0","Tech","1","No","","Neither. I do not pay rents","I do not pay rents","N/A","No" +"2021/01/21 9:41:45 PM GMT+1","27","Male","Bachelor's Degree/Equivalent","Nigeria","Oyo","Industrious","Naira","103000","Health","1","Yes","","Full Flat","High brow area","22000","Yes" +"2021/01/21 9:59:02 PM GMT+1","24","Female","Bachelor's Degree/Equivalent","NIGERIA ","EKITI","Non-Industrious","Naira","0","Engineering ","2","No","","Neither. I do not pay rents","I do not pay rents","N/A","No" +"2021/01/21 10:13:58 PM GMT+1","27","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","0","Hospitality","4","Yes","","Self-contained","Mid-class area","20833","Yes" +"2021/01/21 10:33:53 PM GMT+1","20","Female","High/Secondary School","Nigeria","Kano","Industrious","Naira","0","Student","0","No","","Shared Flat","Mid-class area","5800","No" +"2021/01/21 10:55:26 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Cross River","Non-Industrious","Naira","20000","Education","1","Yes","","Mini Flat","Mid-class area","35,000","Yes" +"2021/01/21 11:28:57 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos State","Most industrious in the country","Naira","50000","Tech","7","Not completely","1/3","Mini Flat","Mid-class area","10000","Yes" +"2021/01/21 11:59:24 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Ondo","Unknown","Naira","50000","UI Design","1","No","","Self-contained","Mid-class area","10000","Yes" +"2021/01/22 1:40:08 AM GMT+1","24","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Industrious","Naira","47000","Tech","1","No","I don't pay","Shared hostel space","Mid-class area","17500","Yes" +"2021/01/22 11:13:54 AM GMT+1","25","Female","Bachelor's Degree/Equivalent","Nigeria","Ondo","Non-Industrious","Naira","0","Tech","0","No","","Neither. I do not pay rents","I do not pay rents","N/A","No" +"2021/01/22 11:59:35 AM GMT+1","19","Female","Bachelor's Degree/Equivalent","Nigeria","Rivers State","Industrious","Naira","0","Tech","1","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/22 1:35:50 PM GMT+1","23","Male","High/Secondary School","Nigeria","FCT Abuja","Industrious","Naira","30000","Hospitality","3","Not completely","1/3","Self-contained","Low brow area","6500","Yes" +"2021/01/22 2:53:26 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Abuja","Industrious","Naira","60000","Law","2","Yes","","Self-contained","Mid-class area","25000","Yes" +"2021/01/22 2:57:48 PM GMT+1","23","Female","Bachelor's Degree/Equivalent","Nigeria","Oyo","Industrious","Naira","40000","Tech","1","Yes","","Self-contained","Mid-class area","10000","Indifferent" +"2021/01/22 4:48:25 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Ogun","Industrious","Naira","0","Data Science, Architecture, Research","1","No","","Neither. I do not pay rents","I do not pay rents","N/A","Indifferent" +"2021/01/22 6:32:59 PM GMT+1","25","Female","Bachelor's Degree/Equivalent","Nigeria ","Lagos ","Most industrious in the country","Naira","0","Health ","0","No","","Full Flat","Mid-class area","N/A","Yes" +"2021/01/22 11:02:24 PM GMT+1","22","Female","Master's Degree","NIGERIA","LAGOS","Industrious","NAIRA","0","Student","3","No","","Neither. I do not pay rents","High brow area","N/A","Yes" +"2021/01/23 7:59:20 AM GMT+1","21","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Non-Industrious","Naira","20000","Tech","0","Yes","","Studio apartment","Low brow area","1000","Yes" +"2021/01/23 5:20:26 PM GMT+1","22","Female","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","0","Tech, science. ","1","No","","Neither. I do not pay rents","I do not pay rents","N/A","Yes" +"2021/01/23 6:31:45 PM GMT+1","21","Female","High/Secondary School","Kenya","Nairobi","Most industrious in the country","Kenyan Shillings","0","Tech","0","No","1/4","Self-contained","Mid-class area","10000","Yes" +"2021/01/24 8:52:09 PM GMT+1","25","Female","Bachelor's Degree/Equivalent","Nigeria","Anambra","Industrious","Naira","10000","Tech","2","Not completely","1/2","Neither. I do not pay rents","Mid-class area","3000","Yes" +"2021/01/25 10:09:33 AM GMT+1","29","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","100000","Aviation","8","Yes","1/2","Mini Flat","Mid-class area","33,333","Yes" +"2021/01/25 10:17:15 AM GMT+1","29","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","70000","Education","10","Yes","","Mini Flat","Low brow area","10000","Yes" +"2021/01/25 10:21:30 AM GMT+1","29","Female","Bachelor's Degree/Equivalent","NIGERIA","OGUN STATE","Industrious","NAIRA","40000","Graphics and printing ","8","No","","Neither. I do not pay rents","I do not pay rents","200,000","Yes" +"2021/01/25 10:32:16 AM GMT+1","29","Male","Bachelor's Degree/Equivalent","Nigeria","LAGOS","Industrious","Naira","143000","Banking","6","Yes","","Self-contained","Mid-class area","17000","Yes" +"2021/01/25 10:51:08 AM GMT+1","28","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Industrious","Naira","150000","Tech","2","No","","Full Flat","Mid-class area","60000","Yes" +"2021/01/25 11:22:15 AM GMT+1","24","Female","Bachelor's Degree/Equivalent","Nigeria ","Lagos ","Industrious","Naira","80000","Tech ","1","Yes","","Shared Flat","Mid-class area","300000","Yes" +"2021/01/25 1:44:50 PM GMT+1","29","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Most industrious in the country","Naira","75000","Advertising, Research","2","Not completely","1/3","Mini Flat","Low brow area","10000","Yes" +"2021/01/26 6:58:33 AM GMT+1","24","Female","Bachelor's Degree/Equivalent","Kenya","Nairobi","Industrious","Kenyan Shillings","64000","Tech","2","Yes","","Studio apartment","Low brow area","18000","Yes" +"2021/01/26 7:54:09 AM GMT+1","25","Male","Bachelor's Degree/Equivalent","Nigeria","Lagos","Industrious","Naira","50000","Insurance","2","Not completely","1/4","Mini Flat","Mid-class area","18000","Indifferent" +"2021/01/26 9:59:20 AM GMT+1","26","Male","High/Secondary School","NIGERIA ","Lagos","Industrious","Naira","40000","Tech ","0","Yes","1/2","Self-contained","Mid-class area","12000","Yes" +"2021/01/26 1:39:35 PM GMT+1","21","Female","High/Secondary School","Nigeria","ogun","Industrious","Naira","0","nil","0","No","","Self-contained","I do not pay rents","140","Yes" \ No newline at end of file diff --git a/Level 2/Intermediate/accomodation_assessment.ipynb b/Level 2/Intermediate/accomodation_assessment.ipynb new file mode 100644 index 0000000..0d39eb2 --- /dev/null +++ b/Level 2/Intermediate/accomodation_assessment.ipynb @@ -0,0 +1,1453 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### A Data Collection, Cleaning and Exploratory Analysis on Accomodation Cost in comparison with Income among Young Adults" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Introduction" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Most at times, it is usually challenging for young adults who are starting out their careers or who are getting into the phase of being independent. \n", + "\n", + "Knowing that many of them go to bigger cities to make ends meet or search for greener pastures, \n", + "accommodation is usually a major factor of concern, which at times limits one's preference.\n", + "\n", + "The goal of this project is to research into this, to know how much young adults (18 - 29 years) \n", + "spend on accommodation, in comparison to their incomes.\n", + "\n", + "Data Collection was done via this [form](https://docs.google.com/forms/d/1VhtGHUs8XawrgDvc-zqtAreu5-1-BDDDs2mmmh8-iy8/edit?usp=drivesdk) which garnered 121 responses over a 7 day-period. \n", + "\n", + "The responses are collected in a CSV file which is used in this notebook. " + ] + }, + { + "cell_type": "code", + "execution_count": 189, + "metadata": {}, + "outputs": [], + "source": [ + "#importing required libraries\n", + "import pandas as pd\n", + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 190, + "metadata": {}, + "outputs": [], + "source": [ + "#importing dataset\n", + "data = pd.read_csv('Accommodation Assessment Form.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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TimestampAgeGenderMaximum Level of EducationCountryState/ProvinceBased on your answer above, how industrious is your State of residence?CurrencyMonthly Salary in the currency you mentioned aboveCareer IndustryYears of working experienceDo you foot your accommodation bills?If you selected \"Not completely\", what fraction of the rent do you pay?Accommodation RentedLocation of accommodationCost of your accommodation per monthDo you think accommodation prices are generally high in your State of residence for young adults?
02021/01/20 7:57:57 AM GMT+124MaleBachelor's Degree/EquivalentNigeriaLagosIndustriousNaira150000Accounting & Tech1.0YesNaNFull FlatMid-class area80000Yes
12021/01/20 9:02:40 AM GMT+127FemaleBachelor's Degree/EquivalentKenyaNairobiMost industrious in the countryKenyan Shillings150000Software Engineer3.0YesNaNShared FlatMid-class area35000Yes
22021/01/20 9:07:23 AM GMT+125FemaleHigh/Secondary SchoolSouth AfricaCape TownNon-IndustriousRand2000Hospitality5.0YesNaNShared FlatMid-class areaR3500Yes
32021/01/20 9:27:25 AM GMT+128FemaleBachelor's Degree/EquivalentNigeriaLagosMost industrious in the countryNaira0IT0.0NoNaNNeither. I do not pay rentsI do not pay rentsNaNYes
42021/01/20 9:27:53 AM GMT+124FemaleBachelor's Degree/EquivalentNigeriaLagosIndustriousNaira70000Tech1.0Not completely1/4Neither. I do not pay rentsLow brow areaN/AYes
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" + ], + "text/plain": [ + " Timestamp Age Gender Maximum Level of Education \\\n", + "0 2021/01/20 7:57:57 AM GMT+1 24 Male Bachelor's Degree/Equivalent \n", + "1 2021/01/20 9:02:40 AM GMT+1 27 Female Bachelor's Degree/Equivalent \n", + "2 2021/01/20 9:07:23 AM GMT+1 25 Female High/Secondary School \n", + "3 2021/01/20 9:27:25 AM GMT+1 28 Female Bachelor's Degree/Equivalent \n", + "4 2021/01/20 9:27:53 AM GMT+1 24 Female Bachelor's Degree/Equivalent \n", + "\n", + " Country State/Province \\\n", + "0 Nigeria Lagos \n", + "1 Kenya Nairobi \n", + "2 South Africa Cape Town \n", + "3 Nigeria Lagos \n", + "4 Nigeria Lagos \n", + "\n", + " Based on your answer above, how industrious is your State of residence? \\\n", + "0 Industrious \n", + "1 Most industrious in the country \n", + "2 Non-Industrious \n", + "3 Most industrious in the country \n", + "4 Industrious \n", + "\n", + " Currency Monthly Salary in the currency you mentioned above \\\n", + "0 Naira 150000 \n", + "1 Kenyan Shillings 150000 \n", + "2 Rand 2000 \n", + "3 Naira 0 \n", + "4 Naira 70000 \n", + "\n", + " Career Industry Years of working experience \\\n", + "0 Accounting & Tech 1.0 \n", + "1 Software Engineer 3.0 \n", + "2 Hospitality 5.0 \n", + "3 IT 0.0 \n", + "4 Tech 1.0 \n", + "\n", + " Do you foot your accommodation bills? \\\n", + "0 Yes \n", + "1 Yes \n", + "2 Yes \n", + "3 No \n", + "4 Not completely \n", + "\n", + " If you selected \"Not completely\", what fraction of the rent do you pay? \\\n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 1/4 \n", + "\n", + " Accommodation Rented Location of accommodation \\\n", + "0 Full Flat Mid-class area \n", + "1 Shared Flat Mid-class area \n", + "2 Shared Flat Mid-class area \n", + "3 Neither. I do not pay rents I do not pay rents \n", + "4 Neither. I do not pay rents Low brow area \n", + "\n", + " Cost of your accommodation per month \\\n", + "0 80000 \n", + "1 35000 \n", + "2 R3500 \n", + "3 NaN \n", + "4 N/A \n", + "\n", + " Do you think accommodation prices are generally high in your State of residence for young adults? \n", + "0 Yes \n", + "1 Yes \n", + "2 Yes \n", + "3 Yes \n", + "4 Yes " + ] + }, + "execution_count": 191, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#printing the first 5 rows\n", + "data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 192, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 121 entries, 0 to 120\n", + "Data columns (total 17 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Timestamp 121 non-null object \n", + " 1 Age 121 non-null int64 \n", + " 2 Gender 121 non-null object \n", + " 3 Maximum Level of Education 121 non-null object \n", + " 4 Country 121 non-null object \n", + " 5 State/Province 121 non-null object \n", + " 6 Based on your answer above, how industrious is your State of residence? 118 non-null object \n", + " 7 Currency 121 non-null object \n", + " 8 Monthly Salary in the currency you mentioned above 121 non-null int64 \n", + " 9 Career Industry 121 non-null object \n", + " 10 Years of working experience 121 non-null float64\n", + " 11 Do you foot your accommodation bills? 121 non-null object \n", + " 12 If you selected \"Not completely\", what fraction of the rent do you pay? 28 non-null object \n", + " 13 Accommodation Rented 121 non-null object \n", + " 14 Location of accommodation 121 non-null object \n", + " 15 Cost of your accommodation per month 83 non-null object \n", + " 16 Do you think accommodation prices are generally high in your State of residence for young adults? 121 non-null object \n", + "dtypes: float64(1), int64(2), object(14)\n", + "memory usage: 16.2+ KB\n" + ] + } + ], + "source": [ + "data.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AgeMonthly Salary in the currency you mentioned aboveYears of working experience
count121.000000121.000000121.000000
mean23.42148860587.6033061.492975
std2.798071113215.1061551.840282
min18.0000000.0000000.000000
25%22.0000000.0000000.000000
50%23.00000020000.0000001.000000
75%25.00000070000.0000002.000000
max29.000000800000.00000010.000000
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" + ], + "text/plain": [ + " Age Monthly Salary in the currency you mentioned above \\\n", + "count 121.000000 121.000000 \n", + "mean 23.421488 60587.603306 \n", + "std 2.798071 113215.106155 \n", + "min 18.000000 0.000000 \n", + "25% 22.000000 0.000000 \n", + "50% 23.000000 20000.000000 \n", + "75% 25.000000 70000.000000 \n", + "max 29.000000 800000.000000 \n", + "\n", + " Years of working experience \n", + "count 121.000000 \n", + "mean 1.492975 \n", + "std 1.840282 \n", + "min 0.000000 \n", + "25% 0.000000 \n", + "50% 1.000000 \n", + "75% 2.000000 \n", + "max 10.000000 " + ] + }, + "execution_count": 193, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Data Cleaning & Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AgeGenderMaximum Level of EducationCountryState/ProvinceBased on your answer above, how industrious is your State of residence?CurrencyMonthly Salary in the currency you mentioned aboveCareer IndustryYears of working experienceDo you foot your accommodation bills?If you selected \"Not completely\", what fraction of the rent do you pay?Accommodation RentedLocation of accommodationCost of your accommodation per monthDo you think accommodation prices are generally high in your State of residence for young adults?
024MaleBachelor's Degree/EquivalentNigeriaLagosIndustriousNaira150000Accounting & Tech1.0YesNaNFull FlatMid-class area80000Yes
127FemaleBachelor's Degree/EquivalentKenyaNairobiMost industrious in the countryKenyan Shillings150000Software Engineer3.0YesNaNShared FlatMid-class area35000Yes
225FemaleHigh/Secondary SchoolSouth AfricaCape TownNon-IndustriousRand2000Hospitality5.0YesNaNShared FlatMid-class areaR3500Yes
328FemaleBachelor's Degree/EquivalentNigeriaLagosMost industrious in the countryNaira0IT0.0NoNaNNeither. I do not pay rentsI do not pay rentsNaNYes
424FemaleBachelor's Degree/EquivalentNigeriaLagosIndustriousNaira70000Tech1.0Not completely1/4Neither. I do not pay rentsLow brow areaN/AYes
\n", + "
" + ], + "text/plain": [ + " Age Gender Maximum Level of Education Country State/Province \\\n", + "0 24 Male Bachelor's Degree/Equivalent Nigeria Lagos \n", + "1 27 Female Bachelor's Degree/Equivalent Kenya Nairobi \n", + "2 25 Female High/Secondary School South Africa Cape Town \n", + "3 28 Female Bachelor's Degree/Equivalent Nigeria Lagos \n", + "4 24 Female Bachelor's Degree/Equivalent Nigeria Lagos \n", + "\n", + " Based on your answer above, how industrious is your State of residence? \\\n", + "0 Industrious \n", + "1 Most industrious in the country \n", + "2 Non-Industrious \n", + "3 Most industrious in the country \n", + "4 Industrious \n", + "\n", + " Currency Monthly Salary in the currency you mentioned above \\\n", + "0 Naira 150000 \n", + "1 Kenyan Shillings 150000 \n", + "2 Rand 2000 \n", + "3 Naira 0 \n", + "4 Naira 70000 \n", + "\n", + " Career Industry Years of working experience \\\n", + "0 Accounting & Tech 1.0 \n", + "1 Software Engineer 3.0 \n", + "2 Hospitality 5.0 \n", + "3 IT 0.0 \n", + "4 Tech 1.0 \n", + "\n", + " Do you foot your accommodation bills? \\\n", + "0 Yes \n", + "1 Yes \n", + "2 Yes \n", + "3 No \n", + "4 Not completely \n", + "\n", + " If you selected \"Not completely\", what fraction of the rent do you pay? \\\n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 1/4 \n", + "\n", + " Accommodation Rented Location of accommodation \\\n", + "0 Full Flat Mid-class area \n", + "1 Shared Flat Mid-class area \n", + "2 Shared Flat Mid-class area \n", + "3 Neither. I do not pay rents I do not pay rents \n", + "4 Neither. I do not pay rents Low brow area \n", + "\n", + " Cost of your accommodation per month \\\n", + "0 80000 \n", + "1 35000 \n", + "2 R3500 \n", + "3 NaN \n", + "4 N/A \n", + "\n", + " Do you think accommodation prices are generally high in your State of residence for young adults? \n", + "0 Yes \n", + "1 Yes \n", + "2 Yes \n", + "3 Yes \n", + "4 Yes " + ] + }, + "execution_count": 194, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#The timestamp column is not needed in our analysis. This column will be dropped\n", + "data = data.drop('Timestamp', axis=1)\n", + "data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": {}, + "outputs": [], + "source": [ + "#As this project is targeted towards young adults who are footing their accomodation bills.\n", + "#We drop rows of people who do not foot their accomodation bills\n", + "data = data.loc[data['Do you foot your accommodation bills?'] != 'No']\n" + ] + }, + { + "cell_type": "code", + "execution_count": 196, + "metadata": {}, + "outputs": [], + "source": [ + "#the subset of people who pay their rents with roommates\n", + "half_rent = data.loc[data['Do you foot your accommodation bills?'] == 'Not completely']" + ] + }, + { + "cell_type": "code", + "execution_count": 197, + "metadata": {}, + "outputs": [], + "source": [ + "#the subset of people who pay their rents themselves completely\n", + "complete_rent = data.loc[data['Do you foot your accommodation bills?'] == 'Yes']" + ] + }, + { + "cell_type": "code", + "execution_count": 198, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Naira 36\n", + "Kenyan Shillings 2\n", + "Rand 1\n", + "Name: Currency, dtype: int64" + ] + }, + "execution_count": 198, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#due to the economy differences we will split the analysis into subsets depending on the currency they earn in\n", + "complete_rent['Currency'] = complete_rent['Currency'].replace({'Naira ':'Naira', ' Naira':'Naira', 'NAIRA':'Naira', 'Naira, Dollars':'Naira'})\n", + "complete_rent['Currency'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 199, + "metadata": {}, + "outputs": [], + "source": [ + "#As the data from people who earn in Kenyan Shillings and Rand is very little. \n", + "#We can not draw suitable conclusions from so little data\n", + "#We will only concern ourselves with those who earn in Naira" + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "metadata": {}, + "outputs": [], + "source": [ + "naira_complete_rent = complete_rent.loc[complete_rent['Currency'] == 'Naira']\n" + ] + }, + { + "cell_type": "code", + "execution_count": 201, + "metadata": {}, + "outputs": [], + "source": [ + "#cleaning the location to be of accepted format\n", + "naira_complete_rent['State/Province'] = naira_complete_rent['State/Province'].replace({'FCT Abuja':'Abuja', 'FCT':'Abuja', 'FEDERAL CAPITAL TERRITORY, ABUJA':'Abuja', 'LAGOS':'Lagos', 'OYO':'Oyo', 'Oyo state':'Oyo'})\n" + ] + }, + { + "cell_type": "code", + "execution_count": 202, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Self-contained 17\n", + "Mini Flat 5\n", + "Shared Flat 5\n", + "Full Flat 4\n", + "Studio apartment 3\n", + "Single room 1\n", + "Shared Duplex 1\n", + "Name: Accommodation Rented, dtype: int64" + ] + }, + "execution_count": 202, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "naira_complete_rent['Accommodation Rented'].value_counts()\n", + "#The most type of accomodation is Self-contained, Mini Flats and Shared Flats are common also. " + ] + }, + { + "cell_type": "code", + "execution_count": 203, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.countplot(x='Accommodation Rented', data=naira_complete_rent)\n", + "plt.title('Types of Accommodation Rented')\n", + "plt.xticks(rotation=90)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "80000 4\n", + "20000 3\n", + "100000 3\n", + "0 3\n", + "200000 3\n", + "40000 2\n", + "50000 2\n", + "30000 2\n", + "500000 2\n", + "150000 2\n", + "800000 1\n", + "190000 1\n", + "70000 1\n", + "103000 1\n", + "145000 1\n", + "4000 1\n", + "143000 1\n", + "450000 1\n", + "60000 1\n", + "62000 1\n", + "Name: Monthly Salary in the currency you mentioned above, dtype: int64" + ] + }, + "execution_count": 204, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "naira_complete_rent['Monthly Salary in the currency you mentioned above'].value_counts()\n", + "# the monthly salary range is 0-800,000 Naira" + ] + }, + { + "cell_type": "code", + "execution_count": 205, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Mid-class area 26\n", + "Low brow area 8\n", + "High brow area 2\n", + "Name: Location of accommodation, dtype: int64" + ] + }, + "execution_count": 205, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "naira_complete_rent['Location of accommodation'].value_counts()\n", + "#Over 70% of the respondents live in Mid-class areas" + ] + }, + { + "cell_type": "code", + "execution_count": 206, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.countplot(x='Location of accommodation', data=naira_complete_rent)\n", + "plt.title('Locations of Accommodations')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "metadata": {}, + "outputs": [], + "source": [ + "#the Cost of accomodation per month will have to be cleaned as some rows contain strings, commas, and spaces\n", + "import re\n", + "naira_complete_rent['Cost of your accommodation per month'] = naira_complete_rent['Cost of your accommodation per month'].apply(lambda x: re.sub(r'[a-z\\s,#]+', '', x))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 209, + "metadata": {}, + "outputs": [], + "source": [ + "#convert the Cost of your accommodation per month column to integer\n", + "naira_complete_rent['Cost of your accommodation per month'] = naira_complete_rent['Cost of your accommodation per month'].astype('int')" + ] + }, + { + "cell_type": "code", + "execution_count": 210, + "metadata": {}, + "outputs": [], + "source": [ + "#The numbers 15 and 45 will be dropped as they are disrepancies in our data set \n", + "naira_complete_rent = naira_complete_rent[~naira_complete_rent['Cost of your accommodation per month'].isin([45, 15])]" + ] + }, + { + "cell_type": "code", + "execution_count": 211, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "5000 3\n", + "25000 3\n", + "17000 2\n", + "15000 2\n", + "10000 2\n", + "12000 1\n", + "300000 1\n", + "33333 1\n", + "2500 1\n", + "3333 1\n", + "6250 1\n", + "40000 1\n", + "23000 1\n", + "55000 1\n", + "120000 1\n", + "20833 1\n", + "20000 1\n", + "60000 1\n", + "167000 1\n", + "6500 1\n", + "1000 1\n", + "180000 1\n", + "700000 1\n", + "22000 1\n", + "30000 1\n", + "35000 1\n", + "80000 1\n", + "Name: Cost of your accommodation per month, dtype: int64" + ] + }, + "execution_count": 211, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "naira_complete_rent['Cost of your accommodation per month'].value_counts()\n", + "#The range of accommodation cost per month is 2500 - 700,000" + ] + }, + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [], + "source": [ + "#create a new column that shows the percent of income spent on accommodation\n", + "naira_complete_rent['percent_accommodation_income'] = naira_complete_rent['Cost of your accommodation per month']/naira_complete_rent['Monthly Salary in the currency you mentioned above']" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AgeGenderMaximum Level of EducationCountryState/ProvinceBased on your answer above, how industrious is your State of residence?CurrencyMonthly Salary in the currency you mentioned aboveCareer IndustryYears of working experienceDo you foot your accommodation bills?If you selected \"Not completely\", what fraction of the rent do you pay?Accommodation RentedLocation of accommodationCost of your accommodation per monthDo you think accommodation prices are generally high in your State of residence for young adults?percent_accommodation_income
024MaleBachelor's Degree/EquivalentNigeriaLagosIndustriousNaira150000Accounting & Tech1.0YesNaNFull FlatMid-class area80000Yes0.533333
927MaleBachelor's Degree/EquivalentNigeriaDeltaIndustriousNaira145000Engineering3.0YesNaNFull FlatLow brow area20000Yes0.137931
1423MaleBachelor's Degree/EquivalentNIGERIAOSUNNon-IndustriousNaira50000AGRICULTURE2.0YesNaNShared FlatLow brow area6500Yes0.130000
1528FemaleMaster's DegreeNigeriaAbujaIndustriousNaira500000Consulting2.0YesNaNStudio apartmentMid-class area55000Yes0.110000
1629MaleBachelor's Degree/EquivalentNigeriaLagosMost industrious in the countryNaira80000Development3.0YesNaNSelf-containedLow brow area15000Yes0.187500
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" + ], + "text/plain": [ + " Age Gender Maximum Level of Education Country State/Province \\\n", + "0 24 Male Bachelor's Degree/Equivalent Nigeria Lagos \n", + "9 27 Male Bachelor's Degree/Equivalent Nigeria Delta \n", + "14 23 Male Bachelor's Degree/Equivalent NIGERIA OSUN \n", + "15 28 Female Master's Degree Nigeria Abuja \n", + "16 29 Male Bachelor's Degree/Equivalent Nigeria Lagos \n", + "\n", + " Based on your answer above, how industrious is your State of residence? \\\n", + "0 Industrious \n", + "9 Industrious \n", + "14 Non-Industrious \n", + "15 Industrious \n", + "16 Most industrious in the country \n", + "\n", + " Currency Monthly Salary in the currency you mentioned above \\\n", + "0 Naira 150000 \n", + "9 Naira 145000 \n", + "14 Naira 50000 \n", + "15 Naira 500000 \n", + "16 Naira 80000 \n", + "\n", + " Career Industry Years of working experience \\\n", + "0 Accounting & Tech 1.0 \n", + "9 Engineering 3.0 \n", + "14 AGRICULTURE 2.0 \n", + "15 Consulting 2.0 \n", + "16 Development 3.0 \n", + "\n", + " Do you foot your accommodation bills? \\\n", + "0 Yes \n", + "9 Yes \n", + "14 Yes \n", + "15 Yes \n", + "16 Yes \n", + "\n", + " If you selected \"Not completely\", what fraction of the rent do you pay? \\\n", + "0 NaN \n", + "9 NaN \n", + "14 NaN \n", + "15 NaN \n", + "16 NaN \n", + "\n", + " Accommodation Rented Location of accommodation \\\n", + "0 Full Flat Mid-class area \n", + "9 Full Flat Low brow area \n", + "14 Shared Flat Low brow area \n", + "15 Studio apartment Mid-class area \n", + "16 Self-contained Low brow area \n", + "\n", + " Cost of your accommodation per month \\\n", + "0 80000 \n", + "9 20000 \n", + "14 6500 \n", + "15 55000 \n", + "16 15000 \n", + "\n", + " Do you think accommodation prices are generally high in your State of residence for young adults? \\\n", + "0 Yes \n", + "9 Yes \n", + "14 Yes \n", + "15 Yes \n", + "16 Yes \n", + "\n", + " percent_accommodation_income \n", + "0 0.533333 \n", + "9 0.137931 \n", + "14 0.130000 \n", + "15 0.110000 \n", + "16 0.187500 " + ] + }, + "execution_count": 213, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "naira_complete_rent.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 214, + "metadata": {}, + "outputs": [], + "source": [ + "#divide the dataset into 4 groups baseed on percent of income spent on accommodation \n", + "labels = ['low', 'medium', 'high', 'very high']\n", + "bins = [0.0, 0.25, 0.50, 0.75, 1.0]\n", + "naira_complete_rent['rent_category'] = pd.cut(naira_complete_rent['percent_accommodation_income'], bins=bins, labels=labels)" + ] + }, + { + "cell_type": "code", + "execution_count": 215, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "low 18\n", + "medium 5\n", + "high 1\n", + "very high 0\n", + "Name: rent_category, dtype: int64" + ] + }, + "execution_count": 215, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "naira_complete_rent['rent_category'].value_counts()\n", + "#75% of our responses spend between 1-25% of their incomes on accommodation\n", + "#21% of our responses spend between 26-50% of their incomes on accommodation" + ] + }, + { + "cell_type": "code", + "execution_count": 224, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rent_and_area_of_accommodation = pd.crosstab(naira_complete_rent['rent_category'], naira_complete_rent['Location of accommodation'])\n", + "rent_and_area_of_accommodation.plot(kind='bar')\n", + "plt.title('Rent_Percent_Category vs Location of Accomodation')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 225, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rent_and_type_of_accommodation = pd.crosstab(naira_complete_rent['rent_category'], naira_complete_rent['Accommodation Rented'])\n", + "rent_and_type_of_accommodation.plot(kind='bar')\n", + "plt.title('Rent_Percent_Category vs Accomodation Type')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 226, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rent_and_state = pd.crosstab(naira_complete_rent['rent_category'], naira_complete_rent['State/Province'])\n", + "rent_and_state.plot(kind='bar')\n", + "plt.title('Rent_Percent_Category vs State/Province')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 227, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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8+XK6d+/OjTfeWHc7t+XLl/PCCy/QvXv3unk89NBDzJs3j8GDBwPJh8gee+xR0Ho4wM2s7EUE/fv3Z9asWQ0Or70Ebbt27Ta7HG27du2oqamhurqav/zlL8yaNYuuXbsybNiwLe4uHxGMHj2a6667rmh1uwnFzMpe3759WbVqVV2Ab9iwgcWLF+c9/dq1a9l1113p2rUrzz77LE8++eQW4xxzzDFMmTKFN954A4A333yTV199taC6HeBmVvY6derElClTuOyyy/jkJz/JoEGDeOKJJ/Ke/vjjj6empoaBAwcyfvx4DjvssC3GOeCAA/jBD37Acccdx8CBAxkxYkTdgdLW8uVki8mXkzVrli8n2zRfTtbMrAw4wM3MMsoBbmaWUQ5wM7OMcoCbmWWUA9zMLKMc4GZWdiRx7rnn1nXX1NRQUVHBqFGjmpyuurq62XHakn9Kb2alVezfT+Tx+4hu3bqxaNEi3n//fbp06cKDDz7I3nvvXdw62kCze+CSJkp6Q9KinH67SXpQ0gvp3123bplmZsX1mc98hvvvT65FPnnyZM4+++y6YU899RRHHHEEBx10EEcccQTPPffcFtOvW7eOMWPGMHjwYA466CDuvffeNqu9Vj5NKJOA4+v1uxx4KCL6AA+l3WZmmXHWWWdx1113sX79ehYuXMihhx5aN6xfv37MnDmT+fPnc8011/Dtb397i+mvvfZahg8fzpw5c3j44Ye55JJLWLduXVuuQvNNKBExU1Jlvd6nAMPS578EqoHLilmYmdnWNHDgQJYuXcrkyZM54YQTNhu2du1aRo8ezQsvvIAkNmzYsMX006dPZ9q0adxwww0ArF+/nmXLlrXpZQJa2wb+0YhYCRARKyUVdlFbM7MSOPnkk/nWt75FdXX1ZjdgGD9+PJ/+9Ke55557WLp0KcOGDdti2ohg6tSp9O3btw0r3txWPwtF0lhJcyXNXbVq1dZenJlZ3saMGcNVV13FgQceuFn/tWvX1h3UnDRpUoPTjhw5kptuuonaCwLOnz9/q9bakNYG+OuS9gRI/77R2IgRMSEiqiKiqqKiopWLMzMrvh49enDRRRdt0f/SSy/liiuuYOjQoY3et3L8+PFs2LCBgQMHMmDAAMaPH7+1y91CXpeTTdvA74uIAWn3j4A1EXG9pMuB3SLi0ubm48vJFnt5vpysZY8vJ9u0ol5OVtJkYBbQV9IKSf8CXA+MkPQCMCLtNjOzNpTPWShnNzLomCLXYmZmLeCf0puZZZQD3MzaXFveyjFLWrpdHOBm1qY6d+7MmjVrHOL1RARr1qyhc+fOeU/ji1mZWZvq0aMHK1aswL8L2VLnzp3p0aNH3uM7wM2sTXXs2JHevXuXuoztgptQzMwyygFuZpZRDnAzs4xygJuZZZQD3MwsoxzgZmYZ5QA3M8soB7iZWUY5wM3MMsoBbmaWUQ5wM7OMcoCbmWWUA9zMLKMc4GZmGeUANzPLKAe4mVlGOcDNzDLKAW5mllEOcDOzjHKAm5lllAPczCyjCgpwSRdLWixpkaTJkjoXqzAzM2taqwNc0t7AvwNVETEAaA+cVazCzMysaYU2oXQAukjqAHQF/lF4SWZmlo9WB3hE/B24AVgGrATWRsT0+uNJGitprqS5q1atan2lZma2mUKaUHYFTgF6A3sB3SSdU3+8iJgQEVURUVVRUdH6Ss3MbDOFNKEcC7wSEasiYgNwN3BEccoyM7PmFBLgy4DDJHWVJOAYYElxyjIzs+YU0gY+G5gCPA08k85rQpHqMjOzZnQoZOKIuBq4uki1mJlZC/iXmGZmGeUANzPLKAe4mVlGOcDNzDLKAW5mllEOcDOzjHKAm5lllAPczCyjHOBmZhnlADczyygHuJlZRjnAzcwyygFuZpZRDnAzs4xygJuZZZQD3MwsoxzgZmYZ5QA3M8soB7iZWUY5wM3MMsoBbmaWUQ5wM7OMcoCbmWWUA9zMLKMc4GZmGVVQgEv6iKQpkp6VtETS4cUqzMzMmtahwOl/CjwQEadL6gR0LUJNZmaWh1YHuKSdgaOA8wAi4p/AP4tTlpmZNaeQJpR9gVXAf0uaL+k2Sd2KVJeZmTWjkCaUDsDBwLiImC3pp8DlwPjckSSNBcYC9OzZs4DFtVzl5fe36fKWdm7TxZlZmStkD3wFsCIiZqfdU0gCfTMRMSEiqiKiqqKiooDFmZlZrlYHeES8BiyX1DftdQzwt6JUZWZmzSr0LJRxwJ3pGSgvA+cXXpKZmeWjoACPiAVAVXFKMTOzlvAvMc3MMsoBbmaWUQ5wM7OMcoCbmWWUA9zMLKMc4GZmGeUANzPLKAe4mVlGOcDNzDLKAW5mllEOcDOzjHKAm5lllAPczCyjHOBmZhnlADczyygHuJlZRjnAzcwyygFuZpZRDnAzs4xygJuZZZQD3MwsoxzgZmYZ5QA3M8soB7iZWUY5wM3MMsoBbmaWUQUHuKT2kuZLuq8YBZmZWX6KsQd+EbCkCPMxM7MWKCjAJfUATgRuK045ZmaWr0L3wH8CXAp82NgIksZKmitp7qpVqwpcnJmZ1Wp1gEsaBbwREfOaGi8iJkREVURUVVRUtHZxZmZWTyF74EOBkyUtBe4Chku6oyhVmZlZs1od4BFxRUT0iIhK4CxgRkScU7TKzMysST4P3MwsozoUYyYRUQ1UF2NeZmaWH++Bm5lllAPczCyjHOBmZhnlADczyygHuJlZRjnAzcwyygFuZpZRDnAzs4xygJuZZZQD3MwsoxzgZmYZ5QA3M8uoolzMyqzYKi+/v02Xt/T6E9t0eWbF4D1wM7OMcoCbmWWUA9zMLKMc4GZmGeUANzPLKAe4mVlGOcDNzDLKAW5mllEOcDOzjHKAm5lllAPczCyjHOBmZhnV6gCXtI+khyUtkbRY0kXFLMzMzJpWyNUIa4BvRsTTknYC5kl6MCL+VqTazMysCa3eA4+IlRHxdPr8HWAJsHexCjMzs6YVpQ1cUiVwEDC7GPMzM7PmFXxDB0k7AlOBr0fE2w0MHwuMBejZs2ehizPbOr67Sxsvb23bLs+2SwXtgUvqSBLed0bE3Q2NExETIqIqIqoqKioKWZyZmeUo5CwUAbcDSyLix8UryczM8lHIHvhQ4FxguKQF6eOEItVlZmbNaHUbeEQ8BqiItZiZWQv4l5hmZhnlADczyygHuJlZRjnAzcwyygFuZpZRDnAzs4xygJuZZZQD3MwsoxzgZmYZ5QA3M8soB7iZWUY5wM3MMqrgGzqYmZVcmd6Qw3vgZmYZ5QA3M8soB7iZWUY5wM3MMsoBbmaWUQ5wM7OMcoCbmWWUA9zMLKMc4GZmGeUANzPLKAe4mVlGOcDNzDLKAW5mllEFBbik4yU9J+lFSZcXqygzM2teqwNcUnvgZuAzwAHA2ZIOKFZhZmbWtEL2wIcAL0bEyxHxT+Au4JTilGVmZs0p5IYOewPLc7pXAIfWH0nSWGBs2vmupOcKWOY2TbA7sLrNFvg9tdmitnd+7TJve3/9ejXUs5AAb2gNYoseEROACQUsJzMkzY2IqlLXYS3n1y7byvX1K6QJZQWwT053D+AfhZVjZmb5KiTA5wB9JPWW1Ak4C5hWnLLMzKw5rW5CiYgaSf8G/BloD0yMiMVFqyybyqKpaDvl1y7byvL1U8QWzdZmZpYB/iWmmVlGOcDNzDLKAW5mllEOcDOzjCrkhzwGSLoGeBR4IiLWlboeaxlJu5L8nqHufyEini5dRdYS6TWZPsrmr9+y0lXUtnwWSoEkjQGOBA4H3iEJ85kRcW9JC7NmSfo+cB7wEpt+RRwRMbxkRVneJI0DrgZeBz5Me0dEDCxdVW3LAV4kkj4GfB74FrBrROxU4pKsGel1eQ5ML8ZmGSPpReDQiFhT6lpKxW3gBZJ0m6QngFtIvsadDuxa2qosT4uAj5S6CGu15cDaUhdRSm4DL1x3kl+ivgW8CayOiJqSVmT5ug6YL2kR8EFtz4g4uXQlWXMkfSN9+jJQLel+Nn/9flySwkrAAV6giDgNQNL+wEjgYUntI6JHaSuzPPwS+CHwDJvaUG3bV9s8uSx9dEofZcdt4AWSNAr4FHAUSdPJLODRiJhY0sKsWZIeiYijS12HWWs5wAsk6WZgJklo+3K6GSLpxyRfvaex+Vdwn0aYAZL+yJb3IFgLzAVujYj1bV9V23KAF4GkjwKD086nIuKNUtZj+ZH0cAO9fRphRkj6KVABTE57nQm8BnQBdo6Ic0tVW1txgBdI0hnADUA1yV2KPgVcEhFTSlmX2fZO0syIOKqhfpIWR0T/UtXWVnwQs3BXAoNr97olVQB/ARzg2zhJVzXUPyKuaetarFUqJPWs/eWlpJ4k98YEKItz+x3ghWtXr8lkDT6/PityL33QGRgFLClRLdZy3wQek/QSybff3sC/SupGcobRds9NKAWS9CNgIJu3wy2MiMtKV5W1hqQdgGkRMbLUtVh+0tesH0mAP1sOBy5zOcCLQNLngKEkb6KZEXFPiUuyVkgvbPVURPQpdS3WOEnDI2KGpM82NDwi7m7rmkrFTShFEBFTgamlrsNaRtIzbDoNrT3JGQ1u/972HQ3MAE5Ku2tfQ6XPyybAvQfeSpLeYctzUCF9E0XEzm1ckrWQpF45nTXA674MQnZI6gx8Dqhk085olNNBaO+Bt5KvNphdknaOiLdJLv+ba2dJRMSbpajLWuwPJNcgehqobfsuqz1S74Fb2ZF0X0SMkvQKyT+8cgZHROxbotKsBSQtiogBpa6jlBzgZpZJkiYAN0XEM6WupVQc4FZ2JB3c1HBfC2XblnPwuQPQh+Sysh+w6fiT78hjtr3KuQZKZ6AK+CvJP/9AYHZEHFmq2qx59Q4+byEiXm2rWkrNBzGt7ETEpwEk3QWMrf0KLmkAyS3xbBtWTgHdHP/k28pZv9z204hYBAwqXTlmLeM9cCtnSyTdBtxB0qZ6Dr4WimWI28CtbKU/BPkqyd2UILkxxy3ldj0Nyy4HuJU1SV2AnhHxXKlrMWspt4Fb2ZJ0MrAAeCDtHiRpWkmLMmsBB7iVs6uBISQ/xyYiFpBcV8MsExzgVs5qImJtqYsway2fhWLlbJGkLwDtJfUB/h14osQ1meXNe+BWzsYB/Ul+hv0bYC1wUUkrMmsBB7iVswPSRweSn9WfAswpaUVmLeDTCK1sSXqO5Kfzi4APa/v7p9qWFW4Dt3K2KiL+WOoizFrLe+BWtiQdA5wNPETSDg6U101xLdu8B27l7HygH9CRTU0oZXVTXMs2B7iVs09GxIGlLsKstXwWipWzJyUdUOoizFrLbeBWtiQtAT4OvEKZ3pLLss0BbmWrsVtz+TRCywoHuJlZRrkN3MwsoxzglnmSzpO0VxHnV5le5Mpsm+YAt22KEi19X54HFC3ASa4JvtUDXFL7rb0M2745wK3k0j3eJZJ+BjwNjJc0R9JCSd+rN84vJC2WNF1SF0mnA1XAnZIWpLdIa2gZgyU9Iemvkp6StFM6z0clPZ0+jkhHvx74VDq/iyW1l/SjnJouSOfZTtLP0nruk/Q/aT1IOkbSfEnPSJooaYe0/1JJV0l6DLhc0tM5NfaRNG8rbWbbHkWEH36U9EGyx/shcBhwHDCB5JS+dsB9JDcdrgRqgEHpNL8DzkmfVwNVTcy/E/AyMDjt3pnkR2xdgc5pvz7A3PT5MOC+nOnHAlemz3cA5gK9gdOB/0nr/Bjwv2m/zsBy4BPpNL8Cvp4+XwpcmjPvh3PW6f8B40r9eviRnYf3wG1b8WpEPEkS4McB80n2xvuRhCvAK5Hc9gxgHvnf/qwvsDIi5gBExNsRUUPyE/pfSHoG+D3JpWUbchzwJUkLgNlA97SmI4HfR8SHEfEaSRjXLu+ViHg+7f4lyYdQrd/mPL8NOD9tTjmT5LrkZnnxT+ltW7Eu/Svguoi4NXegpEpyLjgFbAQabC5pgEiucVLfxcDrwCdJ9qLXNzH9uIj4c72aTmxi/Kasy3k+leTenDOAeRGxpplpzep4D9y2NX8GxkjaEUDS3pL2aGaad4Cdmhj+LLCXpMHpPHeS1AHYhWTP/EPgXKD2oGL9+f0Z+Kqkjun0n5DUDXgM+FzaFv5RkqaX2uVVStov7T4XeKShwiJifTr/W4D/bmY9zTbjPXDbpkTEdEn7A7MkAbwLnEOyx92YScDPJb0PHB4R79eb5z8lnQnclB7kfB84FvgZMFXSGSTNH7V7xguBGkl/Tef9U5LmmqeVFLUKOJVk7/kYkhtCPE/SvLI2ItZLOh/4ffpBMQf4eRP13wl8Fpje5MYxq8e/xDQrgKQdI+JdSd2Bp4ChaXt4S+bxLWCXiBi/VYq07Zb3wM0Kc5+kj5Cc6fL9VoT3PSQX1Bq+FWqz7Zz3wG27kgZi73q9L6t/ANJse+AANzPLKJ+FYmaWUQ5wM7OMcoCbmWWUA9zMLKMc4GZmGeUANzPLqP8DFCyTb1SqOgMAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rent_and_gender = pd.crosstab(naira_complete_rent['rent_category'], naira_complete_rent['Gender'])\n", + "rent_and_gender.plot(kind='bar')\n", + "plt.title('Rent_Percent_Category vs Gender')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 229, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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qMTOzD2k3qCPieWBUN9RiZmat8OF5ZmYZ56A2M8s4B7WZWcY5qM3MMs5BbWZWokLTnJ5++unsuOOO5HI59t57b1566aWytOdpTs2s6tVPqS/r9hZ8a0GbywtNc3ryySdz9tlnA/CrX/2Ks846iyuuuKLT9bhHbWZWokLTnOZPzPTWW291+1wfZmbWipbTnP7kJz/h2muvpX///txzzz1lacM9ajOzDmptmtNzzjmHxsZGjjjiCP77v/+7LO04qM3MOqDQNKfNvvGNbzBjxoyytOWgNjMrUaFpTv/3f/937fWZM2cybNiwsrTnMWozsxI1T3NaX19PLpcD4Nxzz+Xqq69m8eLF9OrVi2222aYsR3yAg9rM1gPtHU5Xbt09zamHPszMMs5BbWaWcQ5qM7OMc1CbmWWcg9rMLOMc1GZmGeegNjMrUaFpTptdeOGFSOK1114rS3s+jtrMqt6iYcPLur3hzyxqc3mhaU532GEHGhsbueuuuxgyZEjZ6nGP2sysRIWmOQX44Q9/yH/913+VbYpTcFCbmXVK/jSnM2fOZOutt2bUqFFlbcNDH2ZmHZQ/zWlNTQ3nnHMOd955Z9nbcY/azKwDWk5z+txzz/HCCy8watQo6urqaGpqYvTo0SxdurTTbblHbWZWotamOa2vr+fVV19du05dXR1z585lwIABnW6v6B61pA0kPSHp1k63amZWxZqnOW1oaCCXy5HL5Zg1a1aXtVdKj3oisAjo196KZmbdqb3D6cqt0DSn+ZYsWVK29orqUUuqBb4MXFW2ls3MrCjF9qgvBk4B+hZaQdIEYAJQ1gO9q8kvDtu/4LKTbvCIkZl1TLs9akn7A69GxLy21ouISRExJiLGDBw4sGwFmpn1dMUMfXwG+IqkJcA0YC9J13dpVWZmtla7QR0R/xYRtRFRB3wdaIiIb3Z5ZWZmBvgHL2ZmmVdSUEfE7IgovMfMzKwHaGua01//+tdsv/32jBgxglNOOaUs7fmXiWZW9S49oaGs2/vXK/Zqc3mhaU5feeUV/vCHP/DUU0+x0UYbrfNLxc5wUJuZlWjQoEEMGjQIWHea0yuvvJLTTjuNjTbaCIAtttiiLO15jNrMrBPypzl99tlnmTNnDrvssgt77LEHjz32WFnacI/azKyD8qc57devH6tXr+Yf//gHDz/8MI899hiHHnoozz//fKdPIuAetZlZB7Sc5hSgtraWgw8+GEmMHTuWXr16leW8iQ5qM7MStTbNKcCBBx5IQ0OyY/PZZ5/l3XffLcs0px76MDMrUfM0p/X19eRyOQDOPfdcjj32WI499lhGjhxJ7969mTJlSlnOneigNrOq197hdOXW1jSn119f/hk2PPRhZpZxDmozs4xzUJuZZZyD2sws4xzUZmYZ56A2M8s4B7WZWYkKTXN62GGHkcvlyOVy1NXVrT3GurN8HLWZVb22TizdEe2djLrQNKc33HDDB9s46ST69+9flnoc1GZmJSo0zekOO+wAJD8xv/HGG9f+nLyzPPRhZtYJ+dOcNpszZw5bbrkl2267bVnacFCbmXVQy2lOm02dOpXDDz+8bO146MPMrANam+YUYPXq1dx8883MmzevbG25R21mVqJC05wC3H333QwbNoza2tqyteegNjMrUfM0pw0NDWsPx5s1axYA06ZNK+uwB3jow8zWA+0dTldubU1zes0115S9PfeozcwyzkFtZpZx7Qa1pD6SHpX0pKSnJf1ndxRmZmaJYsao3wH2iohVkjYE7pf0p4h4uItrMzMzigjqSEbMV6U3N0wvrY+im5lZ2RU1Ri1pA0nzgVeBuyLikS6tyszM1irq8LyIeB/ISdoMuEXSyIhYmL+OpAnABIAhQ4aUu85utWjY8ILLhj+zqBsrMbMsamxs5KijjmLp0qX06tWLCRMmMHHiRObPn88JJ5zA22+/TU1NDZdddhljx47tdHslHUcdESskzQb2BRa2WDYJmAQwZswYD42YWbdpOm1OWbdX+/PPtrm80DSnp5xyCmeccQZf+tKXmDVrFqeccgqzZ8/udD3FHPUxMO1JI2lj4IvAM51u2cysSg0aNIjRo0cD605zKok333wTgDfeeIPBgweXpb1ietSDgCmSNiAJ9hsjont/BmRmllH505xefPHF7LPPPvz4xz9mzZo1PPjgg2Vpo90edUQ8FRGfjogdI2JkRJxVlpbNzKpcy2lOL7/8ci666CIaGxu56KKLOO6448rSjn+ZaGbWAa1NczplypS11w855BAeffTRsrTloDYzK1GhaU4HDx7MvffeC0BDQ0PZzvDi2fPMzErUPM1pfX392jONn3vuuVx55ZVMnDiR1atX06dPHyZNmlSW9hzUZlb12jucrtzamua0nGd2aeahDzOzjHNQm5llnIPazCzjHNRmZhnnoDYzyzgHtZlZxjmozcxK1NjYyJ577snw4cMZMWIEl1xyCQBPPvkku+22G/X19RxwwAFrJ2jqLB9HbWZV78wzz+zW7RWa5vTb3/42F154IXvssQeTJ0/mggsu4Oyzz+50Pe5Rm5mVqNA0p4sXL+Zzn/scAOPGjWPGjBllac9BbWbWCfnTnI4cOZKZM2cCcNNNN9HY2FiWNhzUZmYd1HKa08mTJ3PppZey0047sXLlSnr37l2WdjxGbWbWAa1Nczps2DDuvPNOAJ599lluu+22srTlHrWZWYkKTXP66quvArBmzRp+9rOfccIJJ5SlPQe1mVmJmqc5bWhoIJfLkcvlmDVrFlOnTmW77bZj2LBhDB48mGOOOaYs7Xnow8yqXrkPz2tPW9OcTpw4seztuUdtZpZxDmozs4xzUJuZZZyD2syqUqEx4qzrSN0OajOrOn369GH58uVVF9YRwfLly+nTp09Jj/NRH2ZWdWpra2lqamLZsmWVLqVkffr0oba2tqTHOKjNrOpsuOGGDB06tNJldJt2hz4kfVzSPZIWSXpaUvkPEjQzs4KK6VGvBk6KiMcl9QXmSborIv7SxbWZmRlF9Kgj4uWIeDy9vhJYBGzd1YWZmVmipDFqSXXAp4FHWlk2AZgAMGTIkHLU1qXqp9QXXHZjN9ZhHdPW+7fgWwu6sRKzrlf04XmSNgVmAD+IiA+dCCwiJkXEmIgYM3DgwHLWaGbWoxUV1JI2JAnp30XEzV1bkpmZ5SvmqA8BVwOLIuKXXV+SmZnlK6ZH/RngSGAvSfPTy35dXJeZmaXa3ZkYEfcD6oZazMysFZ7rw8ws4xzUZmYZ56A2M8s4B7WZWcY5qM3MMs5BbWaWcQ5qM7OMc1CbmWWcg9rMLOMc1GZmGeegNjPLOAe1mVnGOajNzDLOQW1mlnEOajOzjHNQm5llnIPazCzjHNRmZhnnoDYzyzgHtZlZxjmozcwyzkFtZpZxDmozs4xzUJuZZZyD2sws49oNakmTJb0qaWF3FGRmZusqpkd9DbBvF9dhZmYFtBvUEXEf8Ho31GJmZq3wGLWZWcbVlGtDkiYAEwCGDBlSrs22q+602wouW9LnG4UfOLT7agRoOm1O4YV9uq+OqnJm/8LLOvj+XXpCQ8Fl/3rFXh3a5plnntmhZda6RcOGF1w2/JlF3VhJdpStRx0RkyJiTESMGThwYLk2a2bW43now8ws44o5PG8q8BCwvaQmScd1fVlmZtas3THqiDi8OwoxM7PWeejDzCzjHNRmZhnnoDYzyzgHtZlZxjmozcwyzkFtZpZxDmozs4xzUJuZZZyD2sws4xzUZmYZ56A2M8s4B7WZWcY5qM3MMs5BbWaWcQ5qM7OMc1CbmWWcg9rMLOMc1GZmGeegNjPLOAe1mVnGOajNzDLOQW1mlnEOajOzjHNQm5llnIPazCzjHNRmZhlXVFBL2lfSYkl/lXRaVxdlZmYfaDeoJW0AXAp8CdgBOFzSDl1dmJmZJYrpUY8F/hoRz0fEu8A04KtdW5aZmTVTRLS9gvQ1YN+I+HZ6+0hgl4j4Xov1JgAT0pvbA4vLX24mDABeq3QR1mF+/6rb+vz+bRMRA1tbUFPEg9XKfR9K94iYBEwqsbCqI2luRIypdB3WMX7/qltPff+KGfpoAj6ed7sWeKlryjEzs5aKCerHgG0lDZXUG/g6MLNryzIzs2btDn1ExGpJ3wPuADYAJkfE011eWXat98M76zm/f9WtR75/7e5MNDOzyvIvE83MMs5BbWaWcQ5qM7OMc1CbmWVcMT946fEknQXMAR6MiLcqXY+VTtJHSX4PsPYzHxGPV64iK1Y639CWrPve/a1yFXU/H/VRBEnHArsDuwErSUL7voj4Q0ULs6JIOhs4GniOD35VGxGxV8WKsqJIOhE4A3gFWJPeHRGxY+Wq6n4O6hJI2go4FPgx8NGI6FvhkqwIkhYD9emkYlZFJP2VZG6h5ZWupZI8Rl0ESVdJehC4nOTr19eAj1a2KivBQmCzShdhHdIIvFHpIirNY9TF2ZzkV5krgNeB1yJidUUrslKcBzwhaSHwTvOdEfGVypVkbZH0o/Tq88BsSbex7nv3y4oUViEO6iJExEEAkoYD+wD3SNogImorW5kVaQpwPrCAD8Y5LduahxX/ll56p5ceyWPURZC0P/BZ4HMkQx4PAXMiYnJFC7OiSLo3IvaodB1mHeWgLoKkS4H7SMLZU7xWGUm/JPnaPJN1vz778LyMk/RHPjz//RvAXOA3EfF291fV/RzURZK0JbBzevPRiHi1kvVY8STd08rdPjyvCki6BBgITE3vOgxYCmwM9IuIIytVW3dyUBdB0iHAhcBskjPefBY4OSKmV7Ius/WdpPsi4nOt3Sfp6YgYUanaupN3Jhbnp8DOzb1oSQOBuwEHdRWQ9B+t3R8RZ3V3LVaygZKGNP8SUdIQkvMmAvSY4+Id1MXp1WKoYzk+Br2a5P/svw+wP7CoQrVYaU4C7pf0HMm32aHAdyV9hORonh7BQx9FkHQBsCPrjpM9FRGnVq4q6yhJGwEzI2KfStdi7Uvfr2EkQf1MT9mBmM9BXSRJ44HPkHxY7ouIWypcknVQOkHToxGxbaVrsdZJ2isiGiQd3NryiLi5u2uqJA99FCkiZgAzKl2HlU7SAj44xGsDkqMIPD6dbXsADcAB6e3m90/p9R4V1O5Rt0HSSj58DCekH5aI6NfNJVkHSNom7+Zq4BVPAVAdJPUBxgN1fNCxjJ62I9g96jZ4drzqJqlfRLxJMjVtvn6SiIjXK1GXleT3JHPsPA40j033uN6le9S23pJ0a0TsL+kFkv/cylscEfGJCpVmRZK0MCJGVrqOSnNQm1lmSZoE/DoiFlS6lkpyUNt6S9LotpZ7ro/sytsBXANsSzLd6Tt8sH/IZ3gxWx/kzfHRBxgDPEnyH31H4JGI2L1StVnbWuwA/pCIeLG7askC70y09VZE7AkgaRowofnrs6SRJKdTs4zqaUHcHv8M2nqCYfljnBGxEMhVrhyz0rhHbT3BIklXAdeTjHt+E8/1YVXEY9S23kt/NPEdkjP0QHISiMt74pwRVp0c1NYjSNoYGBIRiytdi1mpPEZt6z1JXwHmA7ent3OSZla0KLMSOKitJzgDGEvyU2QiYj7J3BFmVcFBbT3B6oh4o9JFmHWUj/qwnmChpG8AG0jaFvg+8GCFazIrmnvU1hOcCIwg+Qny/wBvABMrWpFZCRzU1hPskF5qSH5O/lXgsYpWZFYCH55n6z1Ji0l+Mr4QWNN8v3+mbNXCY9TWEyyLiD9WugizjnKP2tZ7kr4AHA78mWScGuh5J0i16uUetfUExwDDgA35YOijx50g1aqXg9p6glERUV/pIsw6ykd9WE/wsKQdKl2EWUd5jNrWe5IWAZ8EXqAHn87JqpeD2tZ7hU7r5MPzrFo4qM3MMs5j1GZmGeegtqog6WhJg8u4vbp0oiazzHNQW7dTotTP3tFA2YKaZD7qLg9qSRt0dRu2/nNQW7dIe7CLJF0GPA6cLukxSU9J+s8W61wp6WlJd0raWNLXgDHA7yTNT0+r1VobO0t6UNKTkh6V1Dfd5hxJj6eXf0lX/znw2XR7P5S0gaQL8mo6Pt1mL0mXpfXcKmlWWg+SviDpCUkLJE2WtFF6/xJJ/yHpfuA0SY/n1bitpHld9DLb+ioifPGlyy8kPdg1wK7A3sAkksPkegG3kpx4tg5YDeTSx9wIfDO9PhsY08b2ewPPAzunt/uR/KBrE6BPet+2wNz0+ueBW/MePwH4aXp9I2AuMBT4GjArrXMr4B/pfX2ARmC79DHXAj9Iry8BTsnb9j15z+lc4MRKvx++VNfFPWrrTi9GxMMkQb038ARJ73oYSYgCvBDJqbIA5lH8KbO2B16OiMcAIuLNiFhN8rPxKyUtAG4ime60NXsDR0maDzwCbJ7WtDtwU0SsiYilJKHb3N4LEfFsensKH5zlHOCGvOtXAcekwyCHkcyJbVY0/4TcutNb6b8CzouI3+QvlFRH3qRJwPtAq8McrRDJ/B0t/RB4BRhF0it+u43HnxgRd7So6cttrN+Wt/KuzyA5b2MDMC8ilrfzWLN1uEdtlXAHcKykTQEkbS1pi3YesxLo28byZ4DBknZOt9lXUg3Qn6SnvQY4Emjeuddye3cA35G0Yfr47SR9BLgfGJ+OVW9JMmTS3F6dpE+lt48E7m2tsIh4O93+5cBv23meZh/iHrV1u4i4U9Jw4CFJAKuAb5L0oAu5BrhC0j+B3SLiny22+a6kw4Bfpzsb/wl8EbgMmCHpEJJhi+ae7lPAaklPptu+hGSY5XElRS0DDiTpDX+B5KQDz5IMi7wREW9LOga4Kf2D8BhwRRv1/w44GLizzRfHrBX+ZaJZOyRtGhGrJG0OPAp8Jh2vLmUbPwb6R8TpXVKkrdfcozZr362SNiM5suTsDoT0LSSTQu3VBbVZD+AetVWdNPiGtrj71JY7As3WFw5qM7OM81EfZmYZ56A2M8s4B7WZWcY5qM3MMs5BbWaWcQ5qM7OM+/+M6XVjpcTJYwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rent_and_age = pd.crosstab(naira_complete_rent['rent_category'], naira_complete_rent['Age'])\n", + "rent_and_age.plot(kind='bar')\n", + "plt.title('Rent_Percent_Category vs Age')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 230, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rent_and_education = pd.crosstab(naira_complete_rent['rent_category'], naira_complete_rent['Maximum Level of Education'])\n", + "rent_and_education.plot(kind='bar')\n", + "plt.title('Rent_Percent_Category vs Level of Education')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Conclusion" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This analysis focused mostly on young adults who completely pay their rents and earn in Naira. \n", + "\n", + "75% of people in this category spend about 25% of their monthly earnings on acoommodation. \n", + "\n", + "Most of these accommodations are located in Mid-Class Areas.\n", + "\n", + "Self-contained type houses are the also the most common.\n", + "\n", + "Most of the people in this category fall between the ages of 23-29, with Bachelor's Degree/Equivalent education levels.\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}