{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Nigerian Presidential Election Result Analysis - 2015\n",
"\n",
"Author: Umar Yusuf
\n",
"Blog post: http://umar-yusuf.blogspot.com.ng/2016/09/Analysis-of-Nigerian-Presidential-Election-Result-2015-using-Python-Programming-Language.html\n",
"\n",
"### Data Source\n",
"The data was gathered from the Independent National Electoral Commission (INEC) official website.\n",
"\n",
"The Data (in .csv format) used is available for download here. Download it and save it at thesame location with this notebook.\n",
"\n",
"Am going to use these three main python programming packages pandas with matplotlib embedded to analyse the 2015 Presidential Election Result."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Introduction\n",
"Nigeria has 36 states and 1 federal capital territory. The 2015 presidential election was held in the 37 territories within the country.\n",
"\n",
"Fourteen (14) political parties representing fourteen (14) candidates participated in the 2015 presidential elections. The parties are as follow: AA, ACPN, AD, ADC, APA, APC, CPP, HOPE, KOWA, NCP, PDP, PPN, UDP and UPP. See the result table below:-\n",
"\n",
"\n",
"\n",
"Even though the battle was between the two biggest parties (APC and PDP). The dataset we will explore will contain all the parties.\n",
"\n",
"The dataset contains the numeric values by states for:-
\n",
"1~ Vote scored by each political party
\n",
"2~ Number_of_Registered_Voters
\n",
"3~ Number_of_Accredited_Voters
\n",
"4~ Number_of_Valid_Votes
\n",
"5~ Number_of_Rejected_Votes
\n",
"6~ Total_Votes_Cast
\n",
"7~ Population
\n",
"8~ Population_Rank
\n",
"9~ Number_of_LGA
\n",
"\n",
"#### I will attempt to answer the following questions through this analysis:-\n",
"a) What are the minimum and maximum votes for each party?
\n",
"b) Is winning in top states with highest numbers of voters’ turnout, registered voters, total votes cast, and population related to winning the general election?
\n",
"c) Is there any odd case where \"Population\" of a state is lower than \"Number_of_Registered_Voters\" and \"Number_of_Accredited_Voters\"?
\n",
"d) Which state voted most for the lowest rank party?
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Import libraries and load in the dataset"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Lets import the packages\n",
"import pandas as pd\n",
"\n",
"# Lets enable our plot to display inline within notebook\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"
\n",
" \n",
" \n",
" | \n",
" State | \n",
" Capital | \n",
" Code | \n",
" Number_of_Reg_Voters | \n",
" Number_of_Accr_Voters | \n",
" AA | \n",
" ACPN | \n",
" AD | \n",
" ADC | \n",
" APA | \n",
" ... | \n",
" UDP | \n",
" UPP | \n",
" Number_of_Valid_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Total_Votes_Cast | \n",
" Population | \n",
" Population_Rank | \n",
" Number_of_LGA | \n",
" Latitude | \n",
" Longitude | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Abia | \n",
" Umuahia | \n",
" AB | \n",
" 1349134 | \n",
" 442538 | \n",
" 315 | \n",
" 2194 | \n",
" 448 | \n",
" 569 | \n",
" 2766 | \n",
" ... | \n",
" 213 | \n",
" 330 | \n",
" 391045 | \n",
" 10004 | \n",
" 401049 | \n",
" 2833999 | \n",
" 28 | \n",
" 17 | \n",
" 5.614284 | \n",
" 7.552007 | \n",
"
\n",
" \n",
" 1 | \n",
" Adamawa | \n",
" Yola | \n",
" AD | \n",
" 1518123 | \n",
" 709993 | \n",
" 495 | \n",
" 1166 | \n",
" 595 | \n",
" 1012 | \n",
" 1549 | \n",
" ... | \n",
" 289 | \n",
" 334 | \n",
" 636018 | \n",
" 25192 | \n",
" 661210 | \n",
" 3168101 | \n",
" 26 | \n",
" 21 | \n",
" 9.562175 | \n",
" 12.562022 | \n",
"
\n",
" \n",
" 2 | \n",
" Akwa Ibom | \n",
" Uyo | \n",
" AK | \n",
" 1644481 | \n",
" 1074070 | \n",
" 1600 | \n",
" 443 | \n",
" 474 | \n",
" 608 | \n",
" 384 | \n",
" ... | \n",
" 224 | \n",
" 144 | \n",
" 1017064 | \n",
" 11487 | \n",
" 1028551 | \n",
" 3920208 | \n",
" 15 | \n",
" 31 | \n",
" 4.832722 | \n",
" 7.812528 | \n",
"
\n",
" \n",
" 3 | \n",
" Anambra | \n",
" Awka | \n",
" AN | \n",
" 1963427 | \n",
" 774430 | \n",
" 547 | \n",
" 1259 | \n",
" 475 | \n",
" 534 | \n",
" 2303 | \n",
" ... | \n",
" 286 | \n",
" 1121 | \n",
" 688584 | \n",
" 14825 | \n",
" 703409 | \n",
" 4182032 | \n",
" 10 | \n",
" 21 | \n",
" 6.235526 | \n",
" 6.970846 | \n",
"
\n",
" \n",
" 4 | \n",
" Bauchi | \n",
" Bauchi | \n",
" BA | \n",
" 2053484 | \n",
" 1094069 | \n",
" 131 | \n",
" 232 | \n",
" 173 | \n",
" 189 | \n",
" 964 | \n",
" ... | \n",
" 29 | \n",
" 37 | \n",
" 1020338 | \n",
" 19437 | \n",
" 1039775 | \n",
" 4676465 | \n",
" 7 | \n",
" 20 | \n",
" 10.544138 | \n",
" 9.576053 | \n",
"
\n",
" \n",
"
\n",
"
5 rows × 27 columns
\n",
"
"
],
"text/plain": [
" State Capital Code Number_of_Reg_Voters Number_of_Accr_Voters AA \\\n",
"0 Abia Umuahia AB 1349134 442538 315 \n",
"1 Adamawa Yola AD 1518123 709993 495 \n",
"2 Akwa Ibom Uyo AK 1644481 1074070 1600 \n",
"3 Anambra Awka AN 1963427 774430 547 \n",
"4 Bauchi Bauchi BA 2053484 1094069 131 \n",
"\n",
" ACPN AD ADC APA ... UDP UPP Number_of_Valid_Votes \\\n",
"0 2194 448 569 2766 ... 213 330 391045 \n",
"1 1166 595 1012 1549 ... 289 334 636018 \n",
"2 443 474 608 384 ... 224 144 1017064 \n",
"3 1259 475 534 2303 ... 286 1121 688584 \n",
"4 232 173 189 964 ... 29 37 1020338 \n",
"\n",
" Number_of_Rejected_Votes Total_Votes_Cast Population Population_Rank \\\n",
"0 10004 401049 2833999 28 \n",
"1 25192 661210 3168101 26 \n",
"2 11487 1028551 3920208 15 \n",
"3 14825 703409 4182032 10 \n",
"4 19437 1039775 4676465 7 \n",
"\n",
" Number_of_LGA Latitude Longitude \n",
"0 17 5.614284 7.552007 \n",
"1 21 9.562175 12.562022 \n",
"2 31 4.832722 7.812528 \n",
"3 21 6.235526 6.970846 \n",
"4 20 10.544138 9.576053 \n",
"\n",
"[5 rows x 27 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inec_table = pd.read_csv(\"INEC 2015 Presidential Election Results.csv\")\n",
"inec_table.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Statistical summary of all the columns\n",
"\n",
"This will show us the minimum and maximum votes for each party."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"\n",
"
\n",
" \n",
" \n",
" | \n",
" Number_of_Reg_Voters | \n",
" Number_of_Accr_Voters | \n",
" AA | \n",
" ACPN | \n",
" AD | \n",
" ADC | \n",
" APA | \n",
" APC | \n",
" CPP | \n",
" HOPE | \n",
" ... | \n",
" UDP | \n",
" UPP | \n",
" Number_of_Valid_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Total_Votes_Cast | \n",
" Population | \n",
" Population_Rank | \n",
" Number_of_LGA | \n",
" Latitude | \n",
" Longitude | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 3.700000e+01 | \n",
" 3.700000e+01 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 3.700000e+01 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" ... | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 3.700000e+01 | \n",
" 37.000000 | \n",
" 3.700000e+01 | \n",
" 3.700000e+01 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
"
\n",
" \n",
" mean | \n",
" 1.822218e+06 | \n",
" 8.580132e+05 | \n",
" 597.972973 | \n",
" 1089.486486 | \n",
" 829.000000 | \n",
" 801.783784 | \n",
" 1446.945946 | \n",
" 4.168895e+05 | \n",
" 981.081081 | \n",
" 200.945946 | \n",
" ... | \n",
" 248.864865 | \n",
" 492.432432 | \n",
" 7.726369e+05 | \n",
" 22824.837838 | \n",
" 7.954617e+05 | \n",
" 3.783880e+06 | \n",
" 19.000000 | \n",
" 20.918919 | \n",
" 8.573171 | \n",
" 7.335358 | \n",
"
\n",
" \n",
" std | \n",
" 1.026219e+06 | \n",
" 4.641212e+05 | \n",
" 1058.202944 | \n",
" 1537.150658 | \n",
" 1193.011688 | \n",
" 893.409143 | \n",
" 994.589389 | \n",
" 4.137989e+05 | \n",
" 1098.046583 | \n",
" 208.625388 | \n",
" ... | \n",
" 307.701800 | \n",
" 1008.016026 | \n",
" 4.245404e+05 | \n",
" 11468.557038 | \n",
" 4.310620e+05 | \n",
" 1.713420e+06 | \n",
" 10.824355 | \n",
" 7.488430 | \n",
" 2.623850 | \n",
" 2.427991 | \n",
"
\n",
" \n",
" min | \n",
" 6.056370e+05 | \n",
" 3.237390e+05 | \n",
" 40.000000 | \n",
" 38.000000 | \n",
" 69.000000 | \n",
" 105.000000 | \n",
" 70.000000 | \n",
" 5.194000e+03 | \n",
" 44.000000 | \n",
" 4.000000 | \n",
" ... | \n",
" 20.000000 | \n",
" 29.000000 | \n",
" 3.006910e+05 | \n",
" 4672.000000 | \n",
" 3.094450e+05 | \n",
" 1.405201e+06 | \n",
" 1.000000 | \n",
" 6.000000 | \n",
" 4.832722 | \n",
" 3.263435 | \n",
"
\n",
" \n",
" 25% | \n",
" 1.349134e+06 | \n",
" 5.201270e+05 | \n",
" 159.000000 | \n",
" 391.000000 | \n",
" 279.000000 | \n",
" 375.000000 | \n",
" 674.000000 | \n",
" 1.203310e+05 | \n",
" 381.000000 | \n",
" 83.000000 | \n",
" ... | \n",
" 79.000000 | \n",
" 72.000000 | \n",
" 4.737960e+05 | \n",
" 14825.000000 | \n",
" 4.917670e+05 | \n",
" 2.833999e+06 | \n",
" 10.000000 | \n",
" 17.000000 | \n",
" 6.455966 | \n",
" 5.928762 | \n",
"
\n",
" \n",
" 50% | \n",
" 1.644481e+06 | \n",
" 7.099930e+05 | \n",
" 315.000000 | \n",
" 538.000000 | \n",
" 474.000000 | \n",
" 539.000000 | \n",
" 1165.000000 | \n",
" 3.082900e+05 | \n",
" 819.000000 | \n",
" 144.000000 | \n",
" ... | \n",
" 184.000000 | \n",
" 156.000000 | \n",
" 6.426150e+05 | \n",
" 19867.000000 | \n",
" 6.633730e+05 | \n",
" 3.423535e+06 | \n",
" 19.000000 | \n",
" 20.000000 | \n",
" 8.219491 | \n",
" 7.091086 | \n",
"
\n",
" \n",
" 75% | \n",
" 1.977211e+06 | \n",
" 1.074070e+06 | \n",
" 533.000000 | \n",
" 1214.000000 | \n",
" 735.000000 | \n",
" 888.000000 | \n",
" 2177.000000 | \n",
" 5.678830e+05 | \n",
" 1046.000000 | \n",
" 255.000000 | \n",
" ... | \n",
" 286.000000 | \n",
" 290.000000 | \n",
" 9.823880e+05 | \n",
" 29449.000000 | \n",
" 1.000692e+06 | \n",
" 4.182032e+06 | \n",
" 28.000000 | \n",
" 25.000000 | \n",
" 10.564178 | \n",
" 8.513930 | \n",
"
\n",
" \n",
" max | \n",
" 5.827846e+06 | \n",
" 2.364434e+06 | \n",
" 6331.000000 | \n",
" 8979.000000 | \n",
" 6282.000000 | \n",
" 5000.000000 | \n",
" 4468.000000 | \n",
" 1.903999e+06 | \n",
" 6674.000000 | \n",
" 989.000000 | \n",
" ... | \n",
" 1623.000000 | \n",
" 4859.000000 | \n",
" 2.128821e+06 | \n",
" 52289.000000 | \n",
" 2.172447e+06 | \n",
" 9.383682e+06 | \n",
" 37.000000 | \n",
" 44.000000 | \n",
" 13.109266 | \n",
" 12.722342 | \n",
"
\n",
" \n",
"
\n",
"
8 rows × 24 columns
\n",
"
"
],
"text/plain": [
" Number_of_Reg_Voters Number_of_Accr_Voters AA ACPN \\\n",
"count 3.700000e+01 3.700000e+01 37.000000 37.000000 \n",
"mean 1.822218e+06 8.580132e+05 597.972973 1089.486486 \n",
"std 1.026219e+06 4.641212e+05 1058.202944 1537.150658 \n",
"min 6.056370e+05 3.237390e+05 40.000000 38.000000 \n",
"25% 1.349134e+06 5.201270e+05 159.000000 391.000000 \n",
"50% 1.644481e+06 7.099930e+05 315.000000 538.000000 \n",
"75% 1.977211e+06 1.074070e+06 533.000000 1214.000000 \n",
"max 5.827846e+06 2.364434e+06 6331.000000 8979.000000 \n",
"\n",
" AD ADC APA APC CPP \\\n",
"count 37.000000 37.000000 37.000000 3.700000e+01 37.000000 \n",
"mean 829.000000 801.783784 1446.945946 4.168895e+05 981.081081 \n",
"std 1193.011688 893.409143 994.589389 4.137989e+05 1098.046583 \n",
"min 69.000000 105.000000 70.000000 5.194000e+03 44.000000 \n",
"25% 279.000000 375.000000 674.000000 1.203310e+05 381.000000 \n",
"50% 474.000000 539.000000 1165.000000 3.082900e+05 819.000000 \n",
"75% 735.000000 888.000000 2177.000000 5.678830e+05 1046.000000 \n",
"max 6282.000000 5000.000000 4468.000000 1.903999e+06 6674.000000 \n",
"\n",
" HOPE ... UDP UPP Number_of_Valid_Votes \\\n",
"count 37.000000 ... 37.000000 37.000000 3.700000e+01 \n",
"mean 200.945946 ... 248.864865 492.432432 7.726369e+05 \n",
"std 208.625388 ... 307.701800 1008.016026 4.245404e+05 \n",
"min 4.000000 ... 20.000000 29.000000 3.006910e+05 \n",
"25% 83.000000 ... 79.000000 72.000000 4.737960e+05 \n",
"50% 144.000000 ... 184.000000 156.000000 6.426150e+05 \n",
"75% 255.000000 ... 286.000000 290.000000 9.823880e+05 \n",
"max 989.000000 ... 1623.000000 4859.000000 2.128821e+06 \n",
"\n",
" Number_of_Rejected_Votes Total_Votes_Cast Population \\\n",
"count 37.000000 3.700000e+01 3.700000e+01 \n",
"mean 22824.837838 7.954617e+05 3.783880e+06 \n",
"std 11468.557038 4.310620e+05 1.713420e+06 \n",
"min 4672.000000 3.094450e+05 1.405201e+06 \n",
"25% 14825.000000 4.917670e+05 2.833999e+06 \n",
"50% 19867.000000 6.633730e+05 3.423535e+06 \n",
"75% 29449.000000 1.000692e+06 4.182032e+06 \n",
"max 52289.000000 2.172447e+06 9.383682e+06 \n",
"\n",
" Population_Rank Number_of_LGA Latitude Longitude \n",
"count 37.000000 37.000000 37.000000 37.000000 \n",
"mean 19.000000 20.918919 8.573171 7.335358 \n",
"std 10.824355 7.488430 2.623850 2.427991 \n",
"min 1.000000 6.000000 4.832722 3.263435 \n",
"25% 10.000000 17.000000 6.455966 5.928762 \n",
"50% 19.000000 20.000000 8.219491 7.091086 \n",
"75% 28.000000 25.000000 10.564178 8.513930 \n",
"max 37.000000 44.000000 13.109266 12.722342 \n",
"\n",
"[8 rows x 24 columns]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inec_table.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Turnout of Voters for the election\n",
"We can see the ratio of voters turnout for the election by dividing \"Number_of_Reg_Voters\" by \"Total_Votes_Cast\" for each state"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" State | \n",
" Voters Turnout | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Abia | \n",
" 0.297264 | \n",
"
\n",
" \n",
" 1 | \n",
" Adamawa | \n",
" 0.435544 | \n",
"
\n",
" \n",
" 2 | \n",
" Akwa Ibom | \n",
" 0.625456 | \n",
"
\n",
" \n",
" 3 | \n",
" Anambra | \n",
" 0.358256 | \n",
"
\n",
" \n",
" 4 | \n",
" Bauchi | \n",
" 0.506347 | \n",
"
\n",
" \n",
" 5 | \n",
" Bayelsa | \n",
" 0.613798 | \n",
"
\n",
" \n",
" 6 | \n",
" Benue | \n",
" 0.371320 | \n",
"
\n",
" \n",
" 7 | \n",
" Borno | \n",
" 0.286168 | \n",
"
\n",
" \n",
" 8 | \n",
" Cross River | \n",
" 0.407158 | \n",
"
\n",
" \n",
" 9 | \n",
" Delta | \n",
" 0.628481 | \n",
"
\n",
" \n",
" 10 | \n",
" Ebonyi | \n",
" 0.367184 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" State Voters Turnout\n",
"0 Abia 0.297264\n",
"1 Adamawa 0.435544\n",
"2 Akwa Ibom 0.625456\n",
"3 Anambra 0.358256\n",
"4 Bauchi 0.506347\n",
"5 Bayelsa 0.613798\n",
"6 Benue 0.371320\n",
"7 Borno 0.286168\n",
"8 Cross River 0.407158\n",
"9 Delta 0.628481\n",
"10 Ebonyi 0.367184"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inec_table[\"Voters Turnout\"] = inec_table[\"Total_Votes_Cast\"] / inec_table[\"Number_of_Reg_Voters\"]\n",
"\n",
"inec_table[[\"State\", \"Voters Turnout\"]][:11]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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3sfBjsx9+AN54Q3UU4UfX3kqy3rJlsgXltm1qzs9cI6cw18gpzDVyCnONnOKlXJs9G2ja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5AAAJ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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"inec_table.plot(x=\"State\", y='Voters Turnout', figsize=(20, 5), kind=\"line\", grid=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Five top states with the highest \"Number_of_Reg_Voters\""
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" State | \n",
" Capital | \n",
" Code | \n",
" Number_of_Reg_Voters | \n",
" Number_of_Accr_Voters | \n",
" AA | \n",
" ACPN | \n",
" AD | \n",
" ADC | \n",
" APA | \n",
" ... | \n",
" UPP | \n",
" Number_of_Valid_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Total_Votes_Cast | \n",
" Population | \n",
" Population_Rank | \n",
" Number_of_LGA | \n",
" Latitude | \n",
" Longitude | \n",
" Voters Turnout | \n",
"
\n",
" \n",
" \n",
" \n",
" 24 | \n",
" Lagos | \n",
" Ikeja | \n",
" LA | \n",
" 5827846 | \n",
" 1678754 | \n",
" 1795 | \n",
" 3038 | \n",
" 4453 | \n",
" 2072 | \n",
" 2177 | \n",
" ... | \n",
" 244 | \n",
" 1443686 | \n",
" 52289 | \n",
" 1495975 | \n",
" 9013534 | \n",
" 2 | \n",
" 20 | \n",
" 6.455966 | \n",
" 3.263435 | \n",
" 0.256694 | \n",
"
\n",
" \n",
" 19 | \n",
" Kano | \n",
" Kano | \n",
" KN | \n",
" 4943862 | \n",
" 2364434 | \n",
" 426 | \n",
" 778 | \n",
" 708 | \n",
" 657 | \n",
" 2770 | \n",
" ... | \n",
" 156 | \n",
" 2128821 | \n",
" 43626 | \n",
" 2172447 | \n",
" 9383682 | \n",
" 1 | \n",
" 44 | \n",
" 12.107263 | \n",
" 8.353610 | \n",
" 0.439423 | \n",
"
\n",
" \n",
" 18 | \n",
" Kaduna | \n",
" Kaduna | \n",
" KD | \n",
" 3361793 | \n",
" 1746031 | \n",
" 218 | \n",
" 424 | \n",
" 273 | \n",
" 546 | \n",
" 1611 | \n",
" ... | \n",
" 78 | \n",
" 1617482 | \n",
" 32719 | \n",
" 1650201 | \n",
" 6066562 | \n",
" 3 | \n",
" 23 | \n",
" 10.704459 | \n",
" 7.331567 | \n",
" 0.490869 | \n",
"
\n",
" \n",
" 20 | \n",
" Katsina | \n",
" Katsina | \n",
" KT | \n",
" 2842741 | \n",
" 1578646 | \n",
" 183 | \n",
" 402 | \n",
" 283 | \n",
" 498 | \n",
" 1671 | \n",
" ... | \n",
" 72 | \n",
" 1449426 | \n",
" 32288 | \n",
" 1481714 | \n",
" 5792578 | \n",
" 4 | \n",
" 34 | \n",
" 13.029105 | \n",
" 7.491887 | \n",
" 0.521227 | \n",
"
\n",
" \n",
" 30 | \n",
" Oyo | \n",
" Ibadan | \n",
" OY | \n",
" 2344448 | \n",
" 1073849 | \n",
" 6331 | \n",
" 8979 | \n",
" 6282 | \n",
" 5000 | \n",
" 4468 | \n",
" ... | \n",
" 3665 | \n",
" 881352 | \n",
" 47254 | \n",
" 928606 | \n",
" 5591589 | \n",
" 5 | \n",
" 33 | \n",
" 8.219491 | \n",
" 3.744396 | \n",
" 0.396087 | \n",
"
\n",
" \n",
"
\n",
"
5 rows × 28 columns
\n",
"
"
],
"text/plain": [
" State Capital Code Number_of_Reg_Voters Number_of_Accr_Voters AA \\\n",
"24 Lagos Ikeja LA 5827846 1678754 1795 \n",
"19 Kano Kano KN 4943862 2364434 426 \n",
"18 Kaduna Kaduna KD 3361793 1746031 218 \n",
"20 Katsina Katsina KT 2842741 1578646 183 \n",
"30 Oyo Ibadan OY 2344448 1073849 6331 \n",
"\n",
" ACPN AD ADC APA ... UPP Number_of_Valid_Votes \\\n",
"24 3038 4453 2072 2177 ... 244 1443686 \n",
"19 778 708 657 2770 ... 156 2128821 \n",
"18 424 273 546 1611 ... 78 1617482 \n",
"20 402 283 498 1671 ... 72 1449426 \n",
"30 8979 6282 5000 4468 ... 3665 881352 \n",
"\n",
" Number_of_Rejected_Votes Total_Votes_Cast Population Population_Rank \\\n",
"24 52289 1495975 9013534 2 \n",
"19 43626 2172447 9383682 1 \n",
"18 32719 1650201 6066562 3 \n",
"20 32288 1481714 5792578 4 \n",
"30 47254 928606 5591589 5 \n",
"\n",
" Number_of_LGA Latitude Longitude Voters Turnout \n",
"24 20 6.455966 3.263435 0.256694 \n",
"19 44 12.107263 8.353610 0.439423 \n",
"18 23 10.704459 7.331567 0.490869 \n",
"20 34 13.029105 7.491887 0.521227 \n",
"30 33 8.219491 3.744396 0.396087 \n",
"\n",
"[5 rows x 28 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inec_table.sort_values(\"Number_of_Reg_Voters\", ascending=False)[:5]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Which party got the highest vote among the top states with the highest \"Number_of_Reg_Voters\""
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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pLJy3kWOSpDfJlU0aKjYoltpJcghwJXA7cHRV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\n+sZikyRJkiRJkvrm/wDdxiS/6g6oUAAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"win1 = inec_table.sort_values(\"Number_of_Reg_Voters\", ascending=False)[:5]\n",
"\n",
"win1.plot(x=\"State\", y=['AA', 'ACPN', 'AD', 'ADC', 'APA', 'APC', 'CPP', 'HOPE', 'KOWA', 'NCP', 'PDP', 'PPN', 'UDP', 'UPP'], \n",
" figsize=(20, 5), kind=\"bar\", grid=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Five top states with the highest number of \"Total_Votes_Cast\""
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" State | \n",
" Capital | \n",
" Code | \n",
" Number_of_Reg_Voters | \n",
" Number_of_Accr_Voters | \n",
" AA | \n",
" ACPN | \n",
" AD | \n",
" ADC | \n",
" APA | \n",
" ... | \n",
" UPP | \n",
" Number_of_Valid_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Total_Votes_Cast | \n",
" Population | \n",
" Population_Rank | \n",
" Number_of_LGA | \n",
" Latitude | \n",
" Longitude | \n",
" Voters Turnout | \n",
"
\n",
" \n",
" \n",
" \n",
" 19 | \n",
" Kano | \n",
" Kano | \n",
" KN | \n",
" 4943862 | \n",
" 2364434 | \n",
" 426 | \n",
" 778 | \n",
" 708 | \n",
" 657 | \n",
" 2770 | \n",
" ... | \n",
" 156 | \n",
" 2128821 | \n",
" 43626 | \n",
" 2172447 | \n",
" 9383682 | \n",
" 1 | \n",
" 44 | \n",
" 12.107263 | \n",
" 8.353610 | \n",
" 0.439423 | \n",
"
\n",
" \n",
" 18 | \n",
" Kaduna | \n",
" Kaduna | \n",
" KD | \n",
" 3361793 | \n",
" 1746031 | \n",
" 218 | \n",
" 424 | \n",
" 273 | \n",
" 546 | \n",
" 1611 | \n",
" ... | \n",
" 78 | \n",
" 1617482 | \n",
" 32719 | \n",
" 1650201 | \n",
" 6066562 | \n",
" 3 | \n",
" 23 | \n",
" 10.704459 | \n",
" 7.331567 | \n",
" 0.490869 | \n",
"
\n",
" \n",
" 32 | \n",
" Rivers | \n",
" Port Harcourt | \n",
" RV | \n",
" 2324300 | \n",
" 1643409 | \n",
" 1066 | \n",
" 525 | \n",
" 1104 | \n",
" 1031 | \n",
" 513 | \n",
" ... | \n",
" 156 | \n",
" 1565461 | \n",
" 19307 | \n",
" 1584768 | \n",
" 5185400 | \n",
" 6 | \n",
" 23 | \n",
" 4.973002 | \n",
" 6.810525 | \n",
" 0.681826 | \n",
"
\n",
" \n",
" 24 | \n",
" Lagos | \n",
" Ikeja | \n",
" LA | \n",
" 5827846 | \n",
" 1678754 | \n",
" 1795 | \n",
" 3038 | \n",
" 4453 | \n",
" 2072 | \n",
" 2177 | \n",
" ... | \n",
" 244 | \n",
" 1443686 | \n",
" 52289 | \n",
" 1495975 | \n",
" 9013534 | \n",
" 2 | \n",
" 20 | \n",
" 6.455966 | \n",
" 3.263435 | \n",
" 0.256694 | \n",
"
\n",
" \n",
" 20 | \n",
" Katsina | \n",
" Katsina | \n",
" KT | \n",
" 2842741 | \n",
" 1578646 | \n",
" 183 | \n",
" 402 | \n",
" 283 | \n",
" 498 | \n",
" 1671 | \n",
" ... | \n",
" 72 | \n",
" 1449426 | \n",
" 32288 | \n",
" 1481714 | \n",
" 5792578 | \n",
" 4 | \n",
" 34 | \n",
" 13.029105 | \n",
" 7.491887 | \n",
" 0.521227 | \n",
"
\n",
" \n",
"
\n",
"
5 rows × 28 columns
\n",
"
"
],
"text/plain": [
" State Capital Code Number_of_Reg_Voters Number_of_Accr_Voters \\\n",
"19 Kano Kano KN 4943862 2364434 \n",
"18 Kaduna Kaduna KD 3361793 1746031 \n",
"32 Rivers Port Harcourt RV 2324300 1643409 \n",
"24 Lagos Ikeja LA 5827846 1678754 \n",
"20 Katsina Katsina KT 2842741 1578646 \n",
"\n",
" AA ACPN AD ADC APA ... UPP Number_of_Valid_Votes \\\n",
"19 426 778 708 657 2770 ... 156 2128821 \n",
"18 218 424 273 546 1611 ... 78 1617482 \n",
"32 1066 525 1104 1031 513 ... 156 1565461 \n",
"24 1795 3038 4453 2072 2177 ... 244 1443686 \n",
"20 183 402 283 498 1671 ... 72 1449426 \n",
"\n",
" Number_of_Rejected_Votes Total_Votes_Cast Population Population_Rank \\\n",
"19 43626 2172447 9383682 1 \n",
"18 32719 1650201 6066562 3 \n",
"32 19307 1584768 5185400 6 \n",
"24 52289 1495975 9013534 2 \n",
"20 32288 1481714 5792578 4 \n",
"\n",
" Number_of_LGA Latitude Longitude Voters Turnout \n",
"19 44 12.107263 8.353610 0.439423 \n",
"18 23 10.704459 7.331567 0.490869 \n",
"32 23 4.973002 6.810525 0.681826 \n",
"24 20 6.455966 3.263435 0.256694 \n",
"20 34 13.029105 7.491887 0.521227 \n",
"\n",
"[5 rows x 28 columns]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inec_table.sort_values(\"Total_Votes_Cast\", ascending=False)[:5]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Which party got the highest vote among the top states with the highest \"Total_Votes_Cast\""
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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AMUOxKYLf75MxJm4vv9/XonGkpKTos88+a9A2ffp03XHH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\nkvX16WlgFIgAAAAASUVORK5CYII=\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"win2 = inec_table.sort_values(\"Total_Votes_Cast\", ascending=False)[:5]\n",
"\n",
"win2.plot(x=\"State\", y=['AA', 'ACPN', 'AD', 'ADC', 'APA', 'APC', 'CPP', 'HOPE', 'KOWA', 'NCP', 'PDP', 'PPN', 'UDP', 'UPP'], \n",
" figsize=(20, 5), kind=\"bar\", grid=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Five top states with the highest \"Population\""
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" State | \n",
" Capital | \n",
" Code | \n",
" Number_of_Reg_Voters | \n",
" Number_of_Accr_Voters | \n",
" AA | \n",
" ACPN | \n",
" AD | \n",
" ADC | \n",
" APA | \n",
" ... | \n",
" UPP | \n",
" Number_of_Valid_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Total_Votes_Cast | \n",
" Population | \n",
" Population_Rank | \n",
" Number_of_LGA | \n",
" Latitude | \n",
" Longitude | \n",
" Voters Turnout | \n",
"
\n",
" \n",
" \n",
" \n",
" 19 | \n",
" Kano | \n",
" Kano | \n",
" KN | \n",
" 4943862 | \n",
" 2364434 | \n",
" 426 | \n",
" 778 | \n",
" 708 | \n",
" 657 | \n",
" 2770 | \n",
" ... | \n",
" 156 | \n",
" 2128821 | \n",
" 43626 | \n",
" 2172447 | \n",
" 9383682 | \n",
" 1 | \n",
" 44 | \n",
" 12.107263 | \n",
" 8.353610 | \n",
" 0.439423 | \n",
"
\n",
" \n",
" 24 | \n",
" Lagos | \n",
" Ikeja | \n",
" LA | \n",
" 5827846 | \n",
" 1678754 | \n",
" 1795 | \n",
" 3038 | \n",
" 4453 | \n",
" 2072 | \n",
" 2177 | \n",
" ... | \n",
" 244 | \n",
" 1443686 | \n",
" 52289 | \n",
" 1495975 | \n",
" 9013534 | \n",
" 2 | \n",
" 20 | \n",
" 6.455966 | \n",
" 3.263435 | \n",
" 0.256694 | \n",
"
\n",
" \n",
" 18 | \n",
" Kaduna | \n",
" Kaduna | \n",
" KD | \n",
" 3361793 | \n",
" 1746031 | \n",
" 218 | \n",
" 424 | \n",
" 273 | \n",
" 546 | \n",
" 1611 | \n",
" ... | \n",
" 78 | \n",
" 1617482 | \n",
" 32719 | \n",
" 1650201 | \n",
" 6066562 | \n",
" 3 | \n",
" 23 | \n",
" 10.704459 | \n",
" 7.331567 | \n",
" 0.490869 | \n",
"
\n",
" \n",
" 20 | \n",
" Katsina | \n",
" Katsina | \n",
" KT | \n",
" 2842741 | \n",
" 1578646 | \n",
" 183 | \n",
" 402 | \n",
" 283 | \n",
" 498 | \n",
" 1671 | \n",
" ... | \n",
" 72 | \n",
" 1449426 | \n",
" 32288 | \n",
" 1481714 | \n",
" 5792578 | \n",
" 4 | \n",
" 34 | \n",
" 13.029105 | \n",
" 7.491887 | \n",
" 0.521227 | \n",
"
\n",
" \n",
" 30 | \n",
" Oyo | \n",
" Ibadan | \n",
" OY | \n",
" 2344448 | \n",
" 1073849 | \n",
" 6331 | \n",
" 8979 | \n",
" 6282 | \n",
" 5000 | \n",
" 4468 | \n",
" ... | \n",
" 3665 | \n",
" 881352 | \n",
" 47254 | \n",
" 928606 | \n",
" 5591589 | \n",
" 5 | \n",
" 33 | \n",
" 8.219491 | \n",
" 3.744396 | \n",
" 0.396087 | \n",
"
\n",
" \n",
"
\n",
"
5 rows × 28 columns
\n",
"
"
],
"text/plain": [
" State Capital Code Number_of_Reg_Voters Number_of_Accr_Voters AA \\\n",
"19 Kano Kano KN 4943862 2364434 426 \n",
"24 Lagos Ikeja LA 5827846 1678754 1795 \n",
"18 Kaduna Kaduna KD 3361793 1746031 218 \n",
"20 Katsina Katsina KT 2842741 1578646 183 \n",
"30 Oyo Ibadan OY 2344448 1073849 6331 \n",
"\n",
" ACPN AD ADC APA ... UPP Number_of_Valid_Votes \\\n",
"19 778 708 657 2770 ... 156 2128821 \n",
"24 3038 4453 2072 2177 ... 244 1443686 \n",
"18 424 273 546 1611 ... 78 1617482 \n",
"20 402 283 498 1671 ... 72 1449426 \n",
"30 8979 6282 5000 4468 ... 3665 881352 \n",
"\n",
" Number_of_Rejected_Votes Total_Votes_Cast Population Population_Rank \\\n",
"19 43626 2172447 9383682 1 \n",
"24 52289 1495975 9013534 2 \n",
"18 32719 1650201 6066562 3 \n",
"20 32288 1481714 5792578 4 \n",
"30 47254 928606 5591589 5 \n",
"\n",
" Number_of_LGA Latitude Longitude Voters Turnout \n",
"19 44 12.107263 8.353610 0.439423 \n",
"24 20 6.455966 3.263435 0.256694 \n",
"18 23 10.704459 7.331567 0.490869 \n",
"20 34 13.029105 7.491887 0.521227 \n",
"30 33 8.219491 3.744396 0.396087 \n",
"\n",
"[5 rows x 28 columns]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inec_table.sort_values(\"Population\", ascending=False)[:5]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Which party got the highest vote among the top states with the highest \"Population\""
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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D7AFukL3kleZ6AImkqiqgsrLY9V9YGGjWfcaYJu/JyclR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\nSeobi02SJEmSJEnqm/8DTqgkvwfGGtYAAAAASUVORK5CYII=\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"win3 = inec_table.sort_values(\"Population\", ascending=False)[:5]\n",
"\n",
"win3.plot(x=\"State\", y=['AA', 'ACPN', 'AD', 'ADC', 'APA', 'APC', 'CPP', 'HOPE', 'KOWA', 'NCP', 'PDP', 'PPN', 'UDP', 'UPP'], \n",
" figsize=(20, 5), kind=\"bar\", grid=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Five top states with the highest \"Number_of_LGA\""
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" State | \n",
" Capital | \n",
" Code | \n",
" Number_of_Reg_Voters | \n",
" Number_of_Accr_Voters | \n",
" AA | \n",
" ACPN | \n",
" AD | \n",
" ADC | \n",
" APA | \n",
" ... | \n",
" UPP | \n",
" Number_of_Valid_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Total_Votes_Cast | \n",
" Population | \n",
" Population_Rank | \n",
" Number_of_LGA | \n",
" Latitude | \n",
" Longitude | \n",
" Voters Turnout | \n",
"
\n",
" \n",
" \n",
" \n",
" 19 | \n",
" Kano | \n",
" Kano | \n",
" KN | \n",
" 4943862 | \n",
" 2364434 | \n",
" 426 | \n",
" 778 | \n",
" 708 | \n",
" 657 | \n",
" 2770 | \n",
" ... | \n",
" 156 | \n",
" 2128821 | \n",
" 43626 | \n",
" 2172447 | \n",
" 9383682 | \n",
" 1 | \n",
" 44 | \n",
" 12.107263 | \n",
" 8.353610 | \n",
" 0.439423 | \n",
"
\n",
" \n",
" 20 | \n",
" Katsina | \n",
" Katsina | \n",
" KT | \n",
" 2842741 | \n",
" 1578646 | \n",
" 183 | \n",
" 402 | \n",
" 283 | \n",
" 498 | \n",
" 1671 | \n",
" ... | \n",
" 72 | \n",
" 1449426 | \n",
" 32288 | \n",
" 1481714 | \n",
" 5792578 | \n",
" 4 | \n",
" 34 | \n",
" 13.029105 | \n",
" 7.491887 | \n",
" 0.521227 | \n",
"
\n",
" \n",
" 30 | \n",
" Oyo | \n",
" Ibadan | \n",
" OY | \n",
" 2344448 | \n",
" 1073849 | \n",
" 6331 | \n",
" 8979 | \n",
" 6282 | \n",
" 5000 | \n",
" 4468 | \n",
" ... | \n",
" 3665 | \n",
" 881352 | \n",
" 47254 | \n",
" 928606 | \n",
" 5591589 | \n",
" 5 | \n",
" 33 | \n",
" 8.219491 | \n",
" 3.744396 | \n",
" 0.396087 | \n",
"
\n",
" \n",
" 2 | \n",
" Akwa Ibom | \n",
" Uyo | \n",
" AK | \n",
" 1644481 | \n",
" 1074070 | \n",
" 1600 | \n",
" 443 | \n",
" 474 | \n",
" 608 | \n",
" 384 | \n",
" ... | \n",
" 144 | \n",
" 1017064 | \n",
" 11487 | \n",
" 1028551 | \n",
" 3920208 | \n",
" 15 | \n",
" 31 | \n",
" 4.832722 | \n",
" 7.812528 | \n",
" 0.625456 | \n",
"
\n",
" \n",
" 29 | \n",
" Osun | \n",
" Oshogbo | \n",
" OS | \n",
" 1378113 | \n",
" 683169 | \n",
" 377 | \n",
" 1731 | \n",
" 1667 | \n",
" 937 | \n",
" 1306 | \n",
" ... | \n",
" 159 | \n",
" 642615 | \n",
" 20758 | \n",
" 663373 | \n",
" 3423535 | \n",
" 19 | \n",
" 30 | \n",
" 7.578210 | \n",
" 4.485878 | \n",
" 0.481363 | \n",
"
\n",
" \n",
"
\n",
"
5 rows × 28 columns
\n",
"
"
],
"text/plain": [
" State Capital Code Number_of_Reg_Voters Number_of_Accr_Voters \\\n",
"19 Kano Kano KN 4943862 2364434 \n",
"20 Katsina Katsina KT 2842741 1578646 \n",
"30 Oyo Ibadan OY 2344448 1073849 \n",
"2 Akwa Ibom Uyo AK 1644481 1074070 \n",
"29 Osun Oshogbo OS 1378113 683169 \n",
"\n",
" AA ACPN AD ADC APA ... UPP Number_of_Valid_Votes \\\n",
"19 426 778 708 657 2770 ... 156 2128821 \n",
"20 183 402 283 498 1671 ... 72 1449426 \n",
"30 6331 8979 6282 5000 4468 ... 3665 881352 \n",
"2 1600 443 474 608 384 ... 144 1017064 \n",
"29 377 1731 1667 937 1306 ... 159 642615 \n",
"\n",
" Number_of_Rejected_Votes Total_Votes_Cast Population Population_Rank \\\n",
"19 43626 2172447 9383682 1 \n",
"20 32288 1481714 5792578 4 \n",
"30 47254 928606 5591589 5 \n",
"2 11487 1028551 3920208 15 \n",
"29 20758 663373 3423535 19 \n",
"\n",
" Number_of_LGA Latitude Longitude Voters Turnout \n",
"19 44 12.107263 8.353610 0.439423 \n",
"20 34 13.029105 7.491887 0.521227 \n",
"30 33 8.219491 3.744396 0.396087 \n",
"2 31 4.832722 7.812528 0.625456 \n",
"29 30 7.578210 4.485878 0.481363 \n",
"\n",
"[5 rows x 28 columns]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inec_table.sort_values(\"Number_of_LGA\", ascending=False)[:5]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Which party got the highest vote among the top states with the highest \"Number_of_LGA\""
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"win4 = inec_table.sort_values(\"Number_of_LGA\", ascending=False)[:5]\n",
"\n",
"win4.plot(x=\"State\", y=['AA', 'ACPN', 'AD', 'ADC', 'APA', 'APC', 'CPP', 'HOPE', 'KOWA', 'NCP', 'PDP', 'PPN', 'UDP', 'UPP'], \n",
" figsize=(20, 5), kind=\"bar\", grid=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Lets extract the following columns out to form a separate dataframe from the dataset\n",
"1~ Number_of_Registered_Voters
\n",
"2~ Number_of_Accredited_Voters
\n",
"3~ Number_of_Valid_Votes
\n",
"4~ Number_of_Rejected_Votes
\n",
"5~ Total_Votes_Cast
\n",
"6~ Population
\n",
"7~ Population_Rank
\n",
"8~ Number_of_LGA
"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" State | \n",
" Number_of_Reg_Voters | \n",
" Number_of_Accr_Voters | \n",
" Number_of_Valid_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Total_Votes_Cast | \n",
" Population | \n",
" Population_Rank | \n",
" Number_of_LGA | \n",
"
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" \n",
" \n",
" \n",
" 0 | \n",
" Abia | \n",
" 1349134 | \n",
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" 391045 | \n",
" 10004 | \n",
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" 17 | \n",
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" 1 | \n",
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" 1518123 | \n",
" 709993 | \n",
" 636018 | \n",
" 25192 | \n",
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" 661210 | \n",
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" Akwa Ibom | \n",
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" 1963427 | \n",
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" 4672 | \n",
" 4672 | \n",
" 371739 | \n",
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" 36 | \n",
" 8 | \n",
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" 19867 | \n",
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" 703131 | \n",
" 4219244 | \n",
" 9 | \n",
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" 7 | \n",
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" 515008 | \n",
" 4151193 | \n",
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" 27 | \n",
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" 8 | \n",
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" 1449426 | \n",
" 32288 | \n",
" 32288 | \n",
" 1481714 | \n",
" 5792578 | \n",
" 4 | \n",
" 34 | \n",
"
\n",
" \n",
" 21 | \n",
" Kebbi | \n",
" 1457763 | \n",
" 792817 | \n",
" 677003 | \n",
" 38119 | \n",
" 38119 | \n",
" 715122 | \n",
" 3238628 | \n",
" 23 | \n",
" 21 | \n",
"
\n",
" \n",
" 22 | \n",
" Kogi | \n",
" 1350883 | \n",
" 476839 | \n",
" 421328 | \n",
" 17959 | \n",
" 17959 | \n",
" 439287 | \n",
" 3278487 | \n",
" 20 | \n",
" 21 | \n",
"
\n",
" \n",
" 23 | \n",
" Kwara | \n",
" 1181032 | \n",
" 489360 | \n",
" 440080 | \n",
" 21321 | \n",
" 21321 | \n",
" 461401 | \n",
" 2371089 | \n",
" 30 | \n",
" 16 | \n",
"
\n",
" \n",
" 24 | \n",
" Lagos | \n",
" 5827846 | \n",
" 1678754 | \n",
" 1443686 | \n",
" 52289 | \n",
" 52289 | \n",
" 1495975 | \n",
" 9013534 | \n",
" 2 | \n",
" 20 | \n",
"
\n",
" \n",
" 25 | \n",
" Nasarawa | \n",
" 1222054 | \n",
" 562959 | \n",
" 511547 | \n",
" 10094 | \n",
" 10094 | \n",
" 521641 | \n",
" 1863275 | \n",
" 35 | \n",
" 13 | \n",
"
\n",
" \n",
" 26 | \n",
" Niger | \n",
" 1995679 | \n",
" 933607 | \n",
" 813671 | \n",
" 31012 | \n",
" 31012 | \n",
" 844683 | \n",
" 3950249 | \n",
" 13 | \n",
" 25 | \n",
"
\n",
" \n",
" 27 | \n",
" Ogun | \n",
" 1709409 | \n",
" 594975 | \n",
" 533172 | \n",
" 26441 | \n",
" 26441 | \n",
" 559613 | \n",
" 3728098 | \n",
" 16 | \n",
" 20 | \n",
"
\n",
" \n",
" 28 | \n",
" Ondo | \n",
" 1501549 | \n",
" 618040 | \n",
" 561056 | \n",
" 21379 | \n",
" 21379 | \n",
" 582435 | \n",
" 3441024 | \n",
" 18 | \n",
" 18 | \n",
"
\n",
" \n",
" 29 | \n",
" Osun | \n",
" 1378113 | \n",
" 683169 | \n",
" 642615 | \n",
" 20758 | \n",
" 20758 | \n",
" 663373 | \n",
" 3423535 | \n",
" 19 | \n",
" 30 | \n",
"
\n",
" \n",
" 30 | \n",
" Oyo | \n",
" 2344448 | \n",
" 1073849 | \n",
" 881352 | \n",
" 47254 | \n",
" 47254 | \n",
" 928606 | \n",
" 5591589 | \n",
" 5 | \n",
" 33 | \n",
"
\n",
" \n",
" 31 | \n",
" Plateau | \n",
" 1977211 | \n",
" 1076833 | \n",
" 982388 | \n",
" 18304 | \n",
" 18304 | \n",
" 1000692 | \n",
" 3178712 | \n",
" 25 | \n",
" 17 | \n",
"
\n",
" \n",
" 32 | \n",
" Rivers | \n",
" 2324300 | \n",
" 1643409 | \n",
" 1565461 | \n",
" 19307 | \n",
" 19307 | \n",
" 1584768 | \n",
" 5185400 | \n",
" 6 | \n",
" 23 | \n",
"
\n",
" \n",
" 33 | \n",
" Sokoto | \n",
" 1663127 | \n",
" 988899 | \n",
" 834259 | \n",
" 42110 | \n",
" 42110 | \n",
" 876369 | \n",
" 3696999 | \n",
" 17 | \n",
" 23 | \n",
"
\n",
" \n",
" 34 | \n",
" Taraba | \n",
" 1374307 | \n",
" 638578 | \n",
" 579677 | \n",
" 23039 | \n",
" 23039 | \n",
" 602716 | \n",
" 2300736 | \n",
" 33 | \n",
" 16 | \n",
"
\n",
" \n",
" 35 | \n",
" Yobe | \n",
" 1077942 | \n",
" 520127 | \n",
" 473796 | \n",
" 17971 | \n",
" 17971 | \n",
" 491767 | \n",
" 2321591 | \n",
" 32 | \n",
" 17 | \n",
"
\n",
" \n",
" 36 | \n",
" Zamfara | \n",
" 1484941 | \n",
" 875049 | \n",
" 761022 | \n",
" 19157 | \n",
" 19157 | \n",
" 780179 | \n",
" 3259846 | \n",
" 21 | \n",
" 14 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" State Number_of_Reg_Voters Number_of_Accr_Voters \\\n",
"0 Abia 1349134 442538 \n",
"1 Adamawa 1518123 709993 \n",
"2 Akwa Ibom 1644481 1074070 \n",
"3 Anambra 1963427 774430 \n",
"4 Bauchi 2053484 1094069 \n",
"5 Bayelsa 605637 384789 \n",
"6 Benue 1893596 754634 \n",
"7 Borno 1799669 544759 \n",
"8 Cross River 1144288 500577 \n",
"9 Delta 2044372 1350914 \n",
"10 Ebonyi 1071226 425301 \n",
"11 Edo 1650552 599166 \n",
"12 Ekiti 723255 323739 \n",
"13 Enugu 1381563 616112 \n",
"14 Federal Capital Territory 886573 344056 \n",
"15 Gombe 1110105 515828 \n",
"16 Imo 1747681 801712 \n",
"17 Jigawa 1815889 1153428 \n",
"18 Kaduna 3361793 1746031 \n",
"19 Kano 4943862 2364434 \n",
"20 Katsina 2842741 1578646 \n",
"21 Kebbi 1457763 792817 \n",
"22 Kogi 1350883 476839 \n",
"23 Kwara 1181032 489360 \n",
"24 Lagos 5827846 1678754 \n",
"25 Nasarawa 1222054 562959 \n",
"26 Niger 1995679 933607 \n",
"27 Ogun 1709409 594975 \n",
"28 Ondo 1501549 618040 \n",
"29 Osun 1378113 683169 \n",
"30 Oyo 2344448 1073849 \n",
"31 Plateau 1977211 1076833 \n",
"32 Rivers 2324300 1643409 \n",
"33 Sokoto 1663127 988899 \n",
"34 Taraba 1374307 638578 \n",
"35 Yobe 1077942 520127 \n",
"36 Zamfara 1484941 875049 \n",
"\n",
" Number_of_Valid_Votes Number_of_Rejected_Votes Number_of_Rejected_Votes \\\n",
"0 391045 10004 10004 \n",
"1 636018 25192 25192 \n",
"2 1017064 11487 11487 \n",
"3 688584 14825 14825 \n",
"4 1020338 19437 19437 \n",
"5 367067 4672 4672 \n",
"6 683264 19867 19867 \n",
"7 501920 13088 13088 \n",
"8 450514 15392 15392 \n",
"9 1267773 17075 17075 \n",
"10 363888 29449 29449 \n",
"11 500451 22334 22334 \n",
"12 300691 8754 8754 \n",
"13 573173 12459 12459 \n",
"14 306805 9210 9210 \n",
"15 460599 12845 12845 \n",
"16 702964 28957 28957 \n",
"17 1037564 34325 34325 \n",
"18 1617482 32719 32719 \n",
"19 2128821 43626 43626 \n",
"20 1449426 32288 32288 \n",
"21 677003 38119 38119 \n",
"22 421328 17959 17959 \n",
"23 440080 21321 21321 \n",
"24 1443686 52289 52289 \n",
"25 511547 10094 10094 \n",
"26 813671 31012 31012 \n",
"27 533172 26441 26441 \n",
"28 561056 21379 21379 \n",
"29 642615 20758 20758 \n",
"30 881352 47254 47254 \n",
"31 982388 18304 18304 \n",
"32 1565461 19307 19307 \n",
"33 834259 42110 42110 \n",
"34 579677 23039 23039 \n",
"35 473796 17971 17971 \n",
"36 761022 19157 19157 \n",
"\n",
" Total_Votes_Cast Population Population_Rank Number_of_LGA \n",
"0 401049 2833999 28 17 \n",
"1 661210 3168101 26 21 \n",
"2 1028551 3920208 15 31 \n",
"3 703409 4182032 10 21 \n",
"4 1039775 4676465 7 20 \n",
"5 371739 1703358 36 8 \n",
"6 703131 4219244 9 23 \n",
"7 515008 4151193 11 27 \n",
"8 465906 2888966 27 18 \n",
"9 1284848 4098391 12 25 \n",
"10 393337 2173501 34 13 \n",
"11 522785 3218332 24 18 \n",
"12 309445 2384212 29 16 \n",
"13 585632 3257298 22 17 \n",
"14 316015 1405201 37 6 \n",
"15 473444 2353879 31 11 \n",
"16 731921 3934899 14 27 \n",
"17 1071889 4348649 8 27 \n",
"18 1650201 6066562 3 23 \n",
"19 2172447 9383682 1 44 \n",
"20 1481714 5792578 4 34 \n",
"21 715122 3238628 23 21 \n",
"22 439287 3278487 20 21 \n",
"23 461401 2371089 30 16 \n",
"24 1495975 9013534 2 20 \n",
"25 521641 1863275 35 13 \n",
"26 844683 3950249 13 25 \n",
"27 559613 3728098 16 20 \n",
"28 582435 3441024 18 18 \n",
"29 663373 3423535 19 30 \n",
"30 928606 5591589 5 33 \n",
"31 1000692 3178712 25 17 \n",
"32 1584768 5185400 6 23 \n",
"33 876369 3696999 17 23 \n",
"34 602716 2300736 33 16 \n",
"35 491767 2321591 32 17 \n",
"36 780179 3259846 21 14 "
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"voters_table = inec_table[['State', 'Number_of_Reg_Voters', 'Number_of_Accr_Voters', 'Number_of_Valid_Votes', 'Number_of_Rejected_Votes', \n",
" 'Number_of_Rejected_Votes', 'Total_Votes_Cast', 'Population', 'Population_Rank', 'Number_of_LGA']]\n",
"voters_table"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Summary statistics of voters_table"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Number_of_Reg_Voters | \n",
" Number_of_Accr_Voters | \n",
" Number_of_Valid_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Number_of_Rejected_Votes | \n",
" Total_Votes_Cast | \n",
" Population | \n",
" Population_Rank | \n",
" Number_of_LGA | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 3.700000e+01 | \n",
" 3.700000e+01 | \n",
" 3.700000e+01 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 3.700000e+01 | \n",
" 3.700000e+01 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
"
\n",
" \n",
" mean | \n",
" 1.822218e+06 | \n",
" 8.580132e+05 | \n",
" 7.726369e+05 | \n",
" 22824.837838 | \n",
" 22824.837838 | \n",
" 7.954617e+05 | \n",
" 3.783880e+06 | \n",
" 19.000000 | \n",
" 20.918919 | \n",
"
\n",
" \n",
" std | \n",
" 1.026219e+06 | \n",
" 4.641212e+05 | \n",
" 4.245404e+05 | \n",
" 11468.557038 | \n",
" 11468.557038 | \n",
" 4.310620e+05 | \n",
" 1.713420e+06 | \n",
" 10.824355 | \n",
" 7.488430 | \n",
"
\n",
" \n",
" min | \n",
" 6.056370e+05 | \n",
" 3.237390e+05 | \n",
" 3.006910e+05 | \n",
" 4672.000000 | \n",
" 4672.000000 | \n",
" 3.094450e+05 | \n",
" 1.405201e+06 | \n",
" 1.000000 | \n",
" 6.000000 | \n",
"
\n",
" \n",
" 25% | \n",
" 1.349134e+06 | \n",
" 5.201270e+05 | \n",
" 4.737960e+05 | \n",
" 14825.000000 | \n",
" 14825.000000 | \n",
" 4.917670e+05 | \n",
" 2.833999e+06 | \n",
" 10.000000 | \n",
" 17.000000 | \n",
"
\n",
" \n",
" 50% | \n",
" 1.644481e+06 | \n",
" 7.099930e+05 | \n",
" 6.426150e+05 | \n",
" 19867.000000 | \n",
" 19867.000000 | \n",
" 6.633730e+05 | \n",
" 3.423535e+06 | \n",
" 19.000000 | \n",
" 20.000000 | \n",
"
\n",
" \n",
" 75% | \n",
" 1.977211e+06 | \n",
" 1.074070e+06 | \n",
" 9.823880e+05 | \n",
" 29449.000000 | \n",
" 29449.000000 | \n",
" 1.000692e+06 | \n",
" 4.182032e+06 | \n",
" 28.000000 | \n",
" 25.000000 | \n",
"
\n",
" \n",
" max | \n",
" 5.827846e+06 | \n",
" 2.364434e+06 | \n",
" 2.128821e+06 | \n",
" 52289.000000 | \n",
" 52289.000000 | \n",
" 2.172447e+06 | \n",
" 9.383682e+06 | \n",
" 37.000000 | \n",
" 44.000000 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Number_of_Reg_Voters Number_of_Accr_Voters Number_of_Valid_Votes \\\n",
"count 3.700000e+01 3.700000e+01 3.700000e+01 \n",
"mean 1.822218e+06 8.580132e+05 7.726369e+05 \n",
"std 1.026219e+06 4.641212e+05 4.245404e+05 \n",
"min 6.056370e+05 3.237390e+05 3.006910e+05 \n",
"25% 1.349134e+06 5.201270e+05 4.737960e+05 \n",
"50% 1.644481e+06 7.099930e+05 6.426150e+05 \n",
"75% 1.977211e+06 1.074070e+06 9.823880e+05 \n",
"max 5.827846e+06 2.364434e+06 2.128821e+06 \n",
"\n",
" Number_of_Rejected_Votes Number_of_Rejected_Votes Total_Votes_Cast \\\n",
"count 37.000000 37.000000 3.700000e+01 \n",
"mean 22824.837838 22824.837838 7.954617e+05 \n",
"std 11468.557038 11468.557038 4.310620e+05 \n",
"min 4672.000000 4672.000000 3.094450e+05 \n",
"25% 14825.000000 14825.000000 4.917670e+05 \n",
"50% 19867.000000 19867.000000 6.633730e+05 \n",
"75% 29449.000000 29449.000000 1.000692e+06 \n",
"max 52289.000000 52289.000000 2.172447e+06 \n",
"\n",
" Population Population_Rank Number_of_LGA \n",
"count 3.700000e+01 37.000000 37.000000 \n",
"mean 3.783880e+06 19.000000 20.918919 \n",
"std 1.713420e+06 10.824355 7.488430 \n",
"min 1.405201e+06 1.000000 6.000000 \n",
"25% 2.833999e+06 10.000000 17.000000 \n",
"50% 3.423535e+06 19.000000 20.000000 \n",
"75% 4.182032e+06 28.000000 25.000000 \n",
"max 9.383682e+06 37.000000 44.000000 "
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"voters_table.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Graph \"Number_of_Registered_Voters\" Vs \"Number_of_Accredited_Voters\" Vs \"Population\"\n",
"Naturally, \"Number_of_Registered_Voters\" should be higher than \"Number_of_Accredited_Voters\". Likewise, \"Population\" should be higher than both \"Number_of_Registered_Voters\" and \"Number_of_Accredited_Voters\". Lets see if there is any odd case in any particular state?"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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mZt9xzv1eUofnr5n9cxDdVv0jJT0iabCaBo0/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"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"voters_table.plot(x='State', y=['Number_of_Reg_Voters', 'Number_of_Accr_Voters', 'Population'], kind='bar', figsize=(20, 5), title='Bar Plot', grid=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Lets extract the parties columns out to form a separate dataframe from the dataset"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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" AA | \n",
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" CPP | \n",
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" 708 | \n",
" 657 | \n",
" 2770 | \n",
" 1903999 | \n",
" 1552 | \n",
" 292 | \n",
" 288 | \n",
" 697 | \n",
" 215779 | \n",
" 485 | \n",
" 234 | \n",
" 156 | \n",
"
\n",
" \n",
" 20 | \n",
" Katsina | \n",
" 183 | \n",
" 402 | \n",
" 283 | \n",
" 498 | \n",
" 1671 | \n",
" 1345441 | \n",
" 976 | \n",
" 47 | \n",
" 215 | \n",
" 330 | \n",
" 98937 | \n",
" 254 | \n",
" 117 | \n",
" 72 | \n",
"
\n",
" \n",
" 21 | \n",
" Kebbi | \n",
" 214 | \n",
" 361 | \n",
" 450 | \n",
" 472 | \n",
" 2685 | \n",
" 567883 | \n",
" 1794 | \n",
" 213 | \n",
" 448 | \n",
" 519 | \n",
" 100972 | \n",
" 547 | \n",
" 207 | \n",
" 238 | \n",
"
\n",
" \n",
" 22 | \n",
" Kogi | \n",
" 700 | \n",
" 1089 | \n",
" 427 | \n",
" 761 | \n",
" 1001 | \n",
" 264851 | \n",
" 967 | \n",
" 144 | \n",
" 190 | \n",
" 399 | \n",
" 149987 | \n",
" 476 | \n",
" 180 | \n",
" 156 | \n",
"
\n",
" \n",
" 23 | \n",
" Kwara | \n",
" 248 | \n",
" 817 | \n",
" 520 | \n",
" 438 | \n",
" 1165 | \n",
" 302146 | \n",
" 910 | \n",
" 118 | \n",
" 214 | \n",
" 394 | \n",
" 132602 | \n",
" 325 | \n",
" 81 | \n",
" 102 | \n",
"
\n",
" \n",
" 24 | \n",
" Lagos | \n",
" 1795 | \n",
" 3038 | \n",
" 4453 | \n",
" 2072 | \n",
" 2177 | \n",
" 792460 | \n",
" 1125 | \n",
" 255 | \n",
" 1000 | \n",
" 1430 | \n",
" 632327 | \n",
" 1041 | \n",
" 269 | \n",
" 244 | \n",
"
\n",
" \n",
" 25 | \n",
" Nasarawa | \n",
" 40 | \n",
" 95 | \n",
" 74 | \n",
" 105 | \n",
" 310 | \n",
" 236838 | \n",
" 131 | \n",
" 4 | \n",
" 48 | \n",
" 222 | \n",
" 273460 | \n",
" 164 | \n",
" 23 | \n",
" 33 | \n",
"
\n",
" \n",
" 26 | \n",
" Niger | \n",
" 307 | \n",
" 441 | \n",
" 403 | \n",
" 614 | \n",
" 2006 | \n",
" 657678 | \n",
" 1264 | \n",
" 198 | \n",
" 305 | \n",
" 550 | \n",
" 149222 | \n",
" 449 | \n",
" 116 | \n",
" 118 | \n",
"
\n",
" \n",
" 27 | \n",
" Ogun | \n",
" 584 | \n",
" 3072 | \n",
" 1927 | \n",
" 1364 | \n",
" 1930 | \n",
" 308290 | \n",
" 978 | \n",
" 332 | \n",
" 432 | \n",
" 815 | \n",
" 207950 | \n",
" 4339 | \n",
" 562 | \n",
" 597 | \n",
"
\n",
" \n",
" 28 | \n",
" Ondo | \n",
" 386 | \n",
" 2406 | \n",
" 1237 | \n",
" 1227 | \n",
" 1139 | \n",
" 299889 | \n",
" 1012 | \n",
" 184 | \n",
" 223 | \n",
" 846 | \n",
" 251368 | \n",
" 734 | \n",
" 184 | \n",
" 221 | \n",
"
\n",
" \n",
" 29 | \n",
" Osun | \n",
" 377 | \n",
" 1731 | \n",
" 1667 | \n",
" 937 | \n",
" 1306 | \n",
" 383603 | \n",
" 1029 | \n",
" 132 | \n",
" 255 | \n",
" 767 | \n",
" 249929 | \n",
" 599 | \n",
" 124 | \n",
" 159 | \n",
"
\n",
" \n",
" 30 | \n",
" Oyo | \n",
" 6331 | \n",
" 8979 | \n",
" 6282 | \n",
" 5000 | \n",
" 4468 | \n",
" 528620 | \n",
" 6674 | \n",
" 839 | \n",
" 1312 | \n",
" 1895 | \n",
" 303376 | \n",
" 2842 | \n",
" 1069 | \n",
" 3665 | \n",
"
\n",
" \n",
" 31 | \n",
" Plateau | \n",
" 178 | \n",
" 391 | \n",
" 279 | \n",
" 406 | \n",
" 618 | \n",
" 429140 | \n",
" 237 | \n",
" 56 | \n",
" 138 | \n",
" 693 | \n",
" 549615 | \n",
" 554 | \n",
" 54 | \n",
" 29 | \n",
"
\n",
" \n",
" 32 | \n",
" Rivers | \n",
" 1066 | \n",
" 525 | \n",
" 1104 | \n",
" 1031 | \n",
" 513 | \n",
" 69238 | \n",
" 577 | \n",
" 542 | \n",
" 2274 | \n",
" 565 | \n",
" 1487075 | \n",
" 492 | \n",
" 303 | \n",
" 156 | \n",
"
\n",
" \n",
" 33 | \n",
" Sokoto | \n",
" 249 | \n",
" 535 | \n",
" 714 | \n",
" 762 | \n",
" 3482 | \n",
" 671926 | \n",
" 1894 | \n",
" 283 | \n",
" 475 | \n",
" 686 | \n",
" 152199 | \n",
" 605 | \n",
" 269 | \n",
" 180 | \n",
"
\n",
" \n",
" 34 | \n",
" Taraba | \n",
" 962 | \n",
" 811 | \n",
" 586 | \n",
" 320 | \n",
" 1306 | \n",
" 261326 | \n",
" 1033 | \n",
" 161 | \n",
" 153 | \n",
" 876 | \n",
" 310800 | \n",
" 680 | \n",
" 224 | \n",
" 439 | \n",
"
\n",
" \n",
" 35 | \n",
" Yobe | \n",
" 101 | \n",
" 164 | \n",
" 213 | \n",
" 112 | \n",
" 632 | \n",
" 446265 | \n",
" 329 | \n",
" 67 | \n",
" 104 | \n",
" 120 | \n",
" 25526 | \n",
" 101 | \n",
" 30 | \n",
" 32 | \n",
"
\n",
" \n",
" 36 | \n",
" Zamfara | \n",
" 125 | \n",
" 238 | \n",
" 290 | \n",
" 294 | \n",
" 1310 | \n",
" 612202 | \n",
" 655 | \n",
" 14 | \n",
" 122 | \n",
" 404 | \n",
" 144833 | \n",
" 374 | \n",
" 93 | \n",
" 68 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" State AA ACPN AD ADC APA APC CPP \\\n",
"0 Abia 315 2194 448 569 2766 13394 1046 \n",
"1 Adamawa 495 1166 595 1012 1549 374701 819 \n",
"2 Akwa Ibom 1600 443 474 608 384 58411 412 \n",
"3 Anambra 547 1259 475 534 2303 17926 1279 \n",
"4 Bauchi 131 232 173 189 964 931598 391 \n",
"5 Bayelsa 45 38 69 116 70 5194 44 \n",
"6 Benue 315 1464 254 539 945 373961 567 \n",
"7 Borno 145 243 392 201 878 473543 310 \n",
"8 Cross River 279 514 709 749 532 28358 381 \n",
"9 Delta 1473 916 735 888 478 48910 813 \n",
"10 Ebonyi 426 1214 1133 2704 2452 19518 2345 \n",
"11 Edo 159 1284 450 512 709 208469 325 \n",
"12 Ekiti 94 538 854 424 482 120331 330 \n",
"13 Enugu 441 479 269 478 715 14157 237 \n",
"14 Federal Capital Territory 139 342 240 288 674 146399 347 \n",
"15 Gombe 104 192 169 247 773 361245 407 \n",
"16 Imo 533 956 757 1617 2236 133253 733 \n",
"17 Jigawa 394 540 587 375 2527 885988 1553 \n",
"18 Kaduna 218 424 273 546 1611 1127760 824 \n",
"19 Kano 426 778 708 657 2770 1903999 1552 \n",
"20 Katsina 183 402 283 498 1671 1345441 976 \n",
"21 Kebbi 214 361 450 472 2685 567883 1794 \n",
"22 Kogi 700 1089 427 761 1001 264851 967 \n",
"23 Kwara 248 817 520 438 1165 302146 910 \n",
"24 Lagos 1795 3038 4453 2072 2177 792460 1125 \n",
"25 Nasarawa 40 95 74 105 310 236838 131 \n",
"26 Niger 307 441 403 614 2006 657678 1264 \n",
"27 Ogun 584 3072 1927 1364 1930 308290 978 \n",
"28 Ondo 386 2406 1237 1227 1139 299889 1012 \n",
"29 Osun 377 1731 1667 937 1306 383603 1029 \n",
"30 Oyo 6331 8979 6282 5000 4468 528620 6674 \n",
"31 Plateau 178 391 279 406 618 429140 237 \n",
"32 Rivers 1066 525 1104 1031 513 69238 577 \n",
"33 Sokoto 249 535 714 762 3482 671926 1894 \n",
"34 Taraba 962 811 586 320 1306 261326 1033 \n",
"35 Yobe 101 164 213 112 632 446265 329 \n",
"36 Zamfara 125 238 290 294 1310 612202 655 \n",
"\n",
" HOPE KOWA NCP PDP PPN UDP UPP \n",
"0 125 173 745 368303 424 213 330 \n",
"1 267 752 1212 251664 1163 289 334 \n",
"2 192 160 381 953304 327 224 144 \n",
"3 357 311 887 660762 537 286 1121 \n",
"4 46 128 207 86085 128 29 37 \n",
"5 18 52 95 361209 62 20 35 \n",
"6 115 105 683 303737 439 66 74 \n",
"7 88 158 107 25640 143 31 41 \n",
"8 237 312 930 414863 864 289 1487 \n",
"9 166 311 670 1211405 393 354 261 \n",
"10 989 913 1890 323653 1168 624 4859 \n",
"11 22 175 516 286869 729 160 72 \n",
"12 94 108 377 176466 388 60 145 \n",
"13 110 203 761 553003 407 1623 290 \n",
"14 83 165 473 157195 269 95 96 \n",
"15 46 97 227 96873 157 25 37 \n",
"16 157 158 784 559185 414 264 1917 \n",
"17 337 423 548 142904 853 338 197 \n",
"18 105 176 754 484085 549 79 78 \n",
"19 292 288 697 215779 485 234 156 \n",
"20 47 215 330 98937 254 117 72 \n",
"21 213 448 519 100972 547 207 238 \n",
"22 144 190 399 149987 476 180 156 \n",
"23 118 214 394 132602 325 81 102 \n",
"24 255 1000 1430 632327 1041 269 244 \n",
"25 4 48 222 273460 164 23 33 \n",
"26 198 305 550 149222 449 116 118 \n",
"27 332 432 815 207950 4339 562 597 \n",
"28 184 223 846 251368 734 184 221 \n",
"29 132 255 767 249929 599 124 159 \n",
"30 839 1312 1895 303376 2842 1069 3665 \n",
"31 56 138 693 549615 554 54 29 \n",
"32 542 2274 565 1487075 492 303 156 \n",
"33 283 475 686 152199 605 269 180 \n",
"34 161 153 876 310800 680 224 439 \n",
"35 67 104 120 25526 101 30 32 \n",
"36 14 122 404 144833 374 93 68 "
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"parties_table = inec_table[['State', 'AA', 'ACPN', 'AD', 'ADC', 'APA', 'APC', 'CPP', 'HOPE', 'KOWA', 'NCP', 'PDP', 'PPN', 'UDP', 'UPP']] \n",
"\n",
"parties_table"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Summary statistics of parties_table"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" AA | \n",
" ACPN | \n",
" AD | \n",
" ADC | \n",
" APA | \n",
" APC | \n",
" CPP | \n",
" HOPE | \n",
" KOWA | \n",
" NCP | \n",
" PDP | \n",
" PPN | \n",
" UDP | \n",
" UPP | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 3.700000e+01 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 3.700000e+01 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
" 37.000000 | \n",
"
\n",
" \n",
" mean | \n",
" 597.972973 | \n",
" 1089.486486 | \n",
" 829.000000 | \n",
" 801.783784 | \n",
" 1446.945946 | \n",
" 4.168895e+05 | \n",
" 981.081081 | \n",
" 200.945946 | \n",
" 353.405405 | \n",
" 660.945946 | \n",
" 3.473828e+05 | \n",
" 661.486486 | \n",
" 248.864865 | \n",
" 492.432432 | \n",
"
\n",
" \n",
" std | \n",
" 1058.202944 | \n",
" 1537.150658 | \n",
" 1193.011688 | \n",
" 893.409143 | \n",
" 994.589389 | \n",
" 4.137989e+05 | \n",
" 1098.046583 | \n",
" 208.625388 | \n",
" 425.865489 | \n",
" 418.460336 | \n",
" 3.159930e+05 | \n",
" 780.911704 | \n",
" 307.701800 | \n",
" 1008.016026 | \n",
"
\n",
" \n",
" min | \n",
" 40.000000 | \n",
" 38.000000 | \n",
" 69.000000 | \n",
" 105.000000 | \n",
" 70.000000 | \n",
" 5.194000e+03 | \n",
" 44.000000 | \n",
" 4.000000 | \n",
" 48.000000 | \n",
" 95.000000 | \n",
" 2.552600e+04 | \n",
" 62.000000 | \n",
" 20.000000 | \n",
" 29.000000 | \n",
"
\n",
" \n",
" 25% | \n",
" 159.000000 | \n",
" 391.000000 | \n",
" 279.000000 | \n",
" 375.000000 | \n",
" 674.000000 | \n",
" 1.203310e+05 | \n",
" 381.000000 | \n",
" 83.000000 | \n",
" 153.000000 | \n",
" 394.000000 | \n",
" 1.492220e+05 | \n",
" 327.000000 | \n",
" 79.000000 | \n",
" 72.000000 | \n",
"
\n",
" \n",
" 50% | \n",
" 315.000000 | \n",
" 538.000000 | \n",
" 474.000000 | \n",
" 539.000000 | \n",
" 1165.000000 | \n",
" 3.082900e+05 | \n",
" 819.000000 | \n",
" 144.000000 | \n",
" 203.000000 | \n",
" 670.000000 | \n",
" 2.516640e+05 | \n",
" 476.000000 | \n",
" 184.000000 | \n",
" 156.000000 | \n",
"
\n",
" \n",
" 75% | \n",
" 533.000000 | \n",
" 1214.000000 | \n",
" 735.000000 | \n",
" 888.000000 | \n",
" 2177.000000 | \n",
" 5.678830e+05 | \n",
" 1046.000000 | \n",
" 255.000000 | \n",
" 312.000000 | \n",
" 784.000000 | \n",
" 4.148630e+05 | \n",
" 680.000000 | \n",
" 286.000000 | \n",
" 290.000000 | \n",
"
\n",
" \n",
" max | \n",
" 6331.000000 | \n",
" 8979.000000 | \n",
" 6282.000000 | \n",
" 5000.000000 | \n",
" 4468.000000 | \n",
" 1.903999e+06 | \n",
" 6674.000000 | \n",
" 989.000000 | \n",
" 2274.000000 | \n",
" 1895.000000 | \n",
" 1.487075e+06 | \n",
" 4339.000000 | \n",
" 1623.000000 | \n",
" 4859.000000 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" AA ACPN AD ADC APA \\\n",
"count 37.000000 37.000000 37.000000 37.000000 37.000000 \n",
"mean 597.972973 1089.486486 829.000000 801.783784 1446.945946 \n",
"std 1058.202944 1537.150658 1193.011688 893.409143 994.589389 \n",
"min 40.000000 38.000000 69.000000 105.000000 70.000000 \n",
"25% 159.000000 391.000000 279.000000 375.000000 674.000000 \n",
"50% 315.000000 538.000000 474.000000 539.000000 1165.000000 \n",
"75% 533.000000 1214.000000 735.000000 888.000000 2177.000000 \n",
"max 6331.000000 8979.000000 6282.000000 5000.000000 4468.000000 \n",
"\n",
" APC CPP HOPE KOWA NCP \\\n",
"count 3.700000e+01 37.000000 37.000000 37.000000 37.000000 \n",
"mean 4.168895e+05 981.081081 200.945946 353.405405 660.945946 \n",
"std 4.137989e+05 1098.046583 208.625388 425.865489 418.460336 \n",
"min 5.194000e+03 44.000000 4.000000 48.000000 95.000000 \n",
"25% 1.203310e+05 381.000000 83.000000 153.000000 394.000000 \n",
"50% 3.082900e+05 819.000000 144.000000 203.000000 670.000000 \n",
"75% 5.678830e+05 1046.000000 255.000000 312.000000 784.000000 \n",
"max 1.903999e+06 6674.000000 989.000000 2274.000000 1895.000000 \n",
"\n",
" PDP PPN UDP UPP \n",
"count 3.700000e+01 37.000000 37.000000 37.000000 \n",
"mean 3.473828e+05 661.486486 248.864865 492.432432 \n",
"std 3.159930e+05 780.911704 307.701800 1008.016026 \n",
"min 2.552600e+04 62.000000 20.000000 29.000000 \n",
"25% 1.492220e+05 327.000000 79.000000 72.000000 \n",
"50% 2.516640e+05 476.000000 184.000000 156.000000 \n",
"75% 4.148630e+05 680.000000 286.000000 290.000000 \n",
"max 1.487075e+06 4339.000000 1623.000000 4859.000000 "
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"parties_table.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Sum of Votes gotten by each party"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"AA 22125\n",
"ACPN 40311\n",
"AD 30673\n",
"ADC 29666\n",
"APA 53537\n",
"APC 15424911\n",
"CPP 36300\n",
"HOPE 7435\n",
"KOWA 13076\n",
"NCP 24455\n",
"PDP 12853162\n",
"PPN 24475\n",
"UDP 9208\n",
"UPP 18220\n",
"dtype: int64"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vote_sum = parties_table[['AA', 'ACPN', 'AD', 'ADC', 'APA', 'APC', 'CPP', 'HOPE', 'KOWA', 'NCP', 'PDP', 'PPN', 'UDP', 'UPP']].sum()\n",
"\n",
"vote_sum"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Visualize the total votes by party"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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mGzk7Cz8AAAAAW0qPHwB2il4NAJyE6wYwAj1+AAAAAHaQhZ81I+/Z2wTym052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\nbCkLPwAAAABbysIPAAAAwJb6/wFOAdMy2WD5zAAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"vote_sum.plot(kind='bar', figsize=(20, 5), grid=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### As you can see, votes gotten by \"APC\" and \"PDP\" far outweighs that of other parties. So lets focus on these two biggest parties..."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Visualize votes of \"APC\" and \"PDP\" by states"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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wrBd1mc23JEmSNCZmvpepJPsBbwQeBAT4APCiqvrpdp7XzPeozZj5liRpKZj5\n1jitB9ZX1YHAgcDuwCvanZIkSVK/2XwvQ0keDdxcVesAmltS/gnwzCQXJjl40bHnJzkoyYokZyfZ\nkORTSQ5qafrqEXOZGpS1omFYL+oym+/l6cHAJYt3VNVNwNeADwInAiQ5ELh7VV0JnApcWlUPAV4K\nrBvrjCVJknrA5lubOxt4UpIdmW/Cz2j2Hw68FaCqPg6sTHLPdqaovpienm57CpoQ1oqGYb2oy7zD\n5fL0OeA3F+9IsgewP/CfwEeBY4BjgYc1h2z+jb+tfzlhZkSz1Lwdlu9dQ1esmGL9+jM3/UW68KNk\nx44dO3bs+K6MF7bn5uZoi1c7WaaSXAT8TVW9rVnl/jvgv6vqT5OsBd4PfKKqntYc/3rgv6rq5Umm\ngddW1cO2cN762T5d2ppZYHobz8crvQiY/8ty4S9R6c5YLxqUVzvROD0FOC7Jl4AvADczn+Wmqi4F\nvsftkROYz3w/LMkG5q+KcsJ4pytJkjT5XPnWz0hyH+BjVfXAu/BaV741Qq58S5KWjivfal2S/xe4\nAHhJ23ORJEnqG5tv3UFVvbWqVlfV+rbnouVgtu0JaEIs/rKUdGesF3WZzbckSZI0Jma+NVJmvjVa\nZr4lSUvHzLckSZLUYzbfWgLx4WMkj6mp1UhghlfDsV7UZd7hUiNnTECD8kYYkqTlxsy3RipJWVOS\nJGkSmPmWJEmSeszmW1JrzGVqUNaKhmG9qMtsviVJkqQxMfOtkTLzLUmSJoWZb0mSJKnHbL4ltcZc\npgZlrWgY1ou6zOZbkiRJGhMz3xopM9+SJGlSmPmWJEmSeszmW1JrzGVqUNaKhmG9qMtsviVJkqQx\nMfOtkTLzLUmSJoWZb0mSJKnHbL4ltcZcpgZlrWgY1ou6zOZbkiRJGhMz3xopM9+SJGlStJH53mmc\nb6blIRlrDU+Eqf2m2HjdxranIUmSWubKt0YqSTHT9iw6aAb8vfazZmdnmZ6ebnsamgDWioZhvWhQ\nXu1EkiRJ6jFXvjVSrnxvxYwr35IkdY0r35IkSVKP2Xz3XJL9krw3yZeSfDnJ6Un8oq06wWvxalDW\nioZhvajLbL77bz2wvqoOBA4Edgde0e6UJEmSlicz3z2W5NHAn1fV9KJ9uwPXAEcAZwA7M/+PsN8A\nfgp8oKoOao59AXCPqnpZko8DnwaOAvYEnlVV/7GF9zTzvSUzZr4lSeoaM98atQcDlyzeUVU3AV8D\n3gC8vqpjuC/8AAAgAElEQVTWAg8Hrls4ZBvn27Gqfgn4E7DFliRJGpbN9/L1ceClSf4UWFNVtwzw\nmvXNfy8BVi/ZzLRsmMvUoKwVDcN6UZf5xbt++xzwm4t3JNkD2B94DfB24NeADyV5LvBlYMdFh++y\n2fkWGvRb2VbtzGzPlHtqx+7d+XNqajVnnvlmgE03o1j4C2tc48svv7zV93fs2LFjx8trvLA9NzdH\nW8x891ySi4C/qaq3JdkR+Dvgu8DfVtU1zTGnAdcCfwtcD/wC8ENgFvjwosz3C6rq0iR7AZ+pqvtt\n4f1q28kVdUfMoUuSljUz31oKTwGOS/Il4AvMN9UvafZdleQy5rPh66rqp8DLgIuBjwCfX3Sezbs0\nuzZJkqQhufKtkXLle5K0v/I9Ozu76UeC0rZYKxqG9aJBufItSZIk9Zgr3xopV74nSfsr35IktcmV\nb0mSJKnHbL4ltWbxpZ+kbbFWNAzrRV1m8y1JkiSNiZlvjdR85luTYGpqNRs3zrU9DUmSWtNG5ts7\nXGrk/AedJEnSlhk7kdQac5kalLWiYVgv6jKbb0mSJGlMzHxrpJKUNSVJkiaB1/mWJEmSeszmW1Jr\nzGVqUNaKhmG9qMtsviVJkqQxMfOtkTLzLUmSJoWZb0mSJKnHbL4ltcZcpgZlrWgY1ou6zOZbkiRJ\nGhMz3xopM9+SJGlSmPmWJEmSeszmW1JrzGVqUNaKhmG9qMtsviVJkqQxMfOtkTLzLUmSJoWZb0mS\nJKnHbL4ltcZcpgZlrWgY1ou6bKe2J6D+Scb605uJMLXfFBuv29j2NCRJUsvMfGukkhQzbc+ig2bA\n32uSJHWLmW9JkiSpx2y+JbXGXKYGZa1oGNaLuszmW5IkSRoTM989lmQ/4I3Ag4AAHwBeVFU/HfD1\nJwAPr6rnDfGeZr63ZMbMtyRJXWPmW6O2HlhfVQcCBwK7A68Y8hx2jJIkSSNi891TSR4N3FxV6wCa\n207+CfDMJL+f5D1JPpzki0leteh1Jzb7LgQetWj/6iTnJbk8yUeT3Hfcn0n9Yy5Tg7JWNAzrRV1m\n891fDwYuWbyjqm4Cvsr89d0fAhwLHAz8VpL9kqwCZoBHAoczH1dZ8AbgjKo6BHhHM5YkSdIQvMnO\n8hPmoyTnVdX3AZJ8FlgN7A18vKpubPa/Eziged0jgac0228FXr3Vd5hZimlPuB3v2s2HVqyYYv36\nM5mengZuX83py3hhX1fm47i74+np6U7Nx3G3x9aL462NF7bn5uZoi1+47KkkjwH+vKqOXLRvD+Ar\nwP8HPKiqnt/sfz9wGrACeGpVndDsfx5wQFU9P8k3gX2r6tYkOwHXV9U+W3jfMiY+SvGLmpIkLRG/\ncKmRqarzgF2THA+QZEfgNcAZwM1bedmngSOSrEiyM/OxlAWfAn6n2T4eOH9JJq5lZfFKhLQt1oqG\nYb2oy2y+++0pwHFJvgR8Afgh8JItHFcAVbWR+dDIhcw3159bdMzzgROTXA48HThp6aYtSZLUT8ZO\nNFLGTkbN2IkkSUvF2IkkSZLUYzbfklpjLlODslY0DOtFXWbzLUmSJI2JmW+NlJnvUTPzLUnSUjHz\nLUmSJPWYzbeWQHyM6DE1tXrYX/yJYi5Tg7JWNAzrRV3m7eU1csYkJEmStszMt0YqSVlTkiRpEpj5\nliRJknrM5ltSa8xlalDWioZhvajLbL4lSZKkMTHzrZEy8y1JkiaFmW9JkiSpx2y+JbXGXKYGZa1o\nGNaLuszmW5IkSRoTM98aKTPfkiRpUpj5liRJknrM5ltSa8xlalDWioZhvajLbL4lSZKkMTHzrZEy\n8y1JkiaFmW9JkiSpx2y+JbXGXKYGZa1oGNaLuszmW5IkSRoTM98aKTPfkiRpUrSR+d5pnG+m5SEZ\naw23Ymq/KTZet7HtaUiSpAnjyrdGKkkx0/YsxmAG/L2z/WZnZ5menm57GpoA1oqGYb1oUF7tRJIk\nSeoxV741Uq58S5KkSeHKt0YqyX5J3pvkS0m+nOT0JOb8JUmSWmLz3W/rgfVVdSBwILA78Ip2pyTd\nzmvxalDWioZhvajLbL57KsmjgZurah1Ac/2/PwFOTLJLkrOSXJVkfZILk6xtXnfTonP8RpIzmu0z\nkvx1kv9I8p9JntrCx5IkSZpoRhD668HAJYt3VNVNSa4FXgR8u6r+nyQPBi5bfNhm51k8XlVVj0ry\ni8A5zK+sS3eZVyPQoKwVDcN6UZe58r08HQmcCVBVnwWuWPTctr508N7mNZ8H9lmy2UmSJPWUK9/9\n9TngNxfvSLI78HPANzc7dnHDvXile5fNjrtlK6+5o5lBpzjBdhzvzYSmplazcePcphzjwqrOpI9f\n//rXc8ghh3RmPo67O16c4e3CfBx3e2y9ON7aeGF7bm6OtnipwR5LchHwN1X1tiQ7An8HfBfYCDyg\nqv4gyYOAy4HDqurSJF8Cfh34MnAW8L2qemaT/X5/Va1vzn1TVe2+hfesn02uaPull5c2nPVGGBqQ\ntaJhWC8aVBuXGrT57rEk+zHfcD+Q+ZXqDwEvBHYG3gw8CPgCcH/g2Kq6OslvAK9ifnX8M8A9m+b7\nTcAHFjXf36uqPbbwnjbfS6KfzbckSW2y+dZYJNkB2Lmqbklyf+CjwC9U1U9HcG6b7yVh8y1J0qh5\nkx2Ny27AJ5NczvwVS35/FI23NKzFGTxpW6wVDcN6UZf5hctlqKq+Dxza9jwkSZKWG2MnGiljJ0vF\n2IkkSaNm7ESSJEnqMZtvSa0xl6lBWSsahvWiLjPzrSUw1p/eLAtTU6vbnoIkSRoBM98aqSRlTUmS\npElg5luSJEnqMZtvSa0xl6lBWSsahvWiLrP5liRJksbEzLdGysy3JEmaFGa+JUmSpB6z+ZbUGnOZ\nGpS1omFYL+oym29JkiRpTMx8a6TMfEuSpElh5luSJEnqMZtvSa0xl6lBWSsahvWiLrP5liRJksbE\nzLdGysy3JEmaFGa+JUmSpB6z+ZbUGnOZGpS1omFYL+oym29JkiRpTMx8a6TMfEuSpElh5luSJEnq\nMZtvjVySzj9W3XdV279MwlymBmetaBjWi7psp7YnoB6aaXsCd+6GmRvanoIkSVqGzHxrpJLUJDTf\nzIC1L0nS8mbmW5IkSeoxm29JrTGXqUFZKxqG9aIus/nuqSS3JTlt0fgFSf682f69JMe3NztJkqTl\nycx3TyW5GbgeOLSqbkzyAuAeVfWyEb7HjlV162b7zHxLkqSJYOZbo/RT4B+Akzd/IskpSU5utg9N\nsiHJpUleneTKZv8OzfjTSS5P8pxm/5FJ/j3J+4DPjvHzSJIkTTyb7/4q4I3A05Psvo3j3gQ8p6rW\nArc2rwN4FvDfVfVLwCOA5yZZ3Tz3UOB5VfXApZm6lgtzmRqUtaJhWC/qMpvvHquq7wNvAU7a0vNJ\n9gTuWVUXNbvesejpo4HfTXIZ8GlgJXBA89xFVfW1pZm1JElSf3mTnf77a+BS4IytPL+1nFOYX93+\n6B12JkcCP9jmO84MN8FW7Dif85KGsWLFFOvXn8n09DRw++qa46UfT09Pd2o+jrs9tl4cb228sD03\nN0db/MJlTyW5qap2b7ZfBfw28M9V9bIkpwA3VdXrklwBPKuqLk7yl8CvV9XBTcb7icCxVfXTJAcA\nXwcOBV5QVU/eyvvW7ckVqW/iF3UlqUf8wqVGaXGH8FpgL7bcFT8b+KcklwK7Ad9t9v8T8Dng0uZL\nmH8P7Lh009XyNNv2BDQhFq9aSXfGelGXGTvpqaraY9H2N4F7LhqfuujQz1bVQwCSvBj4THNMAS9t\nHot9onlIkiRpSMZOlrkkxwH/m/l/iM0Bz6iqb2/H+YydqMeMnUhSn7QRO7H51kjZfKvfbL4lqU/M\nfEtaZmbbnoAmhBleDcN6UZfZfEuSJEljYuxEI2XsRP1m7ESS+qSN2IlXO9ES8OY16qepqdVtT0GS\nNOFsvjVyrgxqULOzs5vuPiZti7WiYVgv6jIz35IkSdKYmPnWSCUpa0qSJE0CLzUoSZIk9ZjNt6TW\neC1eDcpa0TCsF3WZzbckSZI0Jma+NVJmviVJ0qQw8y1JkiT1mM23pNaYy9SgrBUNw3pRl9l8S5Ik\nSWNi5lsjZeZbkiRNCjPfkiRJUo/ZfEtqjblMDcpa0TCsF3WZzbckSZI0Jma+NVJmviVJ0qQw8y1J\nkiT1mM23pNaYy9SgrBUNw3pRl9l8S5IkSWNi5lsjlcSCGsLUflNsvG5j29OQJGlZaiPzbfOtkUpS\nzLQ9iwkyA/4elCSpHX7hUtKyYi5Tg7JWNAzrRV1m8y1JkiSNibETjZSxkyHNGDuRJKktxk6WoSS3\nJTlt0fgFSf68zTlJkiRpadh8t+8W4KlJVo7jzZKM9V930raYy9SgrBUNw3pRl9l8t++nwD8AJ2/+\nRJJfS3JhkkuS/FuSvZv9RyS5LMmlzXP3aB7nJvlMkg1JntwcuzrJF5K8JcmVwH2T/G2Si5JcmeSU\n5riHJ3lPs/0/kvwwyU5J7p7k6mb/s5vXXZbkXUl2GdOvkSRJUi+Y+W5Zku8B9wGuBA4Gngvco6pe\nlmTPqvpuc9yzgAdW1YuSnAO8sqouSLIb8KPmdLtV1feT7AVcWFUHJFkNXA08sqoubs51r6r67yQ7\nAOcBzwM+D3yxqn6+icEcAfwxsDPwe1X19CQrquo7zTn+AthYVW/c7POY+R7GjJlvSZLa0kbme6dx\nvpm2rGmY3wKcBNy86Kn9k5wF7Mt8E3xNs/8/gNOTvB1YX1VfT7IT8MokRwC3AfdJsk9z/FcXGu/G\nbyd5DvP//1cBD6qqq5JcneSBwCOA1wFHAjsC5zevO7hpuu8F3AP4yBY/0Mxd/ZVYflbcewWzs7NM\nT08Dt/+o1LFjx44dO3Y8+vHC9tzcHG1x5btlSb5XVXskWQFcCpwB0Kx8fxx4TVV9MMmRwClV9ejm\ndQ8GngT8AXA08Ejg8cDTq+q2JNcw3zwHeH9VHdy8bg3wUeBhVfW9JGcAH6+qdUleCvwQeCLw28Bb\nmI8mvaiqPpvkK8CTm0b9BODIqnrmZp+nwJqCuKI9gNlF//CQtsVa0TCsFw3Kq50sTwFo4hxnAc9a\n9NwewPXN9gmbXpDcv6o+W1WvBi4GHgjsCXyzabyPAlZv/h6Lzvl94KYkU8ATFj33SeajJp+qqm8D\newG/UFWfbZ6/J7Axyc7A07fjM0uSJC1Lxk7at3h59LXAHy7adyrw7iQ3Ah8D1jT7/7hpsG8FPgt8\nmPmm+v1JNgCfYT7D/TPvUVVXJLm8ef5a5hvuBZ8G9gH+vRlf0YwX/BlwEfDN5tjdh/+40u1cmdKg\nrBUNw3pRlxk70UgZO1lg7ESSpK4zdiJpWVn8BRhpW6wVDcN6UZfZfEuSJEljYuxEI2XsZIGxE0mS\nus7YiSRJktRjNt+SWmMuU4OyVjQM60Vd5qUGtQTG+tObTpqaWn3nB0mSpGXHzLdGKklZU5IkaRKY\n+ZYkSZJ6zOZbUmvMZWpQ1oqGYb2oy2y+JUmSpDEx862RMvMtSZImhZlvSZIkqcdsviW1xlymBmWt\naBjWi7rM5luSJEkaEzPfGikz35IkaVKY+ZYkSZJ6zOZbUmvMZWpQ1oqGYb2oy2y+JUmSpDEx862R\nMvMtSZImhZlvSZIkqcdsviW1xlymBmWtaBjWi7rM5luSJEkaEzPfGikz35IkaVKY+ZYkSZJ6bKe2\nJ6D+Scb6D0hpZKb2m2LjdRvbnoa2YHZ2lunp6banoQlhvajLbL41ejNtT0AT4xrgfm1P4nY3zNzQ\n9hQkST1n5lsjlaRsvjWxZsA/EyVp+TDzLUmSJPWYzXfPJLmp7TlIA7um7QloUnjdZg3DelGX2Xz3\njz8zlyRJ6iib72Ugya8luTDJJUn+Lcnezf57N+Mrk/xjkrkkK5vnTm72X5HkpGbfbkk+kOSyZv+x\nbX4u9UCHvmypbvPKFRqG9aIus/leHs6vqsOq6mHAO4E/bfafApxXVQcB7wb2B0iyFjgBOBR4JPCc\nJA8BHg98vaoeWlUHA/865s8hSZI00Wy+l4f9k3wkyRXAC4EHN/sPB84EqKqPAN9ZtP/sqvpRVf0A\nWA/8CnAl8Lgkr0xyeFWZL9f2MfOtAZnh1TCsF3WZ1/leHt4AvKaqPpjkSOZXvLdkm5faqaovN6vi\nTwRenuTcqnr5zxw4s52zldqyw+TdJGrFiiluvHH+xkALDcfCj9wdO3bs2PEdxwvbc3NztMXrfPdM\nkpuqavfN9l0CPLuqLkvyJmBNVT06yf8BvlZVr05yNPBhYG9gNXAGcBiwI3AhcDzwTeDGqrolyZOA\nZ1XVUzd7r/I7n9I4xWuTS9Jd1MZ1vl357p9dk3yN+VXsAl7H/Fr0u5PcCHwMWNMceyrwjiTHAxcA\nG4Gbmib9zcDFzTn+oao2NA36aUluA34M/P7YPpUkSVIPuPK9jCW5G3BrVd2a5DDgb6tq7Xae05Vv\nDWEWmG55DpNueax8z87ObvrxsXRnrBcNypVvjdvPAWcl2QG4BXhOy/ORJEnqNVe+NVKufEvjtjxW\nviVpKbSx8u2lBiVJkqQxsfmW1KLZtiegCbH4MmHSnbFe1GU235IkSdKYmPnWSJn5lsbNzLck3VVe\n7UQ9MVl3CJQm2dTU6ranIEkags23Rs5VOA3Ka/FqUNaKhmG9qMvMfEuSJEljYuZbI5WkrClJkjQJ\nvM63JEmS1GM235Ja47V4NShrRcOwXtRlNt+SJEnSmJj51kiZ+ZYkSZPCzLckSZLUYzbfklpjLlOD\nslY0DOtFXWbzLUmSJI2JmW+NlJlvSZI0Kcx8S5IkST1m8y2pNeYyNShrRcOwXtRlNt+SJEnSmJj5\n1kiZ+ZYkSZPCzLckSZLUYzbfklpjLlODslY0DOtFXbZT2xNQ/yRj/enNnZrab4qN121sexqSJElm\nvjVaSYqZtmexmRmwziVJ0ubMfEuSJEk9ZvMtqTXmMjUoa0XDsF7UZTbfkiRJ0piY+e6JJDdV1e7N\n9hOB1wGPq6prxzwPM9+SJGkimPnW9iiAJI8BXg88flSNd5IdR3EeSZKk5c7muz+S5FeA/ws8qarm\nkuyQ5CvNk/dK8tMkhzfjTyR5QJJDk3wqySVJPpnkgOb5E5K8L8l5wLlJ7pHk3CSfSbIhyZNb+6Tq\nDXOZGpS1omFYL+oyr/PdH3cHzgamq+rLAFV1W5IvJPlF4P7AJcCvJLkIuG9VXZ3kBuDw5tjHAK8E\nfrM550OBg6rqu0l2AI6pqu8n2Qu4EDhnvB9RkiRpstl898dPgE8Bzwb+eNH+84Ejgfsx31g/F/h3\n4OLm+XsB65oV7+KONfHRqvpus70D8MokRwC3AfdJsk9VfXOJPo+Wgenp6banoAlhrWgY1ou6zOa7\nP24FjgM+luR/V9Urm/3nA78P7Av8GfCnwHSzH+AvgI9V1VOTrAY+vuicP1i0/XTg3sBDm1Xya4Bd\ntjiTmVF8nBHaoXt33RzUihVTrF9/5qa/SBZ+lOrYsWPHjh07Hn68sD03N0dbvNpJTyxc7STJCuZX\ntk+vqjcluRvwReDqqnpskr8Ffo35XPiVSd4DvK2qzk4yA/xuVd0/yQnAw6rq+c35nw88oKpOSnIU\ncB6wpqq+ttk8qvnup0Yivb5Sy+zs7KY/GKVtsVY0DOtFg/JqJ9oeBVBV3wGeALw0ya9V1Y+BrwEX\nNMedD9yzqq5sxqcBf5XkErZdD28HDk2yATge+PwSfAZJkqRec+VbI+XK96j1e+VbkqQ2ufItSZIk\n9ZjNt6TWLP4CjLQt1oqGYb2oy2y+JUmSpDEx862RMvM9ama+JUlaKma+JUmSpB6z+dYSiI8RPaam\nVg/7iz9RzGVqUNaKhmG9qMu8w6VGzpiEJEnSlpn51kglKWtKkiRNAjPfkiRJUo/ZfEtqjblMDcpa\n0TCsF3WZzbckSZI0Jma+NVJmviVJ0qQw8y1JkiT1mM23pNaYy9SgrBUNw3pRl9l8S5IkSWNi5lsj\nZeZbkiRNCjPfkiRJUo/ZfEtqjblMDcpa0TCsF3WZzbckSZI0Jma+NVJmviVJ0qQw8y1JkiT1mM23\npNaYy9SgrBUNw3pRl9l8S5IkSWNi5lsjZeZbkiRNijYy3zuN8820PCRjreG7ZGq/KTZet7HtaUiS\npGXGlW+NVJJipu1ZDGAGrP32zc7OMj093fY0NAGsFQ3DetGgvNqJJEmS1GOufGukXPmWJEmTwpVv\nSZIkqcdsvpeRJDct2n5iki8k2f8unGffJGeNdnZajrwWrwZlrWgY1ou6zKudLC8FkOQxwOuBo6vq\n2qFPUvUN4LgRz02SJKn3zHwvI83K9xOBM4AnVNWXm/2rgTcBewHfAk6squuS3B94O7AbcA7wx1W1\ne3P8B6rqoC28h5lvSZI0Ecx8a6ndHTgbOGah8W68ATijqg4B3tGMAf4aOL2qHgJcR7Ny3rBzlSRJ\nGpIr38tIkh8A5wFfqao/XrT/W8Cqqro1yU7A9VW1T5L/AvapqtuS7M7/z969h8lWlmf+/94CChq2\n4ql10GzFY1QUwQNGzO7IxAmKeIgYNSZqPM2YEY0YfxMnhtZkxBhjSDRGkhjQMYKHeAiSKCbSguIB\nN5uTUX8e6CjGDUSNEI2K+MwfvRrKbXfvVVBda9Xq7+e6+ur1rlq16q3iAZ5+665V8LWq2tKsfJ9W\nVfdd5TFmo6D2AK7p7uHn5rayc+fStbnElevRbrbxCSecwEEHHdSb+Tju73g0w9uH+Tju99h6cbzW\neGV7aWkJgDe/+c1TX/m2+d5EklwJ3Bb4MMvN8/HN/suB2++m+d4CXNqu+bamdi/GXvCLMNSetaJx\nWC9qy9iJNlqq6nvAo4CnJHlGs/8c4MnN9lOBs5vtjwNPaLaftOu5NnKi2hz8n6PaslY0DutFfebV\nTjaXAqiqbyU5AvhIEzl5PnBykhfTfOCyOf43gbcmeSnwQeDbu55LkiRJ7bnyvYlU1ZaR7Uur6i5V\n9f6q+mpVHV5VB1XVL1TVpc1hX6uqQ5sPYp4HfLq577+sFjmRxjWawZPWY61oHNaL+syVb63nkCSv\nZzli8i3g1zuejyRJ0kzzA5eaKD9w2ZYfuJQkqWt+4FKSJEkaMJtvSZ0xl6m2rBWNw3pRn9l8S5Ik\nSVNi5lsTNTPfcNmxlW+4lCRJ3eki8+3VTjRx/kEnSZK0OmMnkjpjLlNtWSsah/WiPrP5liRJkqbE\nzLcmKklZU5IkaRZ4nW9JkiRpwGy+JXXGXKbaslY0DutFfWbzLUmSJE2JmW9NlJlvSZI0K8x8S5Ik\nSQNm8y2pM+Yy1Za1onFYL+ozm29JkiRpSsx8a6LMfEuSpFlh5luSJEkaMJtvSZ0xl6m2rBWNw3pR\nn9l8S5IkSVNi5lsTZeZbkiTNCjPfkiRJ0oDZfEvqjLlMtWWtaBzWi/psz64noOFJpvfuzdz+c+y8\ndOfUHk+SJOmGMPOtiUpSLEzxARfAGpYkSdeHmW9JkiRpwGy+JXXGXKbaslY0DutFfWbzLUmSJE2J\nzfcAJblqZPuRST6X5I7rHH9ckhetsn9bktPWuM/7k2yZzIy1Wc3Pz3c9Bc0Ia0XjsF7UZ17tZJgK\nIMnhwAnAI6rqqzfkXD+xs+rI63k+SZKkTcuV72FKkocBJwKPqqqlZuetk7wrySebn4eM3OegJOck\n+XySZ43sv3mzyv25JG8YeYBLktxyKs9Gg2UuU21ZKxqH9aI+c+V7mG4CvAeYr6ovjOz/E+C1VXVO\nE0P5IHCv5rYDgQcD+wI7kry/2f9A4GeArwAfTPL4qno3a6yIS5IkaW0238N0NXAO8CzghSP7/yvw\nM7nuW3B+KslNm+33VdUPgG8k+TDwIODbwKeq6l8AkpwCHAa8G1j7mpgLk3siu3Wj6X6pj/ppbm4r\nO3cuXbvatZL3dDyc8fz8fK/m47jfY+vF8Vrjle2lpSW64pfsDFCSK4HbAh8GTquq45v9lwP7V9XV\nuxx/HEBVvbwZvxl4F3Al8PKqmm/2PwO4T1Udm+QS4JCq+uYu5yoXxTV98cuWJElj80t2NCmpqu8B\njwKe0jTNAGcAL7j2oOR+I/d5TJIbJ7kVsA04t9n/oCRbk9wI+GXg7I2fvjaPxa4noBkxumol7Y71\noj4zdjJMBVBV30pyBPCRJFcAxwBvSHIBsAdwFvC85j4XstwJ3Qp4RVXtTHIP4FPA64G7Ah+uqveO\nPoYkSZLaM3aiiTJ2om4YO5Ekjc/YiSRJkjRgNt+SOrTY9QQ0I8zwahzWi/rM5luSJEmaEjPfmigz\n3+qGmW9J0vjMfEuSJEkDZvOtDRB//Jnqz9zcVjRsZng1DutFfeZ1vjVxvv2vthYXF6/96l9JkjYD\nM9+aqCRlTUmSpFlg5luSJEkaMJtvSZ0xl6m2rBWNw3pRn9l8S5IkSVNi5lsTZeZbkiTNCjPfkiRJ\n0oDZfEvqjLlMtWWtaBzWi/rM5luSJEmaEjPfmigz35IkaVaY+ZYkSZIGzOZbUmfMZaota0XjsF7U\nZzbfkiRJ0pSY+dZEmfmWJEmzwsy3JEmSNGA235I6Yy5TbVkrGof1oj6z+ZYkSZKmxMy3JirJVAtq\nbv85dl66c5oPKUmSBqKLzLfNtyYqSbEwxQdcAGtYkiRdH37gUtKmYi5TbVkrGof1oj6z+ZYkSZKm\nxNiJJsrYiSRJmhXGTrRbSa4a2X5kks8lueM6x29L8pDdnPOQJCdMcp6SJEn6STbfs6cAkhwOnAD8\nYlV9dZ3j54GfXfeEVdur6oUTm6HUkrlMtWWtaBzWi/rM5nv2JMnDgBOBR1XVUrPzyCSfSLI9yRlJ\nbpNkK/DfgRcmOS/JQ5M8IclFSXYkWWzuuy3Jac32cUnelOTMJF9M8vyRB35PknOb+z9r2k9ckiRp\n1pn5njFJfgBcCcxX1cUj+29eVd9utp8J3LOqfivJccBVVfXa5rYLgf9WVV9PsqWqrkyyDTi2qo5q\njvlfO+0AACAASURBVP8FllfMbw58HpirqmuS3KKq/j3J3sC5wM9V1bd2mZ+Zb0mSNBPMfKuNq4Fz\ngF1Xnu+Y5INNc/1i4N5r3P+jwJubles91zjm9Kr6YVV9A7gMmGv2vzDJ+cAngDsAd7sBz0OSJGnT\nWav5Un9dAzwR+HCS366q45v9rwNeU1WnNyvZx61256p6XpIHAkcC25McvMph3x/Z/hGwZ3POhwMP\nrqrvJzkT2HvVGS5cj2d1fd1o+a9WSdLGmZvbyqmnngzA/Pw8cF2uuo/j0cx3H+bjuD/jle2lpSW6\nYuxkxiS5qqr2TbIfcBbw2qo6Kcl24FlVtSPJXwN3qqqHJ3kRsKWqFpr7H1BVX262Pwk8G9iPH4+d\njMZULgIeBRwEPLOqHpPknsAOluMrZ+0yv2o+Eyq1sMhywknanUWslS5lpiJ+i4uL1zZd0nqMnaiN\nAmiy1kcAv5PkSJbXm9+V5FzgipHjTwMet/KBS+APk1zYxFM+VlUXtnk84APAXkk+A7wS+PjEnpE2\nsfmuJ6CZMd/1BDRDbLzVZ658a6Jc+ZakIZqtlW+pLVe+JW0yi11PQDNjsesJaIZ4nW/1mc23JEmS\nNCXGTjRRxk4kaYiMnWiYjJ1IkiRJA2bzLalDi11PQDNjsesJaIaY+Vaf+SU72gB+6Y0kDcnc3Nau\npyANhplvTVSSsqYkSdIsMPMtSZIkDZjNt6TOmMtUW9aKxmG9qM9sviVJkqQpMfOtiTLzLUmSZoWZ\nb0mSJGnAbL4ldcZcptqyVjQO60V9ZvMtSZIkTYmZb02UmW9JkjQrzHxLkiRJA2bzLakz5jLVlrWi\ncVgv6jObb0mSJGlKzHxrosx8S5KkWWHmW5IkSRowm29JnTGXqbasFY3DelGf2XxLkiRJU2LmWxNl\n5luSJM0KM9+SJEnSgNl8a+KSbJqf293hdl2/3DPNXKbaslY0DutFfbZn1xPQAC10PYHpuWzhsq6n\nIEmSZoiZb01UktpMzTcL4L9DkiTNJjPfkiRJ0oDZfEvqjLlMtWWtaBzWi/rM5nvgklw1sv3IJJ9L\ncscu5yRJkrRZmfkeuCRXVtWWJIcDfw48oqqWNvDxzHxLkqSZYOZbGyFJHgacCDxqpfFOcmSSTyTZ\nnuSMJLdp9h+X5E1JzkzyxSTPHznRi5JclOTCJC/o5NlIkiTNMJvv4bsJ8B7gsVX1hZH9Z1fVoVV1\nCPB24CUjt90D+AXgwcBxSfZIcgjwNOCBwEOAZye531SegQbLXKbaslY0DutFfWbzPXxXA+cAz9pl\n/x2TfDDJhcCLgXuP3HZ6Vf2wqr4BXAbMAQ8F3lNV36uq7wDvBh628dOXJEkaDr9kZ/iuAZ4IfDjJ\nb1fV8c3+1wGvqarTk2wDjhu5z/d3uf94dbJw/Sc7c260nBeTJEmTMTe3lVNPPRmA+fl54Lp3M27o\neGV7aWlp4vNuyw9cDlySq6pq3yT7AWcBr62qk5JsB55VVTuS/DVwp6p6eJLjgKuq6rXN/S8CHgXc\nCjgJOBTYA/gE8NSqumCXxyuwpiRJ0vWVqV3MwA9caiMUQFV9CzgC+J0kR7K8Pv2uJOcCV7S4/w7g\nZOBc4OPAX+zaeEvjW+x6ApoZi11PQDNlsesJSGty5VsT5cq3xrMIzHc8B82GRawVtbeI9TLLhr3y\nbfOtibL5liRJN8ywm29jJ5IkSdKU2HxL6tBi1xPQzFjsegKaKYtdT0Bak823JEmSNCVmvjVRZr4l\nSdINM+zMt1+yow3gl85IkqTrZ25ua9dT2FA235o4301RW4uLi9d++5i0HmtF47Be1GdmviVJkqQp\nMfOtiUpS1pQkSZoFXudbkiRJGjCbb0mdWVxc7HoKmhHWisZhvajPbL4lSZKkKTHzrYky8y1JkmaF\nmW9JkiRpwGy+JXXGXKbaslY0DutFfWbzLUmSJE2JmW9NlJlvSZI0K8x8S5IkSQNm8y2pM+Yy1Za1\nonFYL+ozm29JkiRpSsx8a6LMfEuSpFlh5luSJEkaMJtvSZ0xl6m2rBWNw3pRn7VqvpPcNMnLkvxl\nM75bkiM3dmqSJEnSsLTKfCd5O7Ad+LWquk+SmwLnVNVBGz1BzZYkBr61qrn959h56c6upyFJ0rW6\nyHzv2fK4u1TVLyd5MkBVfTfJVCeqGbLQ9QTUR5ctXNb1FCRJ6lzbzPcPkuwDFECSuwDf37BZSdoU\nzGWqLWtF47Be1GdtV74XgA8Ad0zyN8BDgWds1KQkSZKkIWp9ne8ktwIOBQJ8oqr+bSMnptmUpIyd\naFUL4DXgJUl90tvrfCf5p6r6RlWdXlXvr6p/S/JPGz05/bgkV41sPzLJ55LccYz7X5LklhszO0mS\nJO3Ous13kr2bZu3WSfZLcsvm507A/tOYoH7MSub+cOAE4Ber6qvj3l/qC3OZasta0TisF/XZ7la+\nn8vyJQbv2fxe+Xkf8PqNnZpWkSQPA04EHlVVS83OI5N8Isn2JGckuU2z/5ZJPpjkouYa7Wn2b01y\n0chJj03yu832mUleleSTzcr6Q0fuc1aSTzc/h073qUuSJM2+ttf5fn5VvW4K89E6kvwAuBKYr6qL\nR/bfvKq+3Ww/E7hnVf1Wkj8Brqiq30/ySOA04DbAvsBpVXXf5j7HAjerqlckORP4dHP/I4AXVdUv\nJNkb+FFV/SDJXYFTquqBq8zRzLdWt2DmW5LUL729zndVvS7JfYB7AXuP7H/LRk1Mq7oaOAd4FvDC\nkf13TPIO4PbAXsAlzf6fAx4HUFV/n+RbLR/n3c3v7cDWZvvGwOuTHARcA9xtzXsvtHwUbS57LP9H\nThqCubmtnHrqyQDMz88D10UdHDt23N/xyvbS0hJdabvyfRwwz3Lz/ffAEcBHq+oJGzo7/ZgkVwK3\nBT7M8sr18c3+M4HXVNXpSbYBx1XVw5PsAB43Ek/5BstN8z7AGVV172b//wb2GFn5PraqzmuucHNu\nVR3Q1MDNquolSfYA/rOqbrzKHMtoudpbZPk/LdLuLNKvWonv5PTY4uLitU2XtJ7eXu0EeAJwOLCz\nqp4B3A+4+YbNSmtJVX0PeBTwlCQr11rfAvxrs/20kePPAn4FoImQ3KLZfxlwm+ZDtDcBjmzx2DcH\nvt5s/xqwx/V+FpIkSZtU2+b7P6vqR8APk2wBLgdaX+JOE1MAVfUtlt99+J0kR7Ic9HhXknOBK0aO\nfznwc82HKx8LfKW5/w+BVwDnAh8EPrvrY6ziDcDTm9X0uwPfmdBz0qY23/UENDPmu56AZoir3uqz\ntrGTNwAvBZ4EHAv8B3B+swouXcvYiaTNwdiJNARdxE5af8PltXdYvsb3lqq6cCMmpNlm863xLOKK\nptpZpF+1YvPdZ2a+1VZvM9+j32ZZVUtVdaHfcClJkiSNZ92V7+bazjcFzmR5yWHlL4MtwAeq6p4b\nPUHNFle+JW0OrnxLQ9DH63w/l+XrSf8Xlq/5vOIq/IZLSZIkaSy7i52cA/ws8OKqOoDlq2dcDHwE\neNsGz03S4C12PQHNjMWuJ6AZMvqFKlLf7G7l+0TgvzbfcPlzwPHA84GDgL9g+frf0i78FkNJwzY3\nt3X3B0nSKnaX+b6gqu7XbP8ZcEVVLTTj86vqoKnMUjMjSZmDlCRJs6CPVzvZI8nK6vjhLH+t+Yrd\nrZpLkiRJGrG75vsU4CNJ3gf8J3A2QJK7At/e4LlJGjhzmWrLWtE4rBf12bqr11X1f5rred8eOGMk\nT3AjlrPfkiRJkloa+xsupfWY+ZYkSbOij5lvSZIkSRNi8y2pM+Yy1Za1onFYL+ozm29JkiRpSsx8\na6LMfEuSpFlh5luSJEkaMJtvSZ0xl6m2rBWNw3pRn9l8S5IkSVNi5lsTZeZbkiTNCjPfkiRJ0oDZ\nfEvqjLlMtWWtaBzWi/rM5luSJEmaEjPfmigz35IkaVaY+ZYkSZIGzOZbE5ektz+3u8Ptun55NMJc\nptqyVjQO60V9tmfXE9AALXQ9gbVdtnBZ11OQJEmbmJlvTVSS6nPzzQJY85IkCcx8S5IkSYNm8z0A\nSa5Kcrsk7+h6LtI4zGWqLWtF47Be1Gdmvoehqmon8MSuJyJJkqS1ufI9EEm2Jrmo2d4nyduTXJzk\n3Uk+keTg5rY3JPlUkouSHNfse0CSv222H5Pku0n2THKTJF9q9j+rud+OJO9MsndXz1XDMT8/3/UU\nNCOsFY3DelGf2XwPRzU/AM8DvllV9wFeBhw8ctxLq+pBwP2A+ST3AXY0Y4DDgIuABwIPBj7R7P/b\nqnpQVd0f+BzwzI18MpIkSUNk8z1MhwGnAlTVZ4ALR257UpLtLDfc9wLuVVXXAF9Kck/gQcBrgW3A\nw4Czm/vdN8lZSS4EngLceyrPRINmLlNtWSsah/WiPjPzvTkEIMmdgGOBQ6rqyiQnASvxkbOAI4Af\nAP8IvJnlP85+q7n9JOCoqro4ydNYbs5XtzDx+U/OjZYvKyRpPHNzWzn11JOB697SX2lwHDt27HhW\nxivbS0tLdMXrfA9AkiuBA4H3V9WBSV4MHFBVz0tyL5ZXuR8C/JDlpvpg4LbABcBLquotSbYBbwFO\nrqrjknwcuG1V3aV5jMtZXin/NnA6cGlV/foqc6nr0i+ShiNeI1/S4HRxnW9Xvmdckj2A7/Pjme83\nACcnuZjlfPZngG9X1ZeSnA98Fvgq8NGRU32S5Yb8rGZ8YTNe8TLgU8DlzbH7bsgTkiRJGjBXvmdc\nkvsBJ1bVoSP7bgTsVVXfT3IA8CHgHlX1wynMx5VvjWERmO94Dmqn25XvxcXFa98+lnbHelFbrnxr\nLEmeCzwfeMEuN90UODPJXs34f0yj8ZYkSdL6XPnWRLnyLQ2VmW9Jw9PFyreXGpQkSZKmxOZbUocW\nu56AZsToZcKk3bFe1Gc235IkSdKUmPnWRC1nviUNzdzcVnbuXOp6GpI0UV7tRIPgH3SSJEmrM3Yi\nqTPmMtWWtaJxWC/qM5tvSZIkaUrMfGuikpQ1JUmSZoHX+ZYkSZIGzOZbUmfMZaota0XjsF7UZzbf\nkiRJ0pSY+dZEmfmWJEmzwsy3JEmSNGA235I6Yy5TbVkrGof1oj6z+ZYkSZKmxMy3JsrMtyRJmhVm\nviVJkqQBs/mW1BlzmWrLWtE4rBf1mc23JEmSNCVmvjVRZr4lSdKsMPMtSZIkDZjNt6TOmMtUW9aK\nxmG9qM/27HoCGp5kqu/eaBOb23+OnZfu7HoakiS1ZuZbE5WkWOh6Fto0FsD/hkmSri8z35IkSdKA\n2XxL6s4lXU9As8IMr8ZhvajPbL4lSZKkKTHzvYkluaqq9p3wOc18a3oWzHxLkq4/M9+aNrsWSZKk\nKbL5Fkm2JVlM8t4kX0xyfJKnJPlkkguS3Lk5bmuSf0pyfpIPJblD13PXjDPzrZbM8Goc1ov6zOZb\nK+4LPAe4F/CrwN2q6sHAm4DnN8e8Djipqg4C3taMJUmS1JLNt1acW1WXV9UPgC8BZzT7LwLu1Gw/\nBDil2f6/wGFTnaGG585dT0CzYn5+vuspaIZYL+ozv+FSK74/sv2jkfGPuK5Ods2Ir54ZX5jktKS1\n7Xfr/VhcXLz2f7QrbzU7duzYsWPHq41XtpeWluiKVzvZxFaudpJkG3BsVR3V7D+zGZ83eluS9wLv\nqqq3Jnk68Oiq+qVdzln9+xxnvCJGTy2ONM7SeqwVjcN6UVtdXO3Ele/Nba2OdK39xwAnJXkxcAXw\njA2ZlSRJ0kC58q2JcuVbkiTNCq/zLUmSJA2Yzbekzox+AEZaj7WicVgv6jObb0mSJGlKzHxrosx8\nS5KkWWHmW5IkSRowm29tgPTqZ25u6wY/X11f5jLVlrWicVgv6jOv862JM+IhSZK0OjPfmqgkZU1J\nkqRZYOZbkiRJGjCbb0mdMZeptqwVjcN6UZ/ZfEuSJElTYuZbE2XmW5IkzQoz35IkSdKA2XxL6oy5\nTLVlrWgc1ov6zOZbkiRJmhIz35ooM9+SJGlWmPmWJEmSBszmW1JnzGWqLWtF47Be1Gc235IkSdKU\nmPnWRJn5liRJs8LMtyRJkjRgNt+SOmMuU21ZKxqH9aI+s/mWJEmSpsTMtybKzLckSZoVXWS+95zm\ng2lzSKZTw3P7z7Hz0p1TeSxJkqRJcOVbE5WkWJjSgy2A9TvbFhcXmZ+f73oamgHWisZhvagtr3Yi\nSZIkDZgr35ooV74lSdKscOVbkiRJGjCb7xmV5LZJ/ibJF5Ocm+RjSR4zgfOemeTgScxR2h2vxau2\nrBWNw3pRn9l8z673AotVddeqeiDwJOAOHc9JkiRJ6zDzPYOSPBx4WVX9/Cq33QT4c+ABwNXAsVW1\nmORpwGOBmwF3Bf4IuDHwq8D3gEdW1b8nORO4ANgG7AE8s6rOTXJT4HXAvYG9gIWqOm2VxzfzLUmS\nZoKZb7V1b+C8NW77DeBHVXVf4CnAm5PceOR+jwUeBPwf4D+q6mDgE8CvjZxjn6q6f3Ouv272/W/g\nn6rqUODhwGuS7DPB5yRJkjR4fsnOACR5PXAY8APgqyyvUFNVn0+yBNy9OfTMqvou8N0k/w68v9l/\nEXDgyClPae5/dpJ9k2wBHgE8OslvNcfcGPhp4PM/MaGFiT219e0xvS/0mWX77TfHN7+5/GVEKznI\nlevfdj0+4YQTOOigg3ozH8f9HY9mePswH8f9Hlsvjtcar2wvLS3RFWMnM6iJnfxuVc2P7LslsJ3l\nFfHXVdVis/8s4HnAIcAhVXVMs/+SZvzNJpJySFUd08ROFqrqI81xSyw35mcCT66qL+xmbgXWVL+k\nt/GcRb8IQy1ZKxqH9aK2jJ2olar6MHCTJM8d2f1TLHe9ZwNPBUhyd+COrLY6vb5fbu5/GPDtqroK\n+CBwzMoBSQ663k9Aavg/R7VlrWgc1ov6zNjJ7HoscEKSlwBXAN8BXgL8HfDGJBey/IHLp1XV1avE\nM9ZaCi3ge0nOY7k+ntHs/73m8S4EAlwCHDXB5yNJkjR4xk40UcZO+sjYiWaftaJxWC9qy9iJJEmS\nNGCufGuiXPnuo/6ufEuS1CVXviVJkqQBs/mW1JnR665K67FWNA7rRX1m8y1JkiRNiZlvTdRy5lt9\nMje3lZ07l7qehiRJvdNF5tvrfGvi/INOkiRpdcZOJHXGXKbaslY0DutFfWbzLUmSJE2JmW9NVJKy\npiRJ0izwOt+SJEnSgNl8S+qMuUy1Za1oHNaL+szmW5IkSZoSM9+aKDPfkiRpVpj5liRJkgbM5ltS\nZ8xlqi1rReOwXtRnNt+SJEnSlJj51kSZ+ZYkSbPCzLckSZI0YDbfkjpjLlNtWSsah/WiPrP5liRJ\nkqbEzLcmysy3JEmaFWa+JUmSpAGz+ZbUGXOZasta0TisF/XZnl1PQMOTTPXdmxtkbv85dl66s+tp\nSJKkTcLMtyYqSbHQ9SzGsAD+OyBJ0uZk5luSJEkaMJtvSZ0xl6m2rBWNw3pRn9l8S5IkSVOyoc13\nkmuSnJdkR/P7p8e470lJHj+heTwtyevWuO2IJOcmuTjJ9iR/eD0f4/ZJ3tFs3y/JES3usy3Jabvs\ne0Tzeu1IclWSzzWv3cnXZ14j5/2HJDdLsl+S596Qc0mTMj8/3/UUNCOsFY3DelGfbfTVTr5TVQdv\n8GMAkGSPqrpmnUN+4lN1Se4DvA44oqq+kOXLdDzn+jx+VX0deGIzPAh4APAPbe66y3nOAM5o5vdh\n4Niq2tF2Hqu9Dln+5psjmu3bA/8dOPGGnFOSJEnj2+jYyU98ejTJjZK8Osknk5yf5Nkjt70+yWeT\nnAHcdmT/wUkWmxXqf0gy1+w/M8kfJ/kUcEySI5N8olnBPiPJbXYzv98Cfr+qvgBQy05szr3quZIc\nl+QtSc5J8vkkz2r2b01yUZI9gVcAT2xWrI9O8sDm+O1JPprkbmO8fte+hkn2SPJHzbzOT/Lrzf7D\nm9fiNODCJHdJ8pkkb01yMXD7JF9NsgU4Hrh7M7dXZtlrm7lfkOSX1jjn7yf5jZG5vCrJ/2j5PKRV\nmctUW9aKxmG9qM82euV7nyTnsdxAfrmqfgl4JvDvVfXgJDcGPtY02wcDd6uqn2lWZ/8ZeFPTzL4O\nOKqqvpHkicArm/MA7FVVDwJIcvOqOrTZfibw/wEvXmd+9wFes8ZtZ+9yrpew3KwDHAg8GNgX2JHk\n/c3+qqofJvld4JCqOqa5/08Bh1XVj5IcznID/IQ2L+AungNcVlWHNq/dJ5rXDuAQ4Geq6mtJ7gLc\nA3jqyqp5kpUV9v8F3GXlHYnm9bxHVR3Y/FFzbpKPrHHOU4A/S3Ij4GiW/5lJkiSppY1uvr+7Suzk\nEcCBSY5uxluAuwE/x3JzR1V9vYlcwHITeR/gQ00s5EbAv46c7+0j23dscte3B/YCLrkBc1/vXO+r\nqh8A32jm+SDggnXOdQvgLc2Kd3H9X/dHAPdM8uRmvPLaAXy8qr42cuyXdomrrHUNy8O47nW/LMnZ\nLEdmrh49Z1V9KcmVSe4N3An4ZFV9e9UzLoz7tLqz3633Y3Fx8dp84MpqiePpjFf29WU+jvs7np+f\n79V8HPd7bL04Xmu8sr20tERXNvRLdpJcWVVbdtn3LuDEqvrQLvv/GLigqk5uxn8L/A3w/zfHP3SV\n85/Jcib6vJHxa6rq9CTbgOOq6uFJnsbISvTI/d8MLFbVSWuce7VzHQdQVS8fOce7gAuB06rqvrs+\nXpKTgO1V9fokW4Ezq+qA5rzHVtVRa7x+uz6/9wJ/UlVn7nLc4cBvVNXjm/FdgHeO/uGT5Css/xFz\nm9Hbkvwp8KmqemszfhvwFpab72vP2dz2ZJZXw+8EvLGq/nGVOdcq8fqeiV+sI0mSBvklO6s9mQ8C\nz2viJCS5W5KbAmcBv5zlTPjtgZ9vjv88cJskKxGQPZPca43H28J1q+JPazG/1wC/vZLBbh575Uog\n653rMUlunORWwDbg3F1uv6q5/+i8Vlaln9FiXmv5IPAbSfZo5nv3JHuvceyur/3K+CqW4zIrzgae\n1GS/54CfBT69xjnfDTwauN9qjbc0rtGVCGk91orGYb2ozza6+V5tefGvWM5zn5fkIuCNwB5V9R7g\ni8BngJOBcwCq6mqW89F/kOR8YAfwkDXO/3LgXUnOBa7Y7eSqLgJeCJyS5DMsr17fucW5LgQWmzm+\noqp27nL7mcC9Vj5wCbwaeFWS7Yz3mu/6/E4EvgCc37x2bwD2aHnfAqiqy4HtzYcrX1lV72T5D5wL\nWb7Kym9W1b+tesKq77P8R9IpYzwHSZIkNTY0djJETezkqqp6bddzmbbmg5Y7gMdU1dIaxxg7kSRJ\nM2GIsRMNRJavif5F4O/XarwlSZK0PpvvMVXVyzfjqndVXVxVB1TVb3c9Fw2HuUy1Za1oHNaL+szm\nW5IkSZoSM9+aKDPfkiRpVpj5liRJkgbM5lsbIL3+mZvbuoHPXeMwl6m2rBWNw3pRn23018trEzLS\nIUmStDoz35qoJGVNSZKkWWDmW5IkSRowm29JnTGXqbasFY3DelGf2XxLkiRJU2LmWxNl5luSJM0K\nM9+SJEnSgNl8S+qMuUy1Za1oHNaL+szmW5IkSZoSM9+aKDPfkiRpVpj5liRJkgbM5ltSZ8xlqi1r\nReOwXtRnNt+SJEnSlJj51kSZ+ZYkSbPCzLckSZI0YDbfkjpjLlNtWSsah/WiPrP5liRJkqbEzLcm\nKokFpQ03t/8cOy/d2fU0JEkzrovMt823JipJsdD1LDR4C+B/uyRJN5QfuJS0uVzS9QQ0K8zwahzW\ni/rM5luSJEmaEmMnmihjJ5qKBWMnkqQbrovYyZ7TfDBtjCTXABcAAQo4tape3e2sJEmStCtjJ8Pw\nnao6uKru3/y28dZsMPOtlszwahzWi/rM5nsYVn27JMklSRaSbE9yQZK7N/uPS/KikeMuSvLTzfbL\nknwuyVlJ3rZyXJIzkxzcbN8qiW2TJEnSmGy+h2GfJOcl2dH8Pnrktsur6hDgjcCL17h/ASR5APA4\n4EDgkcAD1nlMA7e64e7c9QQ0K+bn57uegmaI9aI+M/M9DN+tqoPXuO09ze/tLDfW63ko8L6quhq4\nOslpk5qgJEmSbL43g+83v6/hun/eP+TH3/XYp8V5Ru+z97pHLrSfnHR9zO0/B1yX61xZ5XI83PFo\nhrcP83Hc77H14nit8cr20tISXfFSgwOQ5Kqq2neV/ZcAh1TVN5McAvxhVT08ya8Aj6qqpzQ57k8B\nBwC3ZTme8lBgL5ZXy0+sqtcm+Utge1W9MckLgWOq6oBVHrN+PJESLwmnNS0uLl77H0ZpPdaKxmG9\nqC2/Xl7XS5KrgYu47lKDH6iqlyb5MvCAVZrvvYH3Af8F+CTwEOCIqvpKkt8FngJcBlzenOtNSe4B\nvIPlFfDTgafafEuSpFlm863OJblZVX0nyT7AWcCzq+r8Me5v8y1JkmZCF823VzvRrv4iyQ6WIyfv\nHKfxlsY1msGT1mOtaBzWi/rMD1zqx1TVr3Q9B0mSpKEydqKJMnYiSZJmhbETSZIkacBsviV1xlym\n2rJWNA7rRX1m5lsb4Lp3b+bmtnY4D0mSpH4x862JSlLWlCRJmgVmviVJkqQBs/mW1BlzmWrLWtE4\nrBf1mc23JEmSNCVmvjVRZr4lSdKsMPMtSZIkDZjNt6TOmMtUW9aKxmG9qM9sviVJkqQpMfOtiTLz\nLUmSZoWZb0mSJGnAbL4ldcZcptqyVjQO60V9ZvMtSZIkTYmZb02UmW9JkjQrzHxLkiRJA2bzLakz\n5jLVlrWicVgv6jObb0mSJGlKzHxrosx8S5KkWWHmW5IkSRowm29NXJKZ/rndHW7X9Uu4aZjLVFvW\nisZhvajP9ux6Ahqgha4ncMNctnBZ11OQJEkDZeZbE5WkZr35ZgH890KSpOEz8y1JkiQNmM23pM6Y\ny1Rb1orGYb2oz2y+N5Ek1yQ5L8mO5vdLmv2XJLnlKsd/tPm9NcmTR/YfkuSE6c1ckiRpGMx8Kg1U\nJQAAIABJREFUbyJJrqyqLavs/zLwgKr65hr3mweOrapHt3gMM9+SJGkmmPnWRluruAKQZJ8kf5/k\nmc34qub244HDmtXyFyTZluS0KcxXkiRpUGy+N5d9domdHN3sL2Bf4O+Av6mqN43sB/hfwNlVdXBV\n/ckut0nXm7lMtWWtaBzWi/rM63xvLt+tqoNX2R/gvcCrq+qUKc9JkiRp07D51oqPAb8I3PDme+EG\nn6FT+916v2u3V1ZP5ufnHW/AeGVfX+bjuL/j+fn5Xs3Hcb/H1ovjtcYr20tLS3TFD1xuIkmuqqp9\nV9l/CXAIcBywZ1X9xujxSQ4G/qiqfr7Zv43lD2Aetcq5qh+JlPihSUmStC4/cKmNtvcume9XNvsL\noKpewHIu/FWj+4ELgR8193vBlOesARtdiZDWY61oHNaL+szYySZSVXutsf+Ake1fH9ne0vz+IXD4\nLnf7yEbMUZIkaciMnWiijJ1IkqRZYexEkiRJGjCbb0mdMZeptqwVjcN6UZ/ZfEuSJElTYuZbE2Xm\nW5IkzYouMt9e7UQbYKo1vKq5ua1dT0GSJOknGDvRxFVV5z87dy51/TKoBXOZasta0TisF/WZzbck\nSZI0JWa+NVFJypqSJEmzwOt8S5IkSQNm8y2pM+Yy1Za1onFYL+ozm29JkiRpSsx8a6LMfEuSpFlh\n5luSJEkaMJtvSZ0xl6m2rBWNw3pRn9l8S5IkSVNi5lsTZeZbkiTNCjPfkiRJ0oDZfEvqjLlMtWWt\naBzWi/rM5luSJEmaEjPfmigz35IkaVaY+ZYkSZIGzOZbUmfMZaota0XjsF7UZzbfkiRJ0pSY+dZE\nJbGgboC5/efYeenOrqchSdKm0EXm2+ZbE5WkWOh6FjNsAfx3UpKk6fADl5I2FXOZasta0TisF/WZ\nzbckSZI0JcZONFHGTm6gBWMnkiRNi7ETTU2Sa5Kcl2RH8/slqxyzLclpXcxPkiRpiGy+N6/vVNXB\nVXX/5ver1zjOZVhtGHOZasta0TisF/WZzffmtepbLEl+Mclnk3waePzI/v2SvCfJBUnOSXLg1GYq\nSZI0EGa+N6kkPwQuZLkJL+B44O+ALwDzVfXlJG8H9qmqo5L8KXBFVf1ekp8HXltV91/lvGa+b4gF\nM9+SJE1LF5nvPaf5YOqV71bVwaM7ktwP+HJVfbnZ9Vbg2c32YTQr4VV1ZpJbJvmpqvqPnzjzwobN\nefD2u/V+LC4uMj8/D1z31qljx44dO3bs+IaPV7aXlpboiivfm1SSK6tqyy777gf8aVVta8aPBp7d\nrHyfBzy+qpaa274C3GvX5nv5Gy43Q03FFeoJWBz5Q0Naj7WicVgvasurnWiaViu0zwFbk9y5GT95\n5LazgacCJJlnOYLyk6vekiRJWpMr35tUkquBi7gu8/2Bqnppkv8GnAB8h+WG+y7Nyvd+wF8DBzS3\nPaeqLl7lvK58S5KkmdDFyrfNtybK5luSJM0KYyeSNpXRD8BI67FWNA7rRX1m8y1JkiRNibETTZSx\nE0mSNCuMnUiSJEkDZvMtqTPmMtWWtaJxWC/qM7/hUhtgqu/edGJubmvXU5AkSTPIzLcmKklZU5Ik\naRaY+ZYkSZIGzOZbUmfMZaota0XjsF7UZzbfkiRJ0pSY+dZEmfmWJEmzwsy3JEmSNGA235I6Yy5T\nbVkrGof1oj6z+ZYkSZKmxMy3JsrMtyRJmhVmviVJkqQBs/mW1BlzmWrLWtE4rBf1mc23JEmSNCVm\nvjVRZr4lSdKsMPMtSZIkDZjNt6TOmMtUW9aKxmG9qM9sviVJkqQpMfOtiTLzLUmSZkUXme89p/lg\n2hySqdbwpjS3/xw7L93Z9TQkSdKYXPnWRCUpFrqexSawAEP4d3dxcZH5+fmup6EZYK1oHNaL2vJq\nJ5IkSdKAufKtiXLle0oWhrHyLUlSl1z5liRJkgbM5nuGJbkmyXlJdjS/X9LsvyTJLTfwcQ9JcsJG\nnV+bh9fiVVvWisZhvajPvNrJbPtOVR28yv4NzSNU1XZg+0Y+hiRJ0hCZ+Z5hSa6qqn1X2X8J8A7g\nCOC7wFOq6stJtgJ/DdwKuAJ4RlVdmuQk4ErgAcAc8JKqeneSNwN/W1V/15z3rcDbm2NfXFWPXuWx\nzXxPw4KZb0mSbigz3xrXPrvETo4eue1bVXVf4M+AP2n2vQ44qaoOAt7WjFfcrqoeCjwa+INm35uA\nZwAk2QI8BDi9uc3OT5IkaUw237Ptu1V1cFXdv/n9zpHbTm1+nwIc2mw/pBkD/F/goSPHvxegqj4L\n3LbZPgu4a5JbAU9meRX8RxvzVLQZmctUW9aKxmG9qM/MfA9XrbG9lu+PbI++/fIW4FeBJwFPb/XI\nC62O0g0wt/8ccN3/YFa+TGLWxueff36v5uPYsWPHjoc9XtleWlqiK2a+Z9huMt9/XlWvTvJU4Oiq\nekyS9wLvqqq3Jnk68Oiq+qUm831aVb171/MmuS3wKeDrVfWQZt824NiqOmqVx67Ve/2YUZYkSb3S\nRebble/ZtneS81heqS7gA1X10mZ7vyQXAN9jOTICcAxwUpIX03zgstm/a1d87biqLk/yWeA9G/c0\nJEmSNgdXvrWuJDcFLgAOrqqrWhzvyrdaW1xcvPYtQWk91orGYb2oLa92ol5Jcjjwz8Cftmm8JUmS\ntD5XvjVRrnxLkqRZ4cq3JEmSNGA235I6M3rpJ2k91orGYb2oz2y+JUmSpCkx862JWs58/6S5ua3s\n3Lk05dlIkiStzet8axD8g06SJGl1xk4kdcZcptqyVjQO60V9ZvMtSZIkTYmZb01UkrKmJEnSLPA6\n35IkSdKA2XxL6oy5TLVlrWgc1ov6zOZbkiRJmhIz35ooM9+SJGlWmPmWJEmSBszmW1JnzGWqLWtF\n47Be1Gc235IkSdKUmPnWRJn5liRJs8LMtyRJkjRgNt+SOmMuU21ZKxqH9aI+s/mWJEmSpsTMtybK\nzLckSZoVZr4lSZKkAbP5ltQZc5lqy1rROKwX9dmeXU9Aw5NM9d0bSRqUuf3n2Hnpzq6nIWmDmPnW\nRCUpFrqehSTNsAXw/83SdJj5liRJkgbM5ltSdy7pegKaGdaKxmDmW31m8y1JkiRNic33QCW5Jsl5\nSS5OsiPJi7KbT0Im2Zrkomb7fkmOmM5stWnduesJaGZYKxrD/Px811OQ1uTVTobrO1V1MECSWwOn\nAFtgtx+HXPmUz/2BQ4B/2KgJSpIkbTaufG8CVfVvwHOA/wmQ5EZJXp3kk0nOT/Ls0eOT7Am8HHhi\ns3p+dJIHJjknyfYkH01yt+k/Ew2OOV61Za1oDGa+1WeufG8SVXVJ03TfBngs8O9V9eAkNwY+luSM\nkWN/mOR3gUOq6hiAJD8FHFZVP0pyOHA88IQOnookSdLMsvnenB4BHJjk6Ga8Bbgb8IV17nML4C3N\nindh7WgSzPGqLWtFYzDzrT6zgdokkhwAXFNVVzQfvHx+VX1ol2O2rnOK3wM+XFWPb447c80jFyYw\nYUnapOb2nwOui06sNJKOHTu+4eOV7aWlJbriN1wOVJKrqmrfZvs2wFuBj1XVK5qM9yOBo5uIyd2A\nS4HbAqdV1X2TPB44qqqe3pzjb4G3VtV7kiwAv1ZVB6zyuHXdZzbHmrHf6LYJLS4uukKlVqwVjcN6\nUVt+w6Umae+VSw0CZwAfqKpXNLf9FfDPwHnNpQXfyE++C3ImcK+VD1wCrwZelWQ71o0kSdL14sq3\nJsqVb0mSNCtc+ZYkSZIGzOZbUme8Fq/aslY0DutFfWbzLUmSJE2JmW9NlJlvSZI0K8x8S5IkSQNm\n860NkLF/5ubW+34fDZW5TLVlrWgc1ov6zG+41MQZH5EkSVqdmW9NVJKypiRJ0iww8y1JkiQNmM23\npM6Yy1Rb1orGYb2oz2y+JUmSpCkx862JMvMtSZJmhZlvSZIkacBsviV1xlym2rJWNA7rRX1m8y1J\nkiRNiZlvTZSZb0mSNCvMfEuSJEkDZvMtqTPmMtWWtaJxWC/qM5tvSZIkaUrMfGuizHxLkqRZYeZb\nkiRJGjCbb0mdMZeptqwVjcN6UZ/ZfEuSJElTYuZbE2XmW5IkzYouMt97TvPBtDkkU61hbaC5/efY\neenOrqchSdJguPKtiUpSLHQ9C03MAmzkfyMWFxeZn5/fsPNrOKwVjcN6UVte7USSJEkaMFe+NVGu\nfA/MwsaufEuS1CVXviVJkqQBs/megiRzSU5J8oUk5yZ5f5K7TuFxn5bk8iTnJfnnJC8cue25SZ66\n0XOQ1uO1eNWWtaJxWC/qM692Mh3vAU6qqicDJDkQmAO+uHJAkj2q6poNeOxTq+qYJLcEPp/knVX1\ntao6cRIn38B5S5IkDY4r3xssyc8DP6iqv1zZV1UXVdXHkmxLclaS9wGfaY5/UZKLklyY5AXNvps2\nq+U7mv1HN/tfleTiJOcnefV686iqb7Lc7N++ue9xzWPdI8knR+a7NcmFzfYhSRab1fp/SDLX7D8z\nyR8n+RRwzARfLm0yXo1AbVkrGof1oj5z5Xvj3QfYvs7t9wfuXVVfSXIw8DTggcAewCeTLAJ3Ab5W\nVUcCJNm3Wcl+bFXds9m3Zb1JJPlp4CbAhaP7q+rzSfZKsrWq/gX4ZeDUJHsCfwocVVXfSPJE4JXA\nM5u77lVVD2r/MkiSJMnmu3ufqqqvNNuHAe+pqu8BJHk38DDgg8BrkhwPnF5VH02yB/CfSf4KOB14\n/xrnf1KSbcA9gP9ZVT9Y5Zh3stx0v7r5/cTm+PsAH8ryt+bcCPjXkfu8fc1ntLDb56wZsd+t9/ux\n6+Wu5CgnNT7hhBM46KCDNuz8joczHs3w9mE+jvs9tl4crzVe2V5aWqIrXmpwgyV5OHBcVW1b5bZt\nwLFVdVQzPga4ZVUtNONXAJdX1euT3AJ4JPAc4B+r6veT7AUcDhwN3KmqDt/l/E8DDmky34cAZwA/\nU1WXJzkOuKqqXpvkAJYb8CcBb6uqBya5D3BiVT10lXmf2cz7vFVuK1ivpuKl63StRb8IQy1ZKxqH\n9aK2vNTgAFXVh4EbJ3nWyr4kByY5bJXDzwYem2TvJDcDHgecneT2wH9W1duAPwQOTnJT4BZV9QHg\nRcB9dzOP7cBbgBeuctuXgWuAl3HdivbngdskObSZ855J7jXOc5d2x/85qi1rReOwXtRnNt/T8Tjg\nF5J8MclFLGenv77rQVW1AzgZOBf4OPAXVXUBcCDwqSQ7gN8Ffh/YArw/yQXAWcBvtpjHq4GnN439\nrt4O/ArwjmYuVwNPAP4gyfnADuAhK1Nt86QlSZL044ydaKKMnWgcvjWstqwVjcN6UVvGTiRJkqQB\nc+VbE+XKtyRJmhWufEuSJEkDZvMtqTOj112V1mOtaBzWi/rM5luSJEmaEjPfmqjlzPfa5ua2snPn\n0pRmI0mStLYuMt9+vbwmzj/oJEmSVmfsRFJnzGWqLWtF47Be1Gc235IkSdKUmPnWRCUpa0qSJM0C\nr/MtSZIkDZjNt6TOmMtUW9aKxmG9qM9sviVJkqQpMfOtiTLzLUmSZoWZb0mSJGnAbL4ldcZcptqy\nVjQO60V9ZvMtSZIkTYmZb02UmW9JkjQrzHxLkiRJA2bzLakz5jLVlrWicVgv6jObb0mSJGlKzHxr\nosx8S5KkWWHmW5IkSRowm29JnTGXqbasFY3DelGf2Xxr4pKs+nO7O9yu66lJkiR1ysy3JipJsbDG\njQtgvUmSpL4w8y1JkiQNmM23pM6Yy1Rb1orGYb2oz2y+BybJNUnOS3J+kk8nObTrOUmSJGmZme+B\nSXJlVW1pth8BvLSq5lved4+quuYGPr6Zb0mSNBPMfGsSRgvo5sA3r70h+cMkFyW5IMkTm33bkpyV\n5H3AZ5JsTfLPyf9r796jJavLM49/Hy6KIpCOjIeA2mDEAEFtEBAF7SMGYmICxMgIxoUajTOOt8yQ\nRGOWQweyEnPRwcFxVMxF0AgaQBETRJfdAgnYIDQ3G6KGg5LYEEQJXgaVfueP2qcpmj5NFdSpvavO\n97NWrd77V/vyq9Nvn/P2Pk/tygeT3JDkoiSPbrZ9ZpLLm6vq5ybZZayvTJIkacLZfE+fxzSxk/XA\nB4FTAZK8BHhGVT0dOBL48yQzzT4HAG+qqn2a9acCp1fV/sDdwK8342cCv1tVK4AbYMFr3NJAzGVq\nUNaKhmG9qMtsvqfPD6rqwKraF/gl4Kxm/HDgYwBVdQewBji4eW5tVX2j7xi3VNX1zfKXgT2T7Azs\nUlWXNeMfBp63eC9DkiRp+mzX9gS0eKrqiiS7Jtl1C0/3x1O+v9lz9/Yt3wfssIV9FrZqgfFte9kq\nLR3Lls1w3nlnMzs7C9x/NWp+fX5soeddd31+fXZ2tlPzcb3b69aL6wutzy/Pzc3RFt9wOWWS3FNV\nOzXL+wCXADPAscDrgBcDjwfWAs8G9gVOqqqjm32WAxc28RSSnATsWFWnJLkGeGNV/WOSk4Gdq+qk\nzc5fYE1pXnyTrSSps3zDpUZhhybzfQ29mMmJ1XM+cB1wLfB5etntOxY4xkLd0quAv0iyDngmcMpo\np66lpv9KhLQ11oqGYb2oy4ydTJmq2n4rz70VeOtmY18Evti3fivwjL71d/UtXws8Z5TzlSRJWkqM\nnWikjJ3ogYydSJK6y9iJJEmSNMVsviW1xlymBmWtaBjWi7rM5luSJEkaEzPfGikz33ogM9+SpO5q\nI/Pt3U60CPwgHfXMzCxvewqSJHWKsRONXFX58EFVsWHD3FZrxVymBmWtaBjWi7rM5luSJEkaEzPf\nGqkkZU1JkqRJ4H2+JUmSpClm8y2pNeYyNShrRcOwXtRlNt+SJEnSmJj51kiZ+ZYkSZPCzLckSZI0\nxWy+JbXGXKYGZa1oGNaLuszmW5IkSRoTM98aKTPfkiRpUpj5liRJkqaYzbek1pjL1KCsFQ3DelGX\n2XxLkiRJY2LmWyNl5luSJE0KM9+SJEnSFLP5ltQac5kalLWiYVgv6jKbb0mSJGlMzHxrpJJYUCM2\ns8cMG27b0PY0JEmaOm1kvm2+NVJJilVtz2LKrAL/nUqSNHq+4VLSkmIuU4OyVjQM60VdZvMtSZIk\njYmxE42UsZNFsMrYiSRJi8HYiR6WJPcluTrJuiRXJTm07TlJkiTpwWy+p8P3q+rAqloBvB14Z9sT\nkgZhLlODslY0DOtFXWbzPR36f12yC3DXpieS30mytrkqfnIztjzJV5J8MMkNSS5K8ujmudVJDmyW\nH5/klmZ5myR/luRLzbF+a3wvT5IkaTrYfE+HxzSxk/XAB4FTAZIcCexdVYcABwAHJTm82eepwOlV\ntT9wN/DrCxx7Pmz8GuC7VfVs4BDgdUmWL87L0VIxOzvb9hQ0IawVDcN6UZdt1/YENBI/qKr5q9WH\nAmcB+wNHAUcmuZre1fEdgb2BbwK3VNX1zf5fBvZ8iHMcBTw9yXHN+s7NsW4d4euQJEmaajbfU6aq\nrkiya5Jd6TXcf1JVZ/Rv01yxvrdv6D5gh2b5J9z/G5Ed+ncD3lRVn3vISax6eHPXArbpvRt7FJYt\nm+G8887edFVoPhfZ1vppp53GihUrOjMf17u73p/h7cJ8XO/2uvXi+kLr88tzc3O0xVsNToEk91TV\nTs3yPsAlwAzwC8ApwC9U1feT7A78GHgscGFVPb3Z5yRgx6o6JckZwJer6v1Jfht4c1U9pcl4/zJw\nXFX9JMnewG1V9cPN5lL3J1XUPenUbQvXrFmz6RujtDXWioZhvWhQfry8HpYkPwau5/43Xv5+VV3U\nPPcmYP7NkfcArwA2Ap+uqmc02/Q33z8HfJzeFfDPAK9omu8AfwT8anOeO4Bjq+qezeZi891p3Wq+\nJUlqk823Jp7Nd9fZfEuSNM8P2ZG0pPRn8KStsVY0DOtFXWbzLUmSJI2JsRONlLGTrjN2IknSPGMn\nkiRJ0hSz+ZbUGnOZGpS1omFYL+oyP2RHi2Csv73REGZmlrc9BUmSljQz3xqpJGVNSZKkSWDmW5Ik\nSZpiNt+SWmMuU4OyVjQM60VdZvMtSZIkjYmZb42UmW9JkjQpzHxLkiRJU8zmW1JrzGVqUNaKhmG9\nqMtsviVJkqQxMfOtkTLzLUmSJoWZb0mSJGmK2XxLao25TA3KWtEwrBd1mc23JEmSNCZmvjVSZr4l\nSdKkMPMtSZIkTTGbb0mtMZepQVkrGob1oi6z+ZYkSZLGxMy3RsrMtyRJmhRmviVJkqQpZvOtkUvi\no0OP3Z64W9slsSBzmRqUtaJhWC/qsu3anoCm0Kq2J6B+t6+6ve0pSJKkhplvjVSSsvnumFXgv3NJ\nkh7MzLckSZI0xWy+JbXGXKYGZa1oGNaLuszme0IkuS/J1UnWJbkqyaGLcI57Rn1MSZIk3c/M94RI\n8h9VtXOzfBTw9qqaXaxzPIJjmPnumlVmviVJ2hIz39qa/sLYBbgLIMmOST7fXA2/NsmvNuN/mOQt\nm3ZO/ijJm5rl30mytrmKfvKDTpTsluSLzZX265Ic1oy/r9nv+i3tJ0mSpK2z+Z4cj2ma4fXAB4FT\nm/EfAsdW1UHAEcC7m/G/Ak4ESBLgeOAjSY4E9q6qQ4ADgIOSHL7ZuV4OXFRVBwLPBNY1429v9nsm\nMJtk/8V4oVo6zGVqUNaKhmG9qMu8z/fk+EHTDNPkvc8C9qf3H6g/SfJ8YCOwe5InVNWtSe5M8kxg\nN+DqqvpOE1k5MsnV9K6m7wjsDVzWd64rgb9Msj3wqaq6thk/Pslv0aub3YD9gBseNNNVI37lekSW\n7bps0/L8D6TZ2dlOrK9bt65T83Hdddddd3261+eX5+bmaIuZ7wmxeR47yQZ6zfeLgRcBv1FVG5Pc\nAqysqm8kOQ44jF6j/DdVdVGSvwBurqoztnaOJLs1x34j8C56zfnngGdV1X8k+WtgdVWdudkxCgqI\nOWNJktRpZr61NZsKI8k+9P7uvk0v/31H03i/AFjet88n6TXmBwGfbcY+C/xmkh2bY+2eZNf+cyR5\ncnPMvwQ+BBwI7Ax8D7gnyQzwS4vyKiVJkqaYzffk2KHJfF8DfAw4sXqXlj8KHJzkWuAVwPr5Harq\nx8Bq4OPNtlTV54C/BS5Pch3wCWCn+V2aP2eBa5toyn8G3lNV19HLfq8HPsIDYyrSw9L/a0Bpa6wV\nDcN6UZeZ+Z4QVbX9AuPfBp67peeSbAMcCrx0s31OB07fwrF2bv48EzhzC8+/euiJS5IkaRMz31Mq\nyb7AhcC5VfV7YzyvmW9JkjQR2sh823xrpGy+JUnSpPANl5KWFHOZGpS1omFYL+oym29JkiRpTIyd\naKSMnUiSpElh7ERTIszMLH/ozSRJkpYYm2+NXFWxYcNc29PQBDCXqUFZKxqG9aIus/mWJEmSxsTM\nt0YqSVlTkiRpEpj5liRJkqaYzbek1pjL1KCsFQ3DelGX2XxLkiRJY2LmWyNl5luSJE0KM9+SJEnS\nFLP5ltQac5kalLWiYVgv6jKbb0mSJGlMzHxrpMx8S5KkSWHmW5IkSZpiNt+SWmMuU4OyVjQM60Vd\nZvMtSZIkjYmZb42UmW9JkjQpzHxLkiRJU8zmW1JrzGVqUNaKhmG9qMtsviVJkqQxMfOtkUqyqAU1\ns8cMG27bsJinkCRJS0QbmW+bb41UkmLVIp5gFVizkiRpFHzDpaQlxVymBmWtaBjWi7rM5luSJEka\nE2MnGiljJ5IkaVIYO9FQktyX5Ook65JcleTQER9/ZZJPL/DcB5PsM8rzSZIkTTub78n2/ao6sKpW\nAG8H3rkI59jiZeaqel1V3bQI59MSYi5Tg7JWNAzrRV1m8z3Z+n9NsgtwF0CSHZN8vrkafm2So5vx\n5Umu37RzclKS/9ks/2ySz/VdRd+r2WynJJ9Isj7JWX37rk5y4KK/QkmSpCmyXdsT0CPymCRXA48B\ndgOOaMZ/CBxbVd9L8njgCuCC5rmFAtMfBf64qi5I8ih6/zF7MrAC2A/YAPxjkudW1T8tzsvRUjM7\nO9v2FDQhrBUNw3pRl9l8T7YfVNWBAE3e+yxgf3qN858keT6wEdg9yRMWOkiSxwG7V9UFAFX1o2Yc\nYG1VfatZXwfsCWy9+V71SF7SQ9hm07wkddyyZTOcd97Zmxqh+SiA66677npb6/PLc3NztMW7nUyw\nJP9RVTv3rW+g13y/GHgR8BtVtTHJLcBK4D7g4qr6+Wb7PwC2Bd4NrK+qJ212/JXASVU1H1s5Hbiy\nqs5Msrp57urN9qmFL65Lm1sDzLY8By2ejOzuRGvWrNn0Q1R6KNaLBuXdTjSsTcXS3HlkG+Db9PLf\ndzSN9wuA5c1mtwP/KcmyJI8GfgWgqr4HfDPJMc2xHpXkMWN8HZIkSUuCsZPJtkOT+Z5vwk+sqkry\nUeDTSa4FrgLWA1TVT5KcAlwJ3DY/Pr8v8IHm+R8Bx23hfLXAsvQwzbY9AU0Ir2JqGNaLuszYiUbK\n2Imk+40udiJJi8HYiaQlZk3bE9CE6H+zlPRQrBd1mc23JEmSNCbGTjRSxk4k3c/YiaRuM3YiSZIk\nTTGbb0ktWtP2BDQhzPBqGNaLusxbDWoR+AmUkmBmZvlDbyRJS4yZb41UkrKmJEnSJDDzLUmSJE0x\nm29JrTGXqUFZKxqG9aIus/mWJEmSxsTMt0bKzLckSZoUZr4lSZKkKWbzLak15jI1KGtFw7Be1GU2\n35IkSdKYmPnWSJn5liRJk8LMtyRJkjTFbL4ltcZcpgZlrWgY1ou6zOZbkiRJGhMz3xopM9+SJGlS\nmPmWJEmSppjNt6TWmMvUoKwVDcN6UZfZfEuSJEljYuZbI2XmW5IkTYo2Mt/bjfNkWhqSsdawNDYz\ne8yw4bYNbU9DkjTBvPKtkUpSrGp7FpoYtwB7tT2JIawCv2e2Y82aNczOzrY9DU0I60WD8m4nkiRJ\n0hTzyrdGyivfmmqrvPItSdPEK9+SJEnSFLP57qAkxybZmORpi3ye5UmuX8xzSFt1S9samfr5AAAS\n+0lEQVQT0KTwvs0ahvWiLrP57qbjgUuBE8Zwrof8HXoS60SSJGkEbKo6JsmOwGHAa2ia7yQrk6xO\n8okk65Oc1bf9O5J8Kcl1Sd7fN746ybuTXJnkxiQHJTk3yc1JTu075fZJPpLkK0k+nmSHZv9bkrwz\nyVXAS5O8NsnaJNc089hhLF8QTbdJutOJWuWdKzQM60VdZvPdPccAF1XV14A7kxzQjK8A3gzsB/xs\nkuc246dX1bOr6hnAY5O8uO9Y91bVwcAHgE8BrweeDrwqybJmm58D3ltV+wH3AP+tb/87q+qgqvo4\ncG5VHVJVBwA30fvPgSRJkoZg8909JwBnN8vnAC9vltdW1beaj49cB+zZjL8wyRVJrgNeAPx837Eu\naP68Hrihqu6oqh8BXwee1Dz3jaq6oln+CHB43/7n9C0/PcklzXlevtl5pIfHzLcGZIZXw7Be1GV+\nwmWHNFejjwD2T1LAtvQy2Z8B7u3b9D5guySPBv4PcGBV/VuSk4H+OMj8Phs3279Y+O++PwP+/b7l\nvwGOrqobkrwSWLngC1m14DPSRFu267IHfHjH/A9411133XXXJ2N9fnlubo62eJ/vDknyOuCAqnp9\n39hq4AvAwVV1dDN2OnAlvSjJTfSugm8PXA58oqpOafY7qaquTrKyWT6675gnAd+md+3xOVX1pSRn\nADdW1WlJbgGeVVV3NfvcQS/ycje9/wzcVlW/uYXXUA9+D2e8N7IkSeoc7/OtlwHnbzZ2Hr27n/R3\nrwVQVXcDHwJuBP4BWLv5Ngvof+4m4A1JvgL8FPD+LWwD8I7m+JcC6x/qhUiSJOnBvPKtkfLKt4ax\npi/CIW2NtaJhWC8alFe+JUmSpCnmlW+NlFe+JUnSpPDKtyRJkjTFbL4ltab/1k/S1lgrGob1oi6z\n+ZYkSZLGxMy3Rqr5cKAHmJlZzoYNcy3MRpIkaWFtZL79hEuNnP+hkyRJ2jJjJ5JaYy5Tg7JWNAzr\nRV1m8y1JkiSNiZlvjVSSsqYkSdIk8D7fkiRJ0hSz+ZbUGnOZGpS1omFYL+oym29JkiRpTMx8a6TM\nfEuSpElh5luSJEmaYjbfklpjLlODslY0DOtFXWbzLUmSJI2JmW+NlJlvSZI0Kcx8S5IkSVPM5ltS\na8xlalDWioZhvajLbL4lSZKkMTHzrZEy8y1JkiaFmW9JkiRpitl8S2qNuUwNylrRMKwXddl2bU9A\n0ycZ629vJE2YmT1m2HDbhranIUmtMPOtkUpSrGp7FpI6bRX4s0dSF5j5liRJkqaYzbek9tzS9gQ0\nKczwahjWi7rM5luSJEkaE5vvMUpybJKNSZ7WN7YyyacX8Zz3jOM80sOyV9sT0KSYnZ1tewqaINaL\nuszme7yOBy4FTthsfDHfeVQLLEuSJGnMbL7HJMmOwGHAa3hw8z2/zcFJvpzkKUmuS7JzM35nklc0\nyx9O8sIky5NckuSq5nHoANPYJcmFSW5K8r6+857QnO+6JO/sG78nyZ8luSHJxc38Vif5WpJfeSRf\nDwkw862BmeHVMKwXdZnN9/gcA1xUVV8D7kxyQP+TSZ4DvA84uqr+BbgMOCzJzwNfB57XbPoc4J+A\n24FfqKqD6F1RP32AORwMvAHYF3hqkpck+RngncAssAI4OMnRzfY7Ap+vqv2B7wGnAi8EXtIsS5Ik\naQh+yM74nACc1iyfA7wcuKZZ3w/4AHBUVc1/8sRlwErgVuD9wG8l2R24q6p+2FwVf2+SFcB9wN4D\nzGFtVd0KkORjwOHAT4DVVXVXM/5R4PnABcCPquriZt/rgf9XVRuTXA8sfzhfBOkBzHxrQGZ4NQzr\nRV1m8z0GSZYBRwD7JylgW3r5699tNvkW8GjgQODvm7FL6F2lfhLwB8CvAS+llxkH+O/Ahqp6RpJt\ngR8OMJXNM9/VPBa6ufyP+5Y3AvcCVFUlWbh2Vg0wE0lL1sweM8D90YD5Rsl11113fbHX55fn5uZo\ni59wOQZJXgccUFWv7xtbDbyDXiN+Er0s+OeBN1fVF5ttbgburqpDkvwe8EbgDVX16STvBr5ZVf8r\nyauBD1XVtls49z1VtVOSlcA/0IucfJNek/8B4PLm8SzgbuAi4D1VdeH8vs1xTgbuqap39x93C+er\nR/a+zvjJd0vImjVrNn1jlLbGWtEwrBcNyk+4nF4vA87fbOxc+t54WVX/DvwKvSjJwc3wFcDNzfKl\nwO704ijQy4e/Ksk1wNOA7y9w7v5Odi3wXuBG4OtVdX4Tc3kbsIZeDOaqqrpwC/tu7biSJEkagFe+\nNVJe+ZYkSZPCK9+SJEnSFLP5ltSa/jfASFtjrWgY1ou6zOZbkiRJGhMz3xopM9+SJGlSmPmWJEmS\nppjNtxZBHvZjZsYPzlxKzGVqUNaKhmG9qMv8hEuNnLERSZKkLTPzrZFKUtaUJEmaBGa+JUmSpClm\n8y2pNeYyNShrRcOwXtRlNt+SJEnSmJj51kiZ+ZYkSZPCzLckSZI0xWy+JbXGXKYGZa1oGNaLuszm\nW5IkSRoTM98aKTPfkiRpUpj5liRJkqaYzbek1pjL1KCsFQ3DelGX2XxLkiRJY2LmWyNl5luSJE0K\nM9+SJEnSFLP5ltQac5kalLWiYVgv6jKbb0mSJGlMzHxrpMx8S5KkSdFG5nu7cZ5MS0My1hqeCDN7\nzLDhtg1tT0OSJLXMK98aqSTFqrZn0UGrwH9rD7ZmzRpmZ2fbnoYmgLWiYVgvGpR3O5EkSZKmmFe+\nNVJe+V7AKq98S5LUNV75liRJkqaYzXcHJDk2ycYkT1vg+b9O8pJxz0tabN6LV4OyVjQM60VdZvPd\nDccDlwIntD0RSZIkLR6b75Yl2RE4DHgNfc13kvcmWZ/kYuAJfePvSPKlJNcleX/f+Ook705yZZIb\nkxyU5NwkNyc5tW+785ttrk/y2mbspUne1Sy/JcnXm+W9kly2tfNKj4R3I9CgrBUNw3pRl9l8t+8Y\n4KKq+hpwZ5IDkvwasHdV7Qu8Enhu3/anV9Wzq+oZwGOTvLjvuXur6mDgA8CngNcDTwdelWRZs82r\nm20OBt7SjF8KHN48f3gzj58Bngd8cYDzSpIkaQB+yE77TgBOa5bPAV5O7+/lYwBV9a0kX+jb/oVJ\nfhd4LLAMuAH4TPPcBc2f1wM3VNUdAEn+BXgS8B3gt5Mc22z3RHpN/tokj0vyuGa7vwVW0mu+zx3g\nvA+0avgvwtTbtjsfPrRs2Qx33dX7wJ/5XOT8VaJxr5922mmsWLGitfO7Pjnr/RneLszH9W6vWy+u\nL7Q+vzw3N0dbvNVgi5qrzrcBdwAFbNv8eT5wbVX9TbPducBH6TW7twIHVtW/JTkZqKo6Jclq4KSq\nujrJymb56Gb/1cBJwE7AqcCRVXVvM35yVV2S5AzgOuBZwP+mF4N5Pr2r7j9a6LxbeE3VewnqrnTm\ntodr/CAMDcha0TCsFw3KWw0uPccBZ1bVXlX1lKpaDtwC3AW8LMk2TfzjBc32O9DrbL/dXKV+6ZDn\n2wX4TtN47wMc2vfcZcDv0IuZrGvOeW9V3TOC80pb5A9HDcpa0TCsF3WZsZN2vQz4083GzgX2Bb4K\nfIXeFed/Aqiqu5N8CLgR+Bawtm+/rV3KnH/uIuC/JrkRuBm4vG+bS+nFUC6pqo1JvgGs7zvvGQuc\nV5IkSQMydqKRMnYyCYydaPJYKxqG9aJBGTuRJEmSpphXvjVSXvmeBN258i1JUpu88i1JkiRNMZtv\nSa3pv++qtDXWioZhvajLbL4lSZKkMTHzrZHqZb7VZTMzy9mwYa7taUiS1Lo2Mt/e51sj53/oJEmS\ntszYiaTWmMvUoKwVDcN6UZfZfEuSJEljYuZbI5WkrClJkjQJvM+3JEmSNMVsviW1xlymBmWtaBjW\ni7rM5luSJEkaEzPfGikz35IkaVKY+ZYkSZKmmM23pNaYy9SgrBUNw3pRl9l8S5IkSWNi5lsjZeZb\nkiRNCjPfkiRJ0hSz+ZbUGnOZGpS1omFYL+oym29JkiRpTMx8a6TMfEuSpElh5luSJEmaYjbfklpj\nLlODslY0DOtFXbZd2xPQ9EnG+tsbDWhmjxk23Lah7WlIkrSkmfnWSCUpVrU9C23RKvDfuyRJ9zPz\nLUmSJE0xm29JrTGXqUFZKxqG9aIus/leYpIcm2Rjkqc16yuTfHqBbS9MsvN4ZyhJkjS9zHwvMUnO\nBn4G+EJV/WGSlcBJVXX0iI5v5rurVpn5liSpn5lvLaokOwKHAa8BTuh7apfmKvdNSd7Xt/0tSX66\nWT4/yZVJrk/y2vHOXJIkaTrYfC8txwAXVdXXgDuTHNCMHwy8AdgXeGqSlzTj/ZdJX11VBzfbviXJ\nsnFNWtPLXKYGZa1oGNaLuszme2k5ATi7WT4HeHmzvLaqbm0+F/5jwOHNeP+vYX47yTrgCuCJwN5j\nmK8kSdJU8UN2lojmSvURwP5JCtiW3pXtz2xh89ps35XNvs+uqnuTrAZ2WPBkq0Y0aY3UzB4zm64G\nzc7OArS+Pj/Wlfm43t312dnZTs3H9W6vWy+uL7Q+vzw3N0dbfMPlEpHkdcABVfX6vrHVwBeAtwH7\nAd8E/h54f1V9MsktwLPoXQl/TVUdk2Qf4BrgF6vqki2cpx7Yu8c3+UmSpE7yDZdaTC8Dzt9s7Dzg\neOBK4L3AjcDXq+qTzfPzXfNFwPZJbgT+GLh88aerpaD/SoS0NdaKhmG9qMuMnSwRVfXCLYydDpy+\nlX2e0rf6y4sxL0mSpKXE2IlGytiJJEmaFMZOJEmSpClm8y2pNeYyNShrRcOwXtRlNt+SJEnSmJj5\n1kiZ+ZYkSZOijcy3dzvRIri/hmdmlrc4D0mSpG4xdqKRq6pNjw0b5tqejjrMXKYGZa1oGNaLuszm\nW5IkSRoTM98aqSRlTUmSpEngfb4lSZKkKWbzLak15jI1KGtFw7Be1GU235Jas27duranoAlhrWgY\n1ou6zOZbUmu++93vtj0FTQhrRcOwXtRlNt+SJEnSmNh8S2rN3Nxc21PQhLBWNAzrRV3mrQY1Ur2P\nl5ckSZoM477VoM23JEmSNCbGTiRJkqQxsfmWJEmSxsTmWyOR5EVJbkryz0ne2vZ8tLiSzCW5Nsk1\nSdY2Y8uSXJzk5iSfTbJL3/a/n+SrSdYnOapv/MAk1zV1c1rf+KOSnN3sc3mSJ/c998pm+5uTnDiu\n16zBJfnLJLcnua5vrNX6SLJnkiua5z6WZLvF/SpoEAvUyslJbktydfN4Ud9z1soSleSJSb6Q5MYk\n1yd5czM+ed9bqsqHj0f0oPefuK8By4HtgXXAPm3Py8ei/p3/C7Bss7E/BX6vWX4r8M5meT/gGmA7\nYM+mVubfb/Il4OBm+e+BX2yWXw+8r1l+GXB2s7wM+DqwC/BT88ttfz18PKg+DgdWANd1pT6Ac4Dj\nmuX/C/yXtr9OPhaslZOB/7GFbfe1VpbuA9gNWNEsPw64GdhnEr+3eOVbo3AI8NWqurWqfgycDRzT\n8py0uMKDf3N2DPDhZvnDwLHN8tH0voH9pKrmgK8ChyTZDdipqq5stjuzb5/+Y/0dcESz/IvAxVV1\nd1V9F7gY2HRVTN1QVZcB39lsuO36OAI4t+/8v/aIXqRGYoFagd73mM0dg7WyZFXVhqpa1yx/D1gP\nPJEJ/N5i861R2AP4Zt/6bc2YplcBn0tyZZLXNmMzVXU79L5JAk9oxjevj39txvagVyvz+utm0z5V\ndR9wd5Kf3sqx1H1PaKs+kjwe+E5Vbew71u4jel1aHG9Msi7Jh/piBNaKgF7Ug95vTK6gxZ89D7de\nbL4lPRyHVdWBwC8Db0jyPHoNeb9R3sd0rPdg1ViMuz6socnxPuApVbUC2AC8a4THtlYmXJLH0bsq\n/ZbmCnjbP3uGrhebb43CvwJP7lt/YjOmKVVV32r+/Hfgk/SiR7cnmQFofq13R7P5vwJP6tt9vj4W\nGn/APkm2BXauqruw1iZZa/VRVd8GdkmyzRaOpY6pqn+vJkALnEHv+wtYK0te82bGvwPOqqpPNcMT\n973F5lujcCXw1CTLkzwKOB64oOU5aZEkeWxz5YEkOwJHAdfT+zt/VbPZK4H5b4wXAMc37yLfC3gq\nsLb59eDdSQ5JEuDEzfZ5ZbN8HPCFZvmzwJFJdkmyDDiyGVP3hAdeEWq7PlY3225+frXvAbXSNFDz\nXgLc0CxbK/or4CtV9Z6+scn73tL2u1d9TMeD3hsPbqb3hoa3tT0fH4v6d70XvTvaXEOv6X5bM/7T\nwOebOrgY+Km+fX6f3jvN1wNH9Y0/qznGV4H39I0/Gvh4M34FsGffc69qxv8ZOLHtr4ePLdbI3wL/\nBtwLfAN4Nb27BbRWH03dfqkZPwfYvu2vk48Fa+VM4Lrm+8wn6WV6rZUl/gAOA+7r+/lzddN7tPqz\n5+HUix8vL0mSJI2JsRNJkiRpTGy+JUmSpDGx+ZYkSZLGxOZbkiRJGhObb0mSJGlMbL4lSZKkMbH5\nliRJksbE5luSJEkak/8PDsxiqKvG+woAAAAASUVORK5CYII=\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"parties_table.plot(x=\"State\", y=[\"APC\", \"PDP\"], figsize=(10,25), kind=\"barh\", grid=100)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### States with lowest votes\n",
"\n",
"Lets see what the bottom states with lowest number of votes have to offer"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"HOPE 7435\n",
"UDP 9208\n",
"KOWA 13076\n",
"UPP 18220\n",
"AA 22125\n",
"NCP 24455\n",
"PPN 24475\n",
"ADC 29666\n",
"AD 30673\n",
"CPP 36300\n",
"ACPN 40311\n",
"dtype: int64"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"low_vote_states = vote_sum.sort_values()[:11]\n",
"low_vote_states"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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XmacAVwJvOLSXKkmSpDFbWlomIkb3tbS03Loaadu2dFlmZn5luPkIJu/eJfBi4Jph/hrg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\nTpIkSZLmgIs7SZIkSZoD/z+My2TKYDpX6wAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"low_vote_states.plot(kind=\"bar\", figsize=(15, 5), grid=100)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## HOPE Party\n",
"Lets see the state that voted most for the lowest rank party - HOPE"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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5Tq9+Xlf3GO/sp6Trqn9Xl3Rpwff4CklPkHS1Mnk7uO573BX7Oklrdd1eq/P/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\nCsaNAAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"hope_party = parties_table[['State', 'HOPE']]\n",
"hope_party.plot(x='State', y='HOPE', kind='bar', figsize=(15, 5))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As seen above, the states that voted most for lowest rank party (HOPE) are Ebonyi, Oyo and Rivers."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# What next?\n",
"You can do more with this dataset, but for me that is it on analysing Nigeria 2015 presidential election result with python.\n",
"\n",
"Next, I will do a spatial analysis on thesame election result dataset with QGIS (http://qgis.org/) and Tableau (http://tableau.com/). Note that there are excellent python packages that supports spatial analysis, namely: GeoPandas, PySAL, Pyshp, Shapely, ArcPy, PyQGIS, Fiona, Rasterio, GDAL/OGR etc\n",
"\n",
"So if you are interested in the spatial analysis, click on the link below:-"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"~1~ Spatial Analysis of Nigeria 2015 Presidential Election Result Using QGIS - Desktop Visualization\n",
"\n",
"~2~ Spatial Analysis of Nigeria 2015 Presidential Election Result Using Tableau - Web-based Visualization"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [Root]",
"language": "python",
"name": "Python [Root]"
},
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