library(rio)
link = "https://github.com/jcgcjuan/Magallanes-Clases-/raw/master/Data%20EconoFreedom.xlsx"
freedom=import(link)#eliminando columnas
freedom$CountryID=NULL
freedom$Region=NULL
freedom$`World Rank`=NULL
freedom$`Region Rank`=NULL
freedom$`2019 Score`=NULLmy_na <- is.na(freedom)#omitiendo NAs
(freedom=na.omit(freedom))## Country Name Property Rights
## 1 Afghanistan 19.600000000000001
## 2 Albania 54.8
## 3 Algeria 31.6
## 4 Angola 35.9
## 5 Argentina 47.8
## 6 Armenia 57.2
## 7 Australia 79.099999999999994
## 8 Austria 84.2
## 9 Azerbaijan 59.1
## 10 Bahamas 42.2
## 11 Bahrain 63.5
## 12 Bangladesh 36.1
## 13 Barbados 52.9
## 14 Belarus 55.2
## 15 Belgium 81.3
## 16 Belize 41.7
## 17 Benin 37.200000000000003
## 18 Bhutan 62.5
## 19 Bolivia 20.5
## 20 Bosnia and Herzegovina 40.200000000000003
## 21 Botswana 58.1
## 22 Brazil 57.3
## 23 Brunei Darussalam 64
## 24 Bulgaria 62.5
## 25 Burkina Faso 49.1
## 26 Burma 34.700000000000003
## 27 Burundi 20.6
## 28 Cambodia 37.4
## 29 Cameroon 42.5
## 30 Canada 87
## 31 Cabo Verde 44.1
## 32 Central African Republic 19.600000000000001
## 33 Chad 26.7
## 34 Chile 68.7
## 35 China 49.9
## 36 Colombia 59.2
## 37 Comoros 36.5
## 38 Congo, Democratic Republic of the Congo 25.3
## 39 Congo, Republic of 33.200000000000003
## 40 Costa Rica 58.3
## 41 CĂ´te d'Ivoire 40.9
## 42 Croatia 66
## 43 Cuba 31.6
## 44 Cyprus 73.099999999999994
## 45 Czech Republic 74.8
## 46 Denmark 86.2
## 47 Djibouti 29.7
## 48 Dominica 49.2
## 49 Dominican Republic 50.6
## 50 Ecuador 35.9
## 51 Egypt 37
## 52 El Salvador 37.6
## 53 Equatorial Guinea 29.7
## 54 Eritrea 35.5
## 55 Estonia 81.5
## 56 Eswatini 41.7
## 57 Ethiopia 32.6
## 58 Fiji 67.3
## 59 Finland 89.6
## 60 France 82.5
## 61 Gabon 28.1
## 62 Gambia 39.9
## 63 Georgia 65.900000000000006
## 64 Germany 79.900000000000006
## 65 Ghana 49.1
## 66 Greece 52.4
## 67 Guatemala 40.299999999999997
## 68 Guinea 34.700000000000003
## 69 Guinea-Bissau 32.6
## 70 Guyana 41.7
## 71 Haiti 10.4
## 72 Honduras 43.4
## 73 Hong Kong 93.3
## 74 Hungary 60.9
## 75 Iceland 87.4
## 76 India 57.3
## 77 Indonesia 52.2
## 78 Iran 33.5
## 79 Iraq 37
## 80 Ireland 85.8
## 81 Israel 80
## 82 Italy 71.7
## 83 Jamaica 60.7
## 84 Japan 84.1
## 85 Jordan 58.4
## 86 Kazakhstan 59.3
## 87 Kenya 53.8
## 88 Kiribati 44.1
## 89 Korea, North 31.6
## 90 Korea, South 79.3
## 91 Kosovo 57.2
## 92 Kuwait 52.9
## 93 Kyrgyz Republic 49.9
## 94 Laos 38.799999999999997
## 95 Latvia 67.3
## 96 Lebanon 39.5
## 97 Lesotho 41.5
## 98 Liberia 26.7
## 99 Libya 7.6
## 100 Liechtenstein N/A
## 101 Lithuania 73.599999999999994
## 102 Luxembourg 83
## 103 Macau 60
## 104 Macedonia 65.099999999999994
## 105 Madagascar 33.200000000000003
## 106 Malawi 35.799999999999997
## 107 Malaysia 84.1
## 108 Maldives 43.9
## 109 Mali 33.700000000000003
## 110 Malta 69.8
## 111 Mauritania 27.5
## 112 Mauritius 69.5
## 113 Mexico 59.1
## 114 Micronesia 7.6
## 115 Moldova 55.2
## 116 Mongolia 48.2
## 117 Montenegro 55.4
## 118 Morocco 57.2
## 119 Mozambique 33.9
## 120 Namibia 55.9
## 121 Nepal 39.200000000000003
## 122 Netherlands 88
## 123 New Zealand 95
## 124 Nicaragua 33.4
## 125 Niger 37.200000000000003
## 126 Nigeria 36.5
## 127 Norway 86.1
## 128 Oman 58.1
## 129 Pakistan 41.5
## 130 Panama 60.4
## 131 Papua New Guinea 37.4
## 132 Paraguay 39.5
## 133 Peru 56.1
## 134 Philippines 48.7
## 135 Poland 62.3
## 136 Portugal 71.5
## 137 Qatar 64.5
## 138 Romania 66.7
## 139 Russia 52.4
## 140 Rwanda 72.2
## 141 Saint Lucia 65.900000000000006
## 142 Saint Vincent and the Grenadines 36.5
## 143 Samoa 53.8
## 144 SĂ£o TomĂ© and PrĂncipe 37.4
## 145 Saudi Arabia 55
## 146 Senegal 47.8
## 147 Serbia 50.1
## 148 Seychelles 58.2
## 149 Sierra Leone 35.5
## 150 Singapore 97.4
## 151 Slovakia 68.5
## 152 Slovenia 76.400000000000006
## 153 Solomon Islands 49.9
## 154 Somalia 33.700000000000003
## 155 South Africa 58.8
## 156 Spain 72.900000000000006
## 157 Sri Lanka 44.7
## 158 Sudan 27.5
## 159 Suriname 49.1
## 160 Sweden 89.5
## 161 Switzerland 85.3
## 162 Syria 37
## 163 Taiwan 85.4
## 164 Tajikistan 47.8
## 165 Tanzania 35.4
## 166 Thailand 53.7
## 167 Timor-Leste 29.7
## 168 Togo 35.5
## 169 Tonga 59.2
## 170 Trinidad and Tobago 52.3
## 171 Tunisia 49.2
## 172 Turkey 55.8
## 173 Turkmenistan 31.6
## 174 Uganda 42.2
## 175 Ukraine 43.9
## 176 United Arab Emirates 81.8
## 177 United Kingdom 92.3
## 178 United States 79.3
## 179 Uruguay 68.3
## 180 Uzbekistan 49.8
## 181 Vanuatu 65.900000000000006
## 182 Venezuela 7.6
## 183 Vietnam 49.8
## 184 Yemen 19.600000000000001
## 185 Zambia 45
## 186 Zimbabwe 29.7
## Judical Effectiveness Government Integrity Tax Burden
## 1 29.6 25.2 91.7
## 2 30.6 40.4 86.3
## 3 36.200000000000003 28.9 76.400000000000006
## 4 26.6 20.5 83.9
## 5 44.5 33.5 69.3
## 6 46.3 38.6 84.7
## 7 86.5 79.900000000000006 62.8
## 8 71.3 77.400000000000006 50.5
## 9 53.1 44.7 87.5
## 10 46.9 43.7 97.3
## 11 50.7 53.6 99.7
## 12 34.5 24.4 72.7
## 13 59.9 53.8 70.099999999999994
## 14 51.7 37.700000000000003 89.4
## 15 61.6 72.5 47.1
## 16 46.9 27.2 79.900000000000006
## 17 32.799999999999997 28.1 69.3
## 18 55.4 54.5 83
## 19 12.3 19.7 82.4
## 20 37.9 30.2 84.3
## 21 45.7 52.4 82.7
## 22 51.7 28.1 70.5
## 23 56 43.7 90.7
## 24 41.9 35.1 90.2
## 25 42.9 36.6 81.900000000000006
## 26 18.100000000000001 30.6 86.6
## 27 31 26.2 74
## 28 27.6 16.7 89.7
## 29 31.3 25.5 74.400000000000006
## 30 69.400000000000006 84.6 76.8
## 31 49 43.7 76.400000000000006
## 32 29.6 23.2 65.2
## 33 24.6 23.2 46.1
## 34 56.3 62.3 77.3
## 35 75.2 49.1 70.400000000000006
## 36 34.299999999999997 33.5 74.3
## 37 29.6 24.4 63.9
## 38 30.7 26.2 73.8
## 39 29.6 25.3 59.5
## 40 54 54.5 79.2
## 41 47.8 38.1 77.5
## 42 42.9 38.6 66.400000000000006
## 43 10 37.700000000000003 48.8
## 44 48.1 43.7 74.900000000000006
## 45 47.6 52.1 82.6
## 46 77.8 85.8 42
## 47 18.100000000000001 28.1 76.2
## 48 63.8 54.5 72.099999999999994
## 49 18.100000000000001 23.2 84.6
## 50 20.2 25.3 77
## 51 48.3 29.2 85.2
## 52 29.1 23.4 78.099999999999994
## 53 18.100000000000001 15.8 71.3
## 54 18.100000000000001 19.7 81.400000000000006
## 55 76 73.099999999999994 79.900000000000006
## 56 42.9 35 74.8
## 57 40.9 35.1 77.2
## 58 42.9 23.4 81.099999999999994
## 59 81.2 92.5 66.8
## 60 66.099999999999994 67.900000000000006 48.4
## 61 30.6 35.5 75.8
## 62 42.5 41.2 74.3
## 63 54.6 58.5 87.1
## 64 75.400000000000006 81.3 60.8
## 65 44.2 35.5 78.8
## 66 49.5 37.700000000000003 59.1
## 67 32.299999999999997 26.4 79.2
## 68 32.6 25.5 69.400000000000006
## 69 42.9 25.3 88.8
## 70 42.9 33.200000000000003 67
## 71 25.3 20.3 79.900000000000006
## 72 31 25.3 82.8
## 73 75.3 83.8 93.1
## 74 45.2 35.299999999999997 78.599999999999994
## 75 63.8 83.8 72.7
## 76 61.6 47.8 79.400000000000006
## 77 53.5 39.5 83.7
## 78 41.3 35 80.900000000000006
## 79 12.3 20.3 N/A
## 80 68.400000000000006 78 76.3
## 81 73.400000000000006 67.900000000000006 61.9
## 82 49.8 43.7 55.6
## 83 49.2 45 80.2
## 84 68.5 78 68.2
## 85 52.6 50.3 91.4
## 86 56.1 40.299999999999997 93.4
## 87 46.9 32.1 79.5
## 88 34.299999999999997 35.1 73
## 89 5 24.4 0
## 90 57.5 50.5 64.2
## 91 53.5 44.7 92.5
## 92 43.3 35.299999999999997 97.7
## 93 27.9 27.2 94.1
## 94 42.5 33.5 86.9
## 95 48.4 35.5 77
## 96 26.6 18.2 91.8
## 97 45.7 30.9 59.4
## 98 39 24.2 82.7
## 99 24.4 15.8 N/A
## 100 N/A N/A N/A
## 101 61.2 47.8 86.4
## 102 72.400000000000006 85.8 65.400000000000006
## 103 60 33.200000000000003 77.099999999999994
## 104 60.7 44.7 91.8
## 105 24.4 14.3 91
## 106 40.1 25.2 79.8
## 107 68.2 55.4 85.6
## 108 36.4 33.5 95.8
## 109 33.4 29.6 68.7
## 110 50.4 50.3 64.2
## 111 30.6 30.6 78
## 112 62.1 40.299999999999997 92.1
## 113 34.9 26.3 75.8
## 114 26.6 36.6 92.8
## 115 29.6 25.4 85.4
## 116 23.8 29.8 88.5
## 117 51.8 39.5 85.3
## 118 47.1 39.200000000000003 72.2
## 119 35.200000000000003 28.1 75.5
## 120 54.7 49.8 66.5
## 121 34.700000000000003 26.2 84
## 122 74.7 89.1 51.6
## 123 83.5 96.7 71
## 124 18.7 20.3 76.900000000000006
## 125 31 34.1 76.900000000000006
## 126 34.299999999999997 20.5 85
## 127 81.2 92.3 57.4
## 128 51.6 53.8 97.8
## 129 40.200000000000003 30.6 80.5
## 130 30.1 34.1 85
## 131 49 37.200000000000003 71.8
## 132 30 25.5 96.3
## 133 34 31.8 80.599999999999994
## 134 36.4 30.9 76.900000000000006
## 135 44 49.8 74.900000000000006
## 136 64.3 59.5 59.9
## 137 60 77.400000000000006 99.7
## 138 51.9 39.799999999999997 89.7
## 139 45.1 36.6 89.4
## 140 83.2 67.900000000000006 79.8
## 141 63.8 50.3 76.2
## 142 63.8 50.5 71.2
## 143 31 37.700000000000003 79.900000000000006
## 144 26.6 35.5 87.2
## 145 62.7 49.8 99.8
## 146 40.4 40.299999999999997 70.8
## 147 44.8 37.200000000000003 82
## 148 37.5 39.200000000000003 76.3
## 149 34.5 26.2 87.3
## 150 92.4 95.1 90.4
## 151 37.200000000000003 37.700000000000003 78.599999999999994
## 152 46.5 53.6 58.4
## 153 51.7 33.5 65.5
## 154 26.6 7.9 N/A
## 155 39.299999999999997 39.700000000000003 62.1
## 156 51.4 51.9 62.3
## 157 39.4 28.9 84.9
## 158 22.2 26.2 86.3
## 159 22.2 35.5 70.900000000000006
## 160 84 88 43.2
## 161 82 88 70.5
## 162 24.4 20.3 N/A
## 163 70.099999999999994 69.2 75
## 164 52.1 36.4 91.8
## 165 41.4 33.200000000000003 80.5
## 166 45.9 36.4 81.3
## 167 13.1 32.1 96.3
## 168 29.6 28.1 67.8
## 169 26.6 38.1 85.5
## 170 40.6 32.9 82.3
## 171 42.7 36.6 74.400000000000006
## 172 49.8 41.2 76.400000000000006
## 173 29.8 20.3 95.9
## 174 38.5 25.4 73.3
## 175 31.5 29.6 81.8
## 176 87.1 78.8 99.2
## 177 85.9 83.8 64.7
## 178 78.599999999999994 77.400000000000006 75.099999999999994
## 179 58.9 69.2 77.2
## 180 34.299999999999997 25.2 91.3
## 181 36.4 51.9 97.3
## 182 13.1 7.9 74.7
## 183 40.299999999999997 34 79.7
## 184 22.2 20.3 N/A
## 185 35.6 32.299999999999997 72.3
## 186 24.8 15.8 62.3
## Gov't Spending Fiscal Health Business Freedom Labor Freedom
## 1 80.3 99.3 49.2 60.4
## 2 73.900000000000006 80.599999999999994 69.3 52.7
## 3 48.7 18.7 61.6 49.9
## 4 80.7 58.2 55.7 58.8
## 5 49.5 33 56.4 46.9
## 6 79 53 78.3 71.400000000000006
## 7 60.1 86.2 88.3 84.1
## 8 24.5 85.5 74.900000000000006 68.7
## 9 59.5 89.4 69.5 63.9
## 10 86.8 65.7 68.5 67.5
## 11 62.7 3.7 71.400000000000006 71.099999999999994
## 12 94.5 77.599999999999994 50.9 68.2
## 13 65 79.5 69.8 59.9
## 14 41.3 85.4 75 75.3
## 15 15.2 73.400000000000006 78.099999999999994 61
## 16 65.900000000000006 39.1 61.8 54.8
## 17 83.4 27.9 62.4 53.8
## 18 71.599999999999994 77.599999999999994 68.7 79.5
## 19 49.3 17.600000000000001 58.8 52.9
## 20 46.1 96.6 49.7 67
## 21 65.900000000000006 94.6 68.7 68.2
## 22 55.2 5.9 57.9 51.9
## 23 59.9 20 80.2 90.8
## 24 63.9 98.8 62.7 68.400000000000006
## 25 80 61.8 51.6 52.3
## 26 85.4 78.3 52.8 65.7
## 27 83.3 23.3 50.3 67.5
## 28 85.9 89.1 29.9 63
## 29 87.5 58.4 44.4 47.8
## 30 51.3 83.1 81.900000000000006 73.7
## 31 71.2 59.7 65.2 55.7
## 32 94.2 94.3 24.2 40.1
## 33 92.4 85.2 28.1 43.2
## 34 81 89 76.599999999999994 65
## 35 70.099999999999994 76 56.2 64.2
## 36 75 79.2 71.400000000000006 78.5
## 37 73.400000000000006 91.7 57.2 60.3
## 38 93.9 96.9 53.2 41.9
## 39 40.6 0 38.200000000000003 35.799999999999997
## 40 88.4 42.5 67.2 55.2
## 41 83.9 74.3 61 52.5
## 42 33.4 85.4 60.7 44
## 43 0 15.6 20 20
## 44 55.2 80.3 76.900000000000006 59.5
## 45 52.1 97.6 72.400000000000006 78.099999999999994
## 46 14.4 96.7 90.7 86.4
## 47 27.3 18.100000000000001 54.7 60.4
## 48 53.5 84.7 70.7 60.4
## 49 90.3 89.9 51.9 57.6
## 50 55.5 32.1 54.1 48.2
## 51 68.099999999999994 0 65.900000000000006 51.6
## 52 86.3 81.900000000000006 57.2 53.1
## 53 67.599999999999994 16.399999999999999 37.6 32.700000000000003
## 54 73.900000000000006 0 17.7 70
## 55 51.1 99.8 75.3 57.2
## 56 65.599999999999994 18.3 59.2 67.5
## 57 90.4 83.3 48.6 58
## 58 71.7 82.4 63 72.900000000000006
## 59 7.2 86.4 89.4 50.3
## 60 3.9 64.900000000000006 81.2 45.2
## 61 86.6 82.1 52.1 53
## 62 70.7 0 54 67.400000000000006
## 63 73.599999999999994 93.9 85.8 76.599999999999994
## 64 42.3 91.8 83.3 52.8
## 65 82 23.9 56.5 59.9
## 66 23.3 79 74.099999999999994 52.5
## 67 95.6 96.2 53.6 48.7
## 68 89.8 87.2 54.6 54.9
## 69 86.7 81.400000000000006 35.9 61.2
## 70 69.400000000000006 77.599999999999994 59.3 62
## 71 88.3 95.9 36.200000000000003 62.6
## 72 78.2 95.9 56.9 32
## 73 90.3 100 96.4 89.2
## 74 31.7 85 61.1 64.7
## 75 44 96.7 88.4 64.099999999999994
## 76 77.3 14.7 57.1 41.8
## 77 91.4 88.1 69.3 49.3
## 78 89.8 89.5 62.2 50.7
## 79 52.8 13.3 54.4 53.1
## 80 77.400000000000006 89 83.1 75.3
## 81 52.4 85.3 71.400000000000006 65.099999999999994
## 82 26.5 71.3 71.7 51.1
## 83 76 80 78 73.599999999999994
## 84 55 55.7 80.5 79
## 85 73.400000000000006 60.6 61.8 52.7
## 86 83.7 41 73.900000000000006 86.2
## 87 77.8 13.8 55.8 63.4
## 88 0 98.6 41.9 50.7
## 89 0 0 5 5
## 90 68.599999999999994 96.8 91.3 57.4
## 91 77.7 96 73.8 64.900000000000006
## 92 17.3 99.1 57.4 61.7
## 93 54.2 78.400000000000006 73.400000000000006 79.8
## 94 85.3 66.5 60.1 60.1
## 95 57.1 96.9 77.5 73.3
## 96 75.599999999999994 0 47.9 46.5
## 97 33 63.5 53.3 58.8
## 98 62.1 69.099999999999994 50.6 38.299999999999997
## 99 0 20 40.200000000000003 51.3
## 100 N/A N/A N/A N/A
## 101 65.099999999999994 97.3 75.2 63.6
## 102 46.6 98.9 68.8 45.9
## 103 90.4 100 60 50
## 104 70 82.9 80.2 71.5
## 105 91.8 85.5 47.3 44.6
## 106 70.3 19.100000000000001 41.7 64
## 107 83.2 82.4 83.9 74.400000000000006
## 108 60.8 10.7 78.3 70.8
## 109 85.4 84.2 53.8 52.2
## 110 56.1 94.5 67.099999999999994 61.3
## 111 74.2 80.599999999999994 61.9 51.5
## 112 80.3 73.599999999999994 79.8 60.8
## 113 78.2 83.2 67.8 58.6
## 114 0 98.8 57.4 71.900000000000006
## 115 59.1 92 67 39
## 116 63.1 6.2 66 75
## 117 32.6 23.2 73.3 73.400000000000006
## 118 72.7 66.900000000000006 70.3 33.1
## 119 66.900000000000006 16.600000000000001 57.1 42
## 120 48.9 15.7 65.8 85.1
## 121 83.7 98.5 61.8 47.9
## 122 42.9 93.3 81.400000000000006 60.3
## 123 50.4 98.6 91 86.7
## 124 79.099999999999994 93.9 56 55.8
## 125 75.599999999999994 22.2 56.3 48.2
## 126 96.5 68.2 51.2 83.3
## 127 25.3 97.3 89.4 53.7
## 128 32.5 16.100000000000001 75.2 57.3
## 129 87.6 49.2 56.1 41.8
## 130 85.3 91.3 73.599999999999994 43.4
## 131 89.1 75.2 62.2 72.599999999999994
## 132 78.900000000000006 96.3 61.5 29.2
## 133 86.1 88.5 67.8 63.5
## 134 88.7 97.1 61.3 57.9
## 135 48.8 86.4 65.400000000000006 63.9
## 136 35.6 69.8 79.7 44.3
## 137 56.8 94 71.2 65.900000000000006
## 138 69 89.3 63.1 64.5
## 139 62.3 86.6 78.400000000000006 52.5
## 140 79.400000000000006 86.3 56.2 82.2
## 141 79.3 81.3 76.3 69.2
## 142 74.3 85 76.5 73.5
## 143 62.3 93.6 77 78.2
## 144 67 62.3 65.099999999999994 42.7
## 145 57.5 19.399999999999999 72.3 63.3
## 146 73.3 60 53.3 39.4
## 147 45.1 90.1 72.900000000000006 67.400000000000006
## 148 60.3 92 63.3 63.2
## 149 84.4 13.2 44.9 29.3
## 150 90.7 80 90.8 91
## 151 46.1 87.2 61.3 53.4
## 152 38.299999999999997 82.6 79.3 61.2
## 153 36.5 89.4 68.599999999999994 72
## 154 N/A N/A 31.7 N/A
## 155 67.599999999999994 62.6 64.3 59.1
## 156 46.2 51.1 66.8 57.8
## 157 88.3 30.4 75.099999999999994 58.8
## 158 96.6 76.099999999999994 52.1 59
## 159 77.2 9.6 48.3 73.5
## 160 26.7 96.6 88 53.9
## 161 64.8 96.3 75.400000000000006 72.5
## 162 N/A N/A 49.6 58.2
## 163 90.6 91.6 93.2 60.9
## 164 64.599999999999994 60.3 67.3 49.2
## 165 90.3 85.2 46.6 66.2
## 166 85.8 96.5 82.5 63.9
## 167 0.9 20 60.5 58.8
## 168 77 24.5 50.4 46.7
## 169 40.9 93.4 75.3 69.900000000000006
## 170 61.9 16.600000000000001 67.8 75.599999999999994
## 171 74.400000000000006 37.9 76.7 50.3
## 172 65.099999999999994 92.2 66 49.2
## 173 92 92.3 30 20
## 174 88.7 68.599999999999994 46.3 83.2
## 175 46.9 82.6 66.099999999999994 46.7
## 176 68.8 88.9 79.900000000000006 81.099999999999994
## 177 48.2 68.599999999999994 92.9 73.5
## 178 57.1 53.1 83.8 89.4
## 179 67.5 69.900000000000006 74.3 71.900000000000006
## 180 67.400000000000006 98.7 72.5 58.7
## 181 54.1 15.3 52.4 58.8
## 182 58.1 17.600000000000001 33.9 28
## 183 74.099999999999994 40.700000000000003 63.5 62.8
## 184 83.7 0 45.1 49.8
## 185 80.099999999999994 12.3 71.099999999999994 46
## 186 74.5 23.7 33.4 43.3
## Monetary Freedom Trade Freedom Investment Freedom Financial Freedom
## 1 76.7 66 10 10
## 2 81.5 87.8 70 70
## 3 74.900000000000006 67.400000000000006 30 30
## 4 55.4 61.2 30 40
## 5 60.2 70 55 60
## 6 77.8 80.8 75 70
## 7 86.6 87.6 80 90
## 8 81.5 86 90 70
## 9 63 74.599999999999994 60 60
## 10 78.099999999999994 47.8 50 60
## 11 81.599999999999994 83.8 75 80
## 12 69.900000000000006 63.6 45 30
## 13 78.3 56.6 70 60
## 14 67 76.400000000000006 30 10
## 15 76.099999999999994 86 85 70
## 16 78.7 64 55 50
## 17 86.4 61.8 70 50
## 18 72.599999999999994 79.400000000000006 20 30
## 19 68.8 70.400000000000006 15 40
## 20 83.1 82.6 65 60
## 21 78.8 83.8 65 70
## 22 75.5 69 50 50
## 23 76.5 84 65 50
## 24 88 86 70 60
## 25 86.2 65.2 65 40
## 26 69.599999999999994 70.8 30 20
## 27 62.2 68.2 50 30
## 28 79.400000000000006 65.400000000000006 60 50
## 29 84 53.4 30 50
## 30 77.2 86.8 80 80
## 31 84.1 68.2 80 60
## 32 72.3 51 45 30
## 33 82.3 47.2 60 40
## 34 84.5 88.8 85 70
## 35 71.900000000000006 73 25 20
## 36 75.599999999999994 76 80 70
## 37 82.8 70 45 30
## 38 49.1 62.6 30 20
## 39 82.6 56.8 45 30
## 40 83.2 81.400000000000006 70 50
## 41 74.2 73.599999999999994 75 50
## 42 78.5 86 75 60
## 43 65.599999999999994 64 10 10
## 44 84 86 75 60
## 45 81.5 86 80 80
## 46 84.1 86 90 80
## 47 72.7 50.4 80 50
## 48 85.7 68.2 70 30
## 49 79.7 75.8 70 40
## 50 73.5 66.400000000000006 35 40
## 51 62.3 71.8 60 50
## 52 79 81.400000000000006 75 60
## 53 83.7 48.8 40 30
## 54 61 69.2 0 20
## 55 79.599999999999994 86 90 70
## 56 73.7 87.6 50 40
## 57 60.8 60.8 35 20
## 58 73.5 62.8 55 50
## 59 84.8 86 85 80
## 60 79.099999999999994 81 75 70
## 61 80 51.2 60 40
## 62 62.4 61.6 65 50
## 63 76 88.6 80 70
## 64 77.900000000000006 86 80 70
## 65 66.3 63.4 70 60
## 66 79.099999999999994 81 55 50
## 67 77 82.2 70 50
## 68 66.400000000000006 63.2 50 40
## 69 78.099999999999994 55.6 30 30
## 70 76.900000000000006 66.8 55 30
## 71 66.5 72 45 30
## 72 73 79.400000000000006 65 60
## 73 86.4 95 90 90
## 74 81.8 86 80 70
## 75 81.7 87 85 70
## 76 72.400000000000006 72.400000000000006 40 40
## 77 77.400000000000006 79.8 45 60
## 78 60.1 54.6 5 10
## 79 81.400000000000006 N/A N/A N/A
## 80 87 86 90 70
## 81 86.2 84.4 75 70
## 82 84 86 85 50
## 83 82.6 68.400000000000006 80 50
## 84 85.9 80 70 60
## 85 85 81.400000000000006 70 60
## 86 70.900000000000006 80 50 50
## 87 72.7 60.4 55 50
## 88 81.099999999999994 53.2 25 30
## 89 0 0 0 0
## 90 82 80.400000000000006 70 70
## 91 78.3 70.8 65 30
## 92 70.599999999999994 79 55 60
## 93 74.400000000000006 78.599999999999994 60 50
## 94 78.5 81.8 35 20
## 95 81.099999999999994 86 85 60
## 96 78.099999999999994 79 60 50
## 97 75 81 55 40
## 98 68.900000000000006 60.1 55 20
## 99 52.8 N/A 5 N/A
## 100 N/A N/A 85 80
## 101 84.6 86 80 70
## 102 82.6 86 95 80
## 103 76.5 90 85 70
## 104 78.7 82 65 60
## 105 72.400000000000006 69.2 55 50
## 106 65.5 75.400000000000006 50 50
## 107 78.599999999999994 82 60 50
## 108 81 62.6 35 30
## 109 81.599999999999994 69.8 65 40
## 110 78.2 86 85 60
## 111 81.2 62.6 50 40
## 112 79.400000000000006 88.4 80 70
## 113 75.900000000000006 81.400000000000006 75 60
## 114 85.8 80.599999999999994 35 30
## 115 73.5 78 55 50
## 116 77.8 75.8 50 60
## 117 81.599999999999994 84.7 75 50
## 118 83.5 77.400000000000006 65 70
## 119 65.400000000000006 78 35 50
## 120 74.400000000000006 83 65 40
## 121 69.400000000000006 60.4 10 30
## 122 84 86 90 80
## 123 87.5 92.4 80 80
## 124 72.7 76 60 50
## 125 76.7 65.8 55 40
## 126 65 62.4 45 40
## 127 75.400000000000006 83.2 75 60
## 128 77.7 87 65 60
## 129 72.599999999999994 64.8 55 40
## 130 79.400000000000006 79.2 75 70
## 131 70 80.900000000000006 25 30
## 132 72.8 76.599999999999994 75 60
## 133 83.9 86.4 75 60
## 134 69.599999999999994 78.2 60 60
## 135 82.1 86 80 70
## 136 83 86 70 60
## 137 78.400000000000006 83.2 60 60
## 138 82.7 86 70 50
## 139 65.099999999999994 77.8 30 30
## 140 76.099999999999994 70.400000000000006 60 40
## 141 83.9 73.2 65 40
## 142 82.2 66.599999999999994 70 40
## 143 83.5 63.8 55 30
## 144 70.5 64.2 60 30
## 145 78.099999999999994 76 45 50
## 146 78.2 72 60 40
## 147 80 77 70 50
## 148 80 81.400000000000006 55 30
## 149 65 69.400000000000006 60 20
## 150 85.3 94.8 85 80
## 151 78.599999999999994 86 75 70
## 152 83.6 86 70 50
## 153 86 56.8 15 30
## 154 N/A N/A N/A N/A
## 155 75.2 76 45 50
## 156 87.5 86 85 70
## 157 70.099999999999994 76.2 40 40
## 158 56.9 45 5 20
## 159 56 64.599999999999994 40 30
## 160 82 86 85 80
## 161 85.2 87.4 85 90
## 162 48.3 47 0 N/A
## 163 84.4 87 60 60
## 164 68.5 73.599999999999994 25 30
## 165 70.400000000000006 67.8 55 50
## 166 75.2 83 55 60
## 167 79.5 75 45 20
## 168 79.099999999999994 69.400000000000006 65 30
## 169 69.400000000000006 73.599999999999994 40 20
## 170 75.099999999999994 68.400000000000006 60 50
## 171 76 71.400000000000006 45 30
## 172 70 79.599999999999994 70 60
## 173 73.400000000000006 76 10 10
## 174 80.099999999999994 75.400000000000006 55 40
## 175 58.6 75 35 30
## 176 80.900000000000006 84.4 40 60
## 177 81.2 86 90 80
## 178 76.599999999999994 86.6 85 80
## 179 72.900000000000006 78.599999999999994 85 30
## 180 58.9 62.6 10 10
## 181 75 64.400000000000006 65 40
## 182 0 60 0 10
## 183 68.900000000000006 79.2 30 40
## 184 61.5 71.400000000000006 50 N/A
## 185 70.3 72.599999999999994 55 50
## 186 72.400000000000006 70 25 10#cambiando a numerico
str(freedom)## 'data.frame': 186 obs. of 13 variables:
## $ Country Name : chr "Afghanistan" "Albania" "Algeria" "Angola" ...
## $ Property Rights : chr "19.600000000000001" "54.8" "31.6" "35.9" ...
## $ Judical Effectiveness: chr "29.6" "30.6" "36.200000000000003" "26.6" ...
## $ Government Integrity : chr "25.2" "40.4" "28.9" "20.5" ...
## $ Tax Burden : chr "91.7" "86.3" "76.400000000000006" "83.9" ...
## $ Gov't Spending : chr "80.3" "73.900000000000006" "48.7" "80.7" ...
## $ Fiscal Health : chr "99.3" "80.599999999999994" "18.7" "58.2" ...
## $ Business Freedom : chr "49.2" "69.3" "61.6" "55.7" ...
## $ Labor Freedom : chr "60.4" "52.7" "49.9" "58.8" ...
## $ Monetary Freedom : chr "76.7" "81.5" "74.900000000000006" "55.4" ...
## $ Trade Freedom : chr "66" "87.8" "67.400000000000006" "61.2" ...
## $ Investment Freedom : chr "10" "70" "30" "30" ...
## $ Financial Freedom : chr "10" "70" "30" "40" ...freedom[,c(2:12)]=lapply(freedom[,c(2:12)],as.numeric)## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercion
## Warning in lapply(freedom[, c(2:12)], as.numeric): NAs introduced by coercionstr(freedom)## 'data.frame': 186 obs. of 13 variables:
## $ Country Name : chr "Afghanistan" "Albania" "Algeria" "Angola" ...
## $ Property Rights : num 19.6 54.8 31.6 35.9 47.8 57.2 79.1 84.2 59.1 42.2 ...
## $ Judical Effectiveness: num 29.6 30.6 36.2 26.6 44.5 46.3 86.5 71.3 53.1 46.9 ...
## $ Government Integrity : num 25.2 40.4 28.9 20.5 33.5 38.6 79.9 77.4 44.7 43.7 ...
## $ Tax Burden : num 91.7 86.3 76.4 83.9 69.3 84.7 62.8 50.5 87.5 97.3 ...
## $ Gov't Spending : num 80.3 73.9 48.7 80.7 49.5 79 60.1 24.5 59.5 86.8 ...
## $ Fiscal Health : num 99.3 80.6 18.7 58.2 33 53 86.2 85.5 89.4 65.7 ...
## $ Business Freedom : num 49.2 69.3 61.6 55.7 56.4 78.3 88.3 74.9 69.5 68.5 ...
## $ Labor Freedom : num 60.4 52.7 49.9 58.8 46.9 71.4 84.1 68.7 63.9 67.5 ...
## $ Monetary Freedom : num 76.7 81.5 74.9 55.4 60.2 77.8 86.6 81.5 63 78.1 ...
## $ Trade Freedom : num 66 87.8 67.4 61.2 70 80.8 87.6 86 74.6 47.8 ...
## $ Investment Freedom : num 10 70 30 30 55 75 80 90 60 50 ...
## $ Financial Freedom : chr "10" "70" "30" "40" ...row.names(freedom)=freedom$Countryfreedom=na.omit(freedom)library(cluster)
g.dist = daisy(freedom[,c(2:12)], metric="gower")pam.resultado=pam(g.dist,4,cluster.only = F)
freedom$clusterPT=pam.resultado$clusterlibrary(factoextra)## Loading required package: ggplot2## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBafviz_cluster(object = list(data=g.dist, cluster = freedom$clusterPT),
geom = c("text"),
ellipse.type = "convex")
fviz_nbclust(freedom[,c(2:12)], pam,diss=g.dist,method = "gap_stat",k.max = 10,verbose = F)
#Respuesta: Si es optimo usar cuatro clusters
res.pam = pam(g.dist,4,cluster.only = F)fviz_silhouette(res.pam)## cluster size ave.sil.width
## 1 1 41 0.29
## 2 2 68 0.19
## 3 3 43 0.14
## 4 4 28 0.37
#Respuesta: b) Se podrĂa intentar analizar mediante otras tecnicas como la jerarquica para saber si la silueta es menor