LINKGUERRAS = "https://en.wikipedia.org/wiki/List_of_wars_by_death_toll"
library(htmltab)
ancient = htmltab(doc = LINKGUERRAS,
which ='//*[@id="mw-content-text"]/div/table[4]')
medieval = htmltab(doc = LINKGUERRAS,
which ='//*[@id="mw-content-text"]/div/table[6]')## Warning: Columns [Notes] seem to have no data and are removed. Use
## rm_nodata_cols = F to suppress this behaviormodern = htmltab(doc = LINKGUERRAS,
which ='//*[@id="mw-content-text"]/div/table[7]')## Warning: Columns [Notes] seem to have no data and are removed. Use
## rm_nodata_cols = F to suppress this behaviornames(ancient)## [1] "War" "Deathrange" "Date" "Combatants" "Location"
## [6] "Notes"names(medieval)## [1] "War" "Deathrange" "Date" "Combatants" "Location"names(modern)## [1] "War" "Deathrange" "Date" "Combatants" "Location"guerras1=ancient[,c("War","Location")]
guerras2=medieval[,c("War","Location")]
guerras3=modern[,c("War","Location")]guerras=rbind(guerras1,guerras2,guerras3)str(guerras)## 'data.frame': 166 obs. of 2 variables:
## $ War : chr "Conquests of Cyrus the Great" "Greco–Persian Wars" "Samnite Wars" "Wars of Alexander the Great" ...
## $ Location: chr "Middle East" "Greece" "Italy" "Middle East / North Africa / Central Asia / India" ...table(guerras$Location)##
## Afghanistan
## 3
## Algeria
## 3
## Americas
## 1
## Angola
## 2
## Balkan Peninsula
## 1
## Bangladesh
## 1
## Bosnia
## 1
## British Isles
## 1
## Burundi
## 1
## Caucasus region
## 1
## Central Africa
## 2
## China
## 10
## China, Korea
## 1
## China, Vietnam
## 1
## Colombia
## 3
## Congo
## 4
## Crimean Peninsula
## 1
## Cuba
## 2
## East Asia
## 1
## Eastern Europe
## 4
## Eastern Europe / Middle East / North Africa
## 1
## England
## 2
## England / Wales
## 1
## Ethiopia
## 2
## Eurasia
## 2
## Europe
## 4
## Europe / Americas
## 2
## Europe / Middle East ("Holy Land")
## 1
## Finland
## 1
## France
## 3
## Germany
## 1
## Gran Chaco
## 1
## Greece
## 3
## Haiti
## 1
## Iberian Peninsula
## 1
## India
## 4
## India-Bangladesh
## 1
## Indonesia
## 1
## Iraq
## 5
## Italy
## 1
## Korea
## 3
## Laos
## 1
## Lebanon
## 1
## Libya
## 1
## Madagascar
## 1
## Manchuria
## 1
## Mexico
## 4
## Middle East
## 7
## Middle East / North Africa
## 1
## Middle East / North Africa / Central Asia / India
## 1
## Middle East / North Africa / Southern Europe
## 1
## Middle East/North Africa
## 1
## Mozambique
## 1
## Myanmar
## 1
## Nigeria
## 2
## North Africa
## 1
## North America
## 1
## North India / Pakistan
## 1
## Northeast India
## 2
## Northern China
## 1
## Northern Europe
## 1
## Pakistan
## 1
## Patagonia
## 1
## Peru
## 2
## Philippines
## 3
## Russia
## 2
## Rwanda
## 1
## Scotland / England
## 1
## Sierra Leone
## 1
## Somalia
## 1
## South Africa
## 1
## South America
## 1
## Southeast Asia
## 3
## Southeast Europe
## 1
## Southern Africa
## 1
## Southern Europe
## 1
## Southern Europe / North Africa
## 2
## Spain
## 2
## Sri Lanka
## 1
## Sudan
## 3
## Syria
## 1
## Tunisia
## 1
## Uganda
## 1
## USA
## 1
## Venezuela
## 1
## Vietnam
## 1
## Western Europe
## 4
## Western Europe / North Africa
## 2
## Worldwide
## 7
## Yemen
## 2library(questionr)
library(magrittr)
guerrasTable=freq(guerras$Location,
total = F,
exclude = c(NA)) %>% data.frame()
guerrasTable=data.frame(variable=row.names(guerrasTable),
guerrasTable,
row.names = NULL)
names(guerrasTable)=c("Paises","Cantidad", "Porcentaje")guerrasTable## Paises Cantidad Porcentaje
## 1 Afghanistan 3 1.8
## 2 Algeria 3 1.8
## 3 Americas 1 0.6
## 4 Angola 2 1.2
## 5 Balkan Peninsula 1 0.6
## 6 Bangladesh 1 0.6
## 7 Bosnia 1 0.6
## 8 British Isles 1 0.6
## 9 Burundi 1 0.6
## 10 Caucasus region 1 0.6
## 11 Central Africa 2 1.2
## 12 China 10 6.0
## 13 China, Korea 1 0.6
## 14 China, Vietnam 1 0.6
## 15 Colombia 3 1.8
## 16 Congo 4 2.4
## 17 Crimean Peninsula 1 0.6
## 18 Cuba 2 1.2
## 19 East Asia 1 0.6
## 20 Eastern Europe 4 2.4
## 21 Eastern Europe / Middle East / North Africa 1 0.6
## 22 England 2 1.2
## 23 England / Wales 1 0.6
## 24 Ethiopia 2 1.2
## 25 Eurasia 2 1.2
## 26 Europe 4 2.4
## 27 Europe / Americas 2 1.2
## 28 Europe / Middle East ("Holy Land") 1 0.6
## 29 Finland 1 0.6
## 30 France 3 1.8
## 31 Germany 1 0.6
## 32 Gran Chaco 1 0.6
## 33 Greece 3 1.8
## 34 Haiti 1 0.6
## 35 Iberian Peninsula 1 0.6
## 36 India 4 2.4
## 37 India-Bangladesh 1 0.6
## 38 Indonesia 1 0.6
## 39 Iraq 5 3.0
## 40 Italy 1 0.6
## 41 Korea 3 1.8
## 42 Laos 1 0.6
## 43 Lebanon 1 0.6
## 44 Libya 1 0.6
## 45 Madagascar 1 0.6
## 46 Manchuria 1 0.6
## 47 Mexico 4 2.4
## 48 Middle East 7 4.2
## 49 Middle East / North Africa 1 0.6
## 50 Middle East / North Africa / Central Asia / India 1 0.6
## 51 Middle East / North Africa / Southern Europe 1 0.6
## 52 Middle East/North Africa 1 0.6
## 53 Mozambique 1 0.6
## 54 Myanmar 1 0.6
## 55 Nigeria 2 1.2
## 56 North Africa 1 0.6
## 57 North America 1 0.6
## 58 North India / Pakistan 1 0.6
## 59 Northeast India 2 1.2
## 60 Northern China 1 0.6
## 61 Northern Europe 1 0.6
## 62 Pakistan 1 0.6
## 63 Patagonia 1 0.6
## 64 Peru 2 1.2
## 65 Philippines 3 1.8
## 66 Russia 2 1.2
## 67 Rwanda 1 0.6
## 68 Scotland / England 1 0.6
## 69 Sierra Leone 1 0.6
## 70 Somalia 1 0.6
## 71 South Africa 1 0.6
## 72 South America 1 0.6
## 73 Southeast Asia 3 1.8
## 74 Southeast Europe 1 0.6
## 75 Southern Africa 1 0.6
## 76 Southern Europe 1 0.6
## 77 Southern Europe / North Africa 2 1.2
## 78 Spain 2 1.2
## 79 Sri Lanka 1 0.6
## 80 Sudan 3 1.8
## 81 Syria 1 0.6
## 82 Tunisia 1 0.6
## 83 Uganda 1 0.6
## 84 USA 1 0.6
## 85 Venezuela 1 0.6
## 86 Vietnam 1 0.6
## 87 Western Europe 4 2.4
## 88 Western Europe / North Africa 2 1.2
## 89 Worldwide 7 4.2
## 90 Yemen 2 1.2library(ggplot2)
mititulo="Ubicacion de las Guerras en la historia"
misubtitulo="Solo con mas 25000 muertos"
base = ggplot(data=guerrasTable,aes(x=Paises,
y=Cantidad))
bar1 = base + geom_bar(stat='identity')
bar1 = bar1 + labs(x="Pais/zona", y="Cantidad",
title=mititulo,
subtitle = misubtitulo,
caption = "Fuente: Wikipedia")
bar1= bar1 + theme(axis.text.x =
element_text(angle = 0,
size=10,
hjust = 1))
bar1 + theme(axis.text.x = element_text(angle = 25,size=5,hjust = 1))
base = ggplot(data=guerrasTable,
aes(x=reorder(Paises,Cantidad),
y=Cantidad))
bar2 = base + geom_bar(stat='identity') bar2
library(qcc)## Package 'qcc' version 2.7## Type 'citation("qcc")' for citing this R package in publications.pareto.chart(table(guerras$Location))
##
## Pareto chart analysis for table(guerras$Location)
## Frequency
## China 10.0000000
## Middle East 7.0000000
## Worldwide 7.0000000
## Iraq 5.0000000
## Congo 4.0000000
## Eastern Europe 4.0000000
## Europe 4.0000000
## India 4.0000000
## Mexico 4.0000000
## Western Europe 4.0000000
## Afghanistan 3.0000000
## Algeria 3.0000000
## Colombia 3.0000000
## France 3.0000000
## Greece 3.0000000
## Korea 3.0000000
## Philippines 3.0000000
## Southeast Asia 3.0000000
## Sudan 3.0000000
## Angola 2.0000000
## Central Africa 2.0000000
## Cuba 2.0000000
## England 2.0000000
## Ethiopia 2.0000000
## Eurasia 2.0000000
## Europe / Americas 2.0000000
## Nigeria 2.0000000
## Northeast India 2.0000000
## Peru 2.0000000
## Russia 2.0000000
## Southern Europe / North Africa 2.0000000
## Spain 2.0000000
## Western Europe / North Africa 2.0000000
## Yemen 2.0000000
## Americas 1.0000000
## Balkan Peninsula 1.0000000
## Bangladesh 1.0000000
## Bosnia 1.0000000
## British Isles 1.0000000
## Burundi 1.0000000
## Caucasus region 1.0000000
## China, Korea 1.0000000
## China, Vietnam 1.0000000
## Crimean Peninsula 1.0000000
## East Asia 1.0000000
## Eastern Europe / Middle East / North Africa 1.0000000
## England / Wales 1.0000000
## Europe / Middle East ("Holy Land") 1.0000000
## Finland 1.0000000
## Germany 1.0000000
## Gran Chaco 1.0000000
## Haiti 1.0000000
## Iberian Peninsula 1.0000000
## India-Bangladesh 1.0000000
## Indonesia 1.0000000
## Italy 1.0000000
## Laos 1.0000000
## Lebanon 1.0000000
## Libya 1.0000000
## Madagascar 1.0000000
## Manchuria 1.0000000
## Middle East / North Africa 1.0000000
## Middle East / North Africa / Central Asia / India 1.0000000
## Middle East / North Africa / Southern Europe 1.0000000
## Middle East/North Africa 1.0000000
## Mozambique 1.0000000
## Myanmar 1.0000000
## North Africa 1.0000000
## North America 1.0000000
## North India / Pakistan 1.0000000
## Northern China 1.0000000
## Northern Europe 1.0000000
## Pakistan 1.0000000
## Patagonia 1.0000000
## Rwanda 1.0000000
## Scotland / England 1.0000000
## Sierra Leone 1.0000000
## Somalia 1.0000000
## South Africa 1.0000000
## South America 1.0000000
## Southeast Europe 1.0000000
## Southern Africa 1.0000000
## Southern Europe 1.0000000
## Sri Lanka 1.0000000
## Syria 1.0000000
## Tunisia 1.0000000
## Uganda 1.0000000
## USA 1.0000000
## Venezuela 1.0000000
## Vietnam 1.0000000
##
## Pareto chart analysis for table(guerras$Location)
## Cum.Freq.
## China 10.0000000
## Middle East 17.0000000
## Worldwide 24.0000000
## Iraq 29.0000000
## Congo 33.0000000
## Eastern Europe 37.0000000
## Europe 41.0000000
## India 45.0000000
## Mexico 49.0000000
## Western Europe 53.0000000
## Afghanistan 56.0000000
## Algeria 59.0000000
## Colombia 62.0000000
## France 65.0000000
## Greece 68.0000000
## Korea 71.0000000
## Philippines 74.0000000
## Southeast Asia 77.0000000
## Sudan 80.0000000
## Angola 82.0000000
## Central Africa 84.0000000
## Cuba 86.0000000
## England 88.0000000
## Ethiopia 90.0000000
## Eurasia 92.0000000
## Europe / Americas 94.0000000
## Nigeria 96.0000000
## Northeast India 98.0000000
## Peru 100.0000000
## Russia 102.0000000
## Southern Europe / North Africa 104.0000000
## Spain 106.0000000
## Western Europe / North Africa 108.0000000
## Yemen 110.0000000
## Americas 111.0000000
## Balkan Peninsula 112.0000000
## Bangladesh 113.0000000
## Bosnia 114.0000000
## British Isles 115.0000000
## Burundi 116.0000000
## Caucasus region 117.0000000
## China, Korea 118.0000000
## China, Vietnam 119.0000000
## Crimean Peninsula 120.0000000
## East Asia 121.0000000
## Eastern Europe / Middle East / North Africa 122.0000000
## England / Wales 123.0000000
## Europe / Middle East ("Holy Land") 124.0000000
## Finland 125.0000000
## Germany 126.0000000
## Gran Chaco 127.0000000
## Haiti 128.0000000
## Iberian Peninsula 129.0000000
## India-Bangladesh 130.0000000
## Indonesia 131.0000000
## Italy 132.0000000
## Laos 133.0000000
## Lebanon 134.0000000
## Libya 135.0000000
## Madagascar 136.0000000
## Manchuria 137.0000000
## Middle East / North Africa 138.0000000
## Middle East / North Africa / Central Asia / India 139.0000000
## Middle East / North Africa / Southern Europe 140.0000000
## Middle East/North Africa 141.0000000
## Mozambique 142.0000000
## Myanmar 143.0000000
## North Africa 144.0000000
## North America 145.0000000
## North India / Pakistan 146.0000000
## Northern China 147.0000000
## Northern Europe 148.0000000
## Pakistan 149.0000000
## Patagonia 150.0000000
## Rwanda 151.0000000
## Scotland / England 152.0000000
## Sierra Leone 153.0000000
## Somalia 154.0000000
## South Africa 155.0000000
## South America 156.0000000
## Southeast Europe 157.0000000
## Southern Africa 158.0000000
## Southern Europe 159.0000000
## Sri Lanka 160.0000000
## Syria 161.0000000
## Tunisia 162.0000000
## Uganda 163.0000000
## USA 164.0000000
## Venezuela 165.0000000
## Vietnam 166.0000000
##
## Pareto chart analysis for table(guerras$Location)
## Percentage
## China 6.0240964
## Middle East 4.2168675
## Worldwide 4.2168675
## Iraq 3.0120482
## Congo 2.4096386
## Eastern Europe 2.4096386
## Europe 2.4096386
## India 2.4096386
## Mexico 2.4096386
## Western Europe 2.4096386
## Afghanistan 1.8072289
## Algeria 1.8072289
## Colombia 1.8072289
## France 1.8072289
## Greece 1.8072289
## Korea 1.8072289
## Philippines 1.8072289
## Southeast Asia 1.8072289
## Sudan 1.8072289
## Angola 1.2048193
## Central Africa 1.2048193
## Cuba 1.2048193
## England 1.2048193
## Ethiopia 1.2048193
## Eurasia 1.2048193
## Europe / Americas 1.2048193
## Nigeria 1.2048193
## Northeast India 1.2048193
## Peru 1.2048193
## Russia 1.2048193
## Southern Europe / North Africa 1.2048193
## Spain 1.2048193
## Western Europe / North Africa 1.2048193
## Yemen 1.2048193
## Americas 0.6024096
## Balkan Peninsula 0.6024096
## Bangladesh 0.6024096
## Bosnia 0.6024096
## British Isles 0.6024096
## Burundi 0.6024096
## Caucasus region 0.6024096
## China, Korea 0.6024096
## China, Vietnam 0.6024096
## Crimean Peninsula 0.6024096
## East Asia 0.6024096
## Eastern Europe / Middle East / North Africa 0.6024096
## England / Wales 0.6024096
## Europe / Middle East ("Holy Land") 0.6024096
## Finland 0.6024096
## Germany 0.6024096
## Gran Chaco 0.6024096
## Haiti 0.6024096
## Iberian Peninsula 0.6024096
## India-Bangladesh 0.6024096
## Indonesia 0.6024096
## Italy 0.6024096
## Laos 0.6024096
## Lebanon 0.6024096
## Libya 0.6024096
## Madagascar 0.6024096
## Manchuria 0.6024096
## Middle East / North Africa 0.6024096
## Middle East / North Africa / Central Asia / India 0.6024096
## Middle East / North Africa / Southern Europe 0.6024096
## Middle East/North Africa 0.6024096
## Mozambique 0.6024096
## Myanmar 0.6024096
## North Africa 0.6024096
## North America 0.6024096
## North India / Pakistan 0.6024096
## Northern China 0.6024096
## Northern Europe 0.6024096
## Pakistan 0.6024096
## Patagonia 0.6024096
## Rwanda 0.6024096
## Scotland / England 0.6024096
## Sierra Leone 0.6024096
## Somalia 0.6024096
## South Africa 0.6024096
## South America 0.6024096
## Southeast Europe 0.6024096
## Southern Africa 0.6024096
## Southern Europe 0.6024096
## Sri Lanka 0.6024096
## Syria 0.6024096
## Tunisia 0.6024096
## Uganda 0.6024096
## USA 0.6024096
## Venezuela 0.6024096
## Vietnam 0.6024096
##
## Pareto chart analysis for table(guerras$Location)
## Cum.Percent.
## China 6.0240964
## Middle East 10.2409639
## Worldwide 14.4578313
## Iraq 17.4698795
## Congo 19.8795181
## Eastern Europe 22.2891566
## Europe 24.6987952
## India 27.1084337
## Mexico 29.5180723
## Western Europe 31.9277108
## Afghanistan 33.7349398
## Algeria 35.5421687
## Colombia 37.3493976
## France 39.1566265
## Greece 40.9638554
## Korea 42.7710843
## Philippines 44.5783133
## Southeast Asia 46.3855422
## Sudan 48.1927711
## Angola 49.3975904
## Central Africa 50.6024096
## Cuba 51.8072289
## England 53.0120482
## Ethiopia 54.2168675
## Eurasia 55.4216867
## Europe / Americas 56.6265060
## Nigeria 57.8313253
## Northeast India 59.0361446
## Peru 60.2409639
## Russia 61.4457831
## Southern Europe / North Africa 62.6506024
## Spain 63.8554217
## Western Europe / North Africa 65.0602410
## Yemen 66.2650602
## Americas 66.8674699
## Balkan Peninsula 67.4698795
## Bangladesh 68.0722892
## Bosnia 68.6746988
## British Isles 69.2771084
## Burundi 69.8795181
## Caucasus region 70.4819277
## China, Korea 71.0843373
## China, Vietnam 71.6867470
## Crimean Peninsula 72.2891566
## East Asia 72.8915663
## Eastern Europe / Middle East / North Africa 73.4939759
## England / Wales 74.0963855
## Europe / Middle East ("Holy Land") 74.6987952
## Finland 75.3012048
## Germany 75.9036145
## Gran Chaco 76.5060241
## Haiti 77.1084337
## Iberian Peninsula 77.7108434
## India-Bangladesh 78.3132530
## Indonesia 78.9156627
## Italy 79.5180723
## Laos 80.1204819
## Lebanon 80.7228916
## Libya 81.3253012
## Madagascar 81.9277108
## Manchuria 82.5301205
## Middle East / North Africa 83.1325301
## Middle East / North Africa / Central Asia / India 83.7349398
## Middle East / North Africa / Southern Europe 84.3373494
## Middle East/North Africa 84.9397590
## Mozambique 85.5421687
## Myanmar 86.1445783
## North Africa 86.7469880
## North America 87.3493976
## North India / Pakistan 87.9518072
## Northern China 88.5542169
## Northern Europe 89.1566265
## Pakistan 89.7590361
## Patagonia 90.3614458
## Rwanda 90.9638554
## Scotland / England 91.5662651
## Sierra Leone 92.1686747
## Somalia 92.7710843
## South Africa 93.3734940
## South America 93.9759036
## Southeast Europe 94.5783133
## Southern Africa 95.1807229
## Southern Europe 95.7831325
## Sri Lanka 96.3855422
## Syria 96.9879518
## Tunisia 97.5903614
## Uganda 98.1927711
## USA 98.7951807
## Venezuela 99.3975904
## Vietnam 100.0000000library(DescTools)
Mode(guerras$Location)## [1] "China"dataTable=table(guerras$Location)
Herfindahl(dataTable)## [1] 0.0187255