###Installar base de datos gapminder: install.packages("gapminder")
###Cargar base de datos a nuestras sesion
library("gapminder")
gapminder->gapminder
print(gapminder)
## # A tibble: 1,704 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Afghanistan Asia 1952 28.8 8425333 779.
## 2 Afghanistan Asia 1957 30.3 9240934 821.
## 3 Afghanistan Asia 1962 32.0 10267083 853.
## 4 Afghanistan Asia 1967 34.0 11537966 836.
## 5 Afghanistan Asia 1972 36.1 13079460 740.
## 6 Afghanistan Asia 1977 38.4 14880372 786.
## 7 Afghanistan Asia 1982 39.9 12881816 978.
## 8 Afghanistan Asia 1987 40.8 13867957 852.
## 9 Afghanistan Asia 1992 41.7 16317921 649.
## 10 Afghanistan Asia 1997 41.8 22227415 635.
## # … with 1,694 more rows
##Carga dplyr
library (dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
###Primer exploracion de nuestro data frame gapminder
glimpse(gapminder)
## Rows: 1,704
## Columns: 6
## $ country <fct> "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", …
## $ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, …
## $ year <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, …
## $ lifeExp <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854, 40.8…
## $ pop <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880372, 12…
## $ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.1134, …
###Filtar datadrame segun una condicion numerica
gapminder%>%
filter(year==1952)
## # A tibble: 142 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Afghanistan Asia 1952 28.8 8425333 779.
## 2 Albania Europe 1952 55.2 1282697 1601.
## 3 Algeria Africa 1952 43.1 9279525 2449.
## 4 Angola Africa 1952 30.0 4232095 3521.
## 5 Argentina Americas 1952 62.5 17876956 5911.
## 6 Australia Oceania 1952 69.1 8691212 10040.
## 7 Austria Europe 1952 66.8 6927772 6137.
## 8 Bahrain Asia 1952 50.9 120447 9867.
## 9 Bangladesh Asia 1952 37.5 46886859 684.
## 10 Belgium Europe 1952 68 8730405 8343.
## # … with 132 more rows
###Filtar datadrame segun una condicion de tipo texto
gapminder%>%
filter(country=="El Salvador")
## # A tibble: 12 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 El Salvador Americas 1952 45.3 2042865 3048.
## 2 El Salvador Americas 1957 48.6 2355805 3422.
## 3 El Salvador Americas 1962 52.3 2747687 3777.
## 4 El Salvador Americas 1967 55.9 3232927 4359.
## 5 El Salvador Americas 1972 58.2 3790903 4520.
## 6 El Salvador Americas 1977 56.7 4282586 5139.
## 7 El Salvador Americas 1982 56.6 4474873 4098.
## 8 El Salvador Americas 1987 63.2 4842194 4140.
## 9 El Salvador Americas 1992 66.8 5274649 4444.
## 10 El Salvador Americas 1997 69.5 5783439 5155.
## 11 El Salvador Americas 2002 70.7 6353681 5352.
## 12 El Salvador Americas 2007 71.9 6939688 5728.
##reordenar datos segun una variable de menor a mayor
gapminder%>%
arrange(gdpPercap)
## # A tibble: 1,704 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Congo, Dem. Rep. Africa 2002 45.0 55379852 241.
## 2 Congo, Dem. Rep. Africa 2007 46.5 64606759 278.
## 3 Lesotho Africa 1952 42.1 748747 299.
## 4 Guinea-Bissau Africa 1952 32.5 580653 300.
## 5 Congo, Dem. Rep. Africa 1997 42.6 47798986 312.
## 6 Eritrea Africa 1952 35.9 1438760 329.
## 7 Myanmar Asia 1952 36.3 20092996 331
## 8 Lesotho Africa 1957 45.0 813338 336.
## 9 Burundi Africa 1952 39.0 2445618 339.
## 10 Eritrea Africa 1957 38.0 1542611 344.
## # … with 1,694 more rows
##reordenar datos segun una variable de mayor a menor
gapminder%>%
arrange(desc(gdpPercap))
## # A tibble: 1,704 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Kuwait Asia 1957 58.0 212846 113523.
## 2 Kuwait Asia 1972 67.7 841934 109348.
## 3 Kuwait Asia 1952 55.6 160000 108382.
## 4 Kuwait Asia 1962 60.5 358266 95458.
## 5 Kuwait Asia 1967 64.6 575003 80895.
## 6 Kuwait Asia 1977 69.3 1140357 59265.
## 7 Norway Europe 2007 80.2 4627926 49357.
## 8 Kuwait Asia 2007 77.6 2505559 47307.
## 9 Singapore Asia 2007 80.0 4553009 47143.
## 10 Norway Europe 2002 79.0 4535591 44684.
## # … with 1,694 more rows
###manipular data frame segun dos condiciones
gapminder%>%
filter(year==2007 & continent=="Americas")%>%
arrange(desc(gdpPercap))%>%
print(n=100)
## # A tibble: 25 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 United States Americas 2007 78.2 301139947 42952.
## 2 Canada Americas 2007 80.7 33390141 36319.
## 3 Puerto Rico Americas 2007 78.7 3942491 19329.
## 4 Trinidad and Tobago Americas 2007 69.8 1056608 18009.
## 5 Chile Americas 2007 78.6 16284741 13172.
## 6 Argentina Americas 2007 75.3 40301927 12779.
## 7 Mexico Americas 2007 76.2 108700891 11978.
## 8 Venezuela Americas 2007 73.7 26084662 11416.
## 9 Uruguay Americas 2007 76.4 3447496 10611.
## 10 Panama Americas 2007 75.5 3242173 9809.
## 11 Costa Rica Americas 2007 78.8 4133884 9645.
## 12 Brazil Americas 2007 72.4 190010647 9066.
## 13 Cuba Americas 2007 78.3 11416987 8948.
## 14 Peru Americas 2007 71.4 28674757 7409.
## 15 Jamaica Americas 2007 72.6 2780132 7321.
## 16 Colombia Americas 2007 72.9 44227550 7007.
## 17 Ecuador Americas 2007 75.0 13755680 6873.
## 18 Dominican Republic Americas 2007 72.2 9319622 6025.
## 19 El Salvador Americas 2007 71.9 6939688 5728.
## 20 Guatemala Americas 2007 70.3 12572928 5186.
## 21 Paraguay Americas 2007 71.8 6667147 4173.
## 22 Bolivia Americas 2007 65.6 9119152 3822.
## 23 Honduras Americas 2007 70.2 7483763 3548.
## 24 Nicaragua Americas 2007 72.9 5675356 2749.
## 25 Haiti Americas 2007 60.9 8502814 1202.
##crear una nuevo data frame
gapminder_Americas_2007<- gapminder%>%
filter(year==2007 & continent=="Americas")%>%
arrange(desc(gdpPercap))%>%
print(n=100)
## # A tibble: 25 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 United States Americas 2007 78.2 301139947 42952.
## 2 Canada Americas 2007 80.7 33390141 36319.
## 3 Puerto Rico Americas 2007 78.7 3942491 19329.
## 4 Trinidad and Tobago Americas 2007 69.8 1056608 18009.
## 5 Chile Americas 2007 78.6 16284741 13172.
## 6 Argentina Americas 2007 75.3 40301927 12779.
## 7 Mexico Americas 2007 76.2 108700891 11978.
## 8 Venezuela Americas 2007 73.7 26084662 11416.
## 9 Uruguay Americas 2007 76.4 3447496 10611.
## 10 Panama Americas 2007 75.5 3242173 9809.
## 11 Costa Rica Americas 2007 78.8 4133884 9645.
## 12 Brazil Americas 2007 72.4 190010647 9066.
## 13 Cuba Americas 2007 78.3 11416987 8948.
## 14 Peru Americas 2007 71.4 28674757 7409.
## 15 Jamaica Americas 2007 72.6 2780132 7321.
## 16 Colombia Americas 2007 72.9 44227550 7007.
## 17 Ecuador Americas 2007 75.0 13755680 6873.
## 18 Dominican Republic Americas 2007 72.2 9319622 6025.
## 19 El Salvador Americas 2007 71.9 6939688 5728.
## 20 Guatemala Americas 2007 70.3 12572928 5186.
## 21 Paraguay Americas 2007 71.8 6667147 4173.
## 22 Bolivia Americas 2007 65.6 9119152 3822.
## 23 Honduras Americas 2007 70.2 7483763 3548.
## 24 Nicaragua Americas 2007 72.9 5675356 2749.
## 25 Haiti Americas 2007 60.9 8502814 1202.