Nothing
inst/doc/cookbook.R
In ipeaplot: Add Ipea Editorial Standards to 'ggplot2' Graphics
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
eval = identical(tolower(Sys.getenv("NOT_CRAN")), "true"),
out.width = "100%"
)
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# # Leitura de bibliotecas
# library(ipeaplot)
# library(ggplot2)
# library(dplyr)
# library(data.table)
# library(abjData)
# library(geobr)
# library(reshape)
# library(knitr)
#
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# # Leitura dos dados
# ## Gráfico 1
# Ano <- factor(c(2000,2005,2010,2015,2020,2025,2030,2035,2040,2045,2050))
# Populacao <- c(6.1,6.5,6.9,7.3,7.7,8.0,8.3,8.6,8.9,9.1,9.3)
# labels <- as.character(Populacao)
# labels <- gsub("." , "," , labels, fixed=T)
# base_graf1 <- data.frame(Ano,Populacao,labels)
#
# ## Gráfico 2
# Ano <- factor(c(1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958,
# 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967,
# 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976,
# 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985,
# 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994,
# 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
# 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012,
# 2013, 2014))
# Populacao<- c( 1.850116458, 1.791417471, 1.760491225, 1.751060624,
# 1.757374206, 1.773968217, 1.795950884, 1.81926587,
# 1.840930397, 1.860403495, 1.879485845, 1.90178203,
# 1.931384556, 1.96968284 , 2.011263472, 2.052385316,
# 2.083875031, 2.098137208, 2.091095193, 2.06831928,
# 2.043373483, 2.018775478, 1.985792138, 1.944170268,
# 1.898407101, 1.850171278, 1.807798778, 1.779963926,
# 1.770930519, 1.77532254 , 1.778741317, 1.77934085,
# 1.787498884, 1.803957627, 1.823106379, 1.844715108,
# 1.856490979, 1.844087147, 1.801286156, 1.7376904,
# 1.669804195, 1.607655387, 1.548374095, 1.4949701,
# 1.447065626, 1.399607643, 1.354384982, 1.318725392,
# 1.294773864, 1.279786607, 1.268049775, 1.257045807,
# 1.248951736, 1.243210965, 1.239058923, 1.236026043,
# 1.23309632, 1.229128787, 1.223387196, 1.215887987,
# 1.207869122, 1.198749205, 1.186540058, 1.170622969,
# 1.151783904)
# labels <- as.character(Populacao)
# labels <- gsub("." , "," , labels, fixed=T)
# base_graf2<- data.frame(Ano,Populacao, labels)
#
# ## Gráfico 3
# # Valores Hipoteticos
# Pais <- factor(c("Ìndia","Japão","Alemanha","Reino Unido","França",
# "Arábia Saudita","Rússia","China","Estados Unidos"))
# Gasto <- c(40,50,50,60,70,40,90,207,640)
# base_graf3<- data.frame(Pais,Gasto)
# base_graf3$pos <- ifelse(base_graf3$Pais == 'Estados Unidos',2,1)
#
# library(dplyr)
# base_graf3 <- base_graf3 %>%
# group_by(pos) %>%
# mutate(total = sum(Gasto))
#
# ## Gráfico 4
# Ano <- seq(2009,2020,1)
# Exabytes <- c(130,360,750,1400,3100,6000,10000,14000,19000,25000,31500,40000)
#
# base_graf4 <- data.frame(Ano,Exabytes)
#
# ## Gráfico 5
#
# Ano <- seq(2004,2013,1)
# Mundo <- c(4.2,3.8,4.1,4,1.5,-2,4,2.9,2.4,2.1)
# UE <- c(2.6,2.2,3.4,3.2,0.6,-4.6,2.1,1.7,-0.4,0)
#
# base_graf5 <- data.frame(Ano,Mundo,UE)
# base_graf5<- melt(base_graf5, id=c("Ano"))
#
# ## Gráfico 6
# pais <- c("Áustria","Bélgica","Bulgária","Croácia","Chipre","República Tcheca",
# "Dinamarca","Estônia","Finlândia","França","Alemanha","Grécia",
# "Hungria","Irlanda","Itália","Letônia","Lituânia","Luxemburgo",
# "Malta","Holanda","Polônia","Portugal","România",
# "Eslováquia","Eslovênia","Espanha","Suécia","Reino Unido")
#
# petroleo <- c(90,100,97,72,104,96,-37,60,90,97,96,100,
# 81,102,89,104,90,98,98,97,96,98,52,89,107,96,95,38)
#
# base_graf6 <- data.frame(pais,petroleo)
#
# ## Gráfico 7
# pais <- c("África do Sul","Brasil","Federação Russa",
# "China","Índia","OCDE")
#
# final <- c(0.695,0.55,0.43,0.413,0.38,0.315)
#
# inicio <- c(0.67,0.61,0.4,0.33,0.32,0.297)
#
# base_graf7 <- data.frame(pais,final,inicio)
#
# ## Gráfico 8
# # link <- 'https://github.com/ipeadata-lab/ipeaplot/files'
# # base_graf8 <- data.table::fread(paste0(link,'/12239277/dados_grafico9.csv'),
# # dec = ",", encoding = 'Latin-1')
#
# base_graf8 <- data.table(pais = c("Nigéria", "Vietnã", "Índia", "Indonésia",
# "Malásia", "China", "Arábia Saudita", "África do Sul", "México",
# "Turquia", "Brasil", "Argentina", "Austrália", "Rússia", "Polônia",
# "Canadá", "USA", "Fraça", "Reino Unido", "Espanha", "Coreia do Sul",
# "Itália", "Japão", "Alemanha"),
# `crescimento medio do PIB per capita_perct` = c(2,0.5, 0.8, 0.5, 1, 0.1, 1.1, 0.4, 0.5, 0.5, 0.3, 0.5, 0.7, -0.2,
# -0.1, 0.5, 0.5, 0.3, 0.32, 0.3, 0.12, 0.1, -0.1, 0),
# `crescimento populacional medio_perct` = c(3.9,5.3, 4.6, 4.2, 3.65, 4.2, 3.1, 3.62, 3.46, 3.3, 3.4, 3.1, 2.5,
# 3.37, 3.1, 2.2, 2.2, 2.2, 2.18, 2.1, 2.28, 1.9, 2.1, 1.8),
# `crescimento do PIB (ppc)_perct` = c(5.9,5.8, 5.4, 4.7, 4.65, 4.3, 4.2, 4.02, 3.96, 3.8, 3.7, 3.6, 3.2,
# 3.17, 3, 2.7, 2.7, 2.5, 2.5, 2.4, 2.4, 2, 2, 1.8))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico1.png"))
# #{fig-align="center", width='80%'}
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# graf1 <- ggplot(data=base_graf1, aes(x=as.numeric(as.character(Ano)), y=Populacao)) +
# geom_bar(stat="identity", fill = '#015f96', width=2) +
# geom_rug(aes(x = as.numeric(as.character(Ano)) - 2.5),
# outside = TRUE, sides = "b", length = unit(2, "mm"), linewidth = 0.25) +
# coord_cartesian(expand = TRUE, clip = "off") +
# labs(fill = "",
# title="GRÁFICO 1",
# subtitle="Evolução do crescimento da população mundial 2000-2050\n(Em bilhões)",
# caption = 'Fonte: United Nations (2012a).\nTradução dos autores.') +
# theme_ipea(x_breaks = 11,include_ticks = F,
# include_x_text_title = F,include_y_text_title = F) +
# geom_text(aes(label = gsub("\\.", ",",round(Populacao,1))),
# hjust = 0.5, vjust = -0.5)
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico1.png"), width=724, height=546)
# print(graf1)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico1.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico2.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# base_graf2$Ano <- as.numeric(as.character(base_graf2$Ano))
# ref <- (subset(base_graf2,substr(Ano,4,4) %in% c('5','0')))
#
# graf2 <- ggplot(base_graf2, aes(x=Ano, y=Populacao, group = 1))+
# geom_line(color = '#015f96') +
# labs(fill = "",
# title="GRÁFICO 2",
# subtitle="Taxa de crescimento da população mundial (Em %)",
# caption = 'Elaboração dos autores.') +
# theme_ipea(x_breaks = 14, x_text_angle = 90, include_ticks = F,expand_y_limit = T,
# include_x_text_title = F,include_y_text_title = F) +
# geom_rug(data = ref, aes(x = Ano+2),inherit.aes = FALSE,
# outside = TRUE, sides = "b", length = unit(2, "mm"), linewidth = 0.25) +
# coord_cartesian(clip = "off")
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico2.png"), width=724, height=546)
# print(graf2)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico2.png"))
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico3.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# temp <- base_graf3 %>% distinct(pos, .keep_all = T)
#
#
# graf3 <- ggplot(base_graf3, aes(x= as.character(pos), y=Gasto, fill=Pais,
# label = Pais))+
# geom_bar(width = 0.5, stat = "identity", color= NA) +
# labs(y="Gastos com defesa",
# fill = "",
# title="GRÁFICO 3",
# subtitle="Gastos com defesa (Em bilhões de dólares)",
# caption = 'Fonte: Peter G. Peterson Foundation (2013).\nTradução dos autores.') +
# scale_fill_ipea() +
# geom_text( position = position_stack(vjust = 0.5), color = 'white') +
# geom_text(data = temp, aes(y = total ,label = paste0("U$ ",total)), vjust = -.5) +
# theme_ipea(legend.position="none",
# include_x_text_title = F) +
# theme(axis.ticks.x = ggplot2::element_blank(),
# axis.text.x = ggplot2::element_blank())
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico3.png"), width=724, height=546)
# print(graf3)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico3.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico4.png"))
## ----eval=FALSE, message=FALSE------------------------------------------------
# graf4 <- ggplot(base_graf4, aes(x=Ano)) +
# geom_ribbon(aes(ymin=0, ymax=Exabytes), fill = "#015f96")+
# labs(fill = "",
# title="GRÁFICO 4",
# subtitle="Evolução do volume de informação digital até 2020",
# caption = 'Fonte: IDC’s Digital Universe Study (Gantz e Reinsel, 2012).') +
# theme_ipea(legend.position="none",expand_x_limit = F,
# x_breaks = 10, y_breaks = 4,
# include_x_text_title = F,include_y_text_title = F)
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico4.png"), width=724, height=546)
# print(graf4)
# dev.off()
#
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico4.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico5.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# graf5 <- ggplot(base_graf5, aes(Ano, value, group=variable, color=variable))+
# geom_line(linewidth=1)+
# geom_point(aes(shape=variable, fill = variable),
# size=3, stroke=1.5, show.legend = F)+
# labs(color = "",
# title="GRÁFICO 5",
# subtitle="Crescimento anual do PIB da União Europeia (2004-2013) (Em %)",
# caption = 'Fonte: World Bank (2014).\nTradução dos autores.\nObs.: Os dados foram coletados no sítio do Banco Mundial.\nDisponível em: <http://goo.gl/IvtZ1a>. Acesso em: 26 set. 2014.') +
# theme_ipea(x_breaks = 10, y_breaks = 10, legend.position = 'bottom',
# expand_y_limit = T,expand_x_limit = F,
# include_x_text_title = F,include_y_text_title = F) +
# scale_color_ipea(palette_direction = -1, ) +
# scale_shape_manual(values = c(19, 21)) +
# scale_fill_manual(values = c(NA,"white"))
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico5.png"), width=724, height=546)
# print(graf5)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico5.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico6.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# base_graf6$pais<- factor(base_graf6$pais, levels=rev(sort(base_graf6$pais)))
# graf6 <- ggplot(data=base_graf6, aes(x=pais, y=petroleo)) +
# geom_bar(stat="identity", fill = '#015f96') +
# coord_flip() +
# labs(fill = "",
# title="GRÁFICO 6",
# subtitle="Importações de energia em termos do consumo total\nde energia dos países da União Europeia",
# caption = 'Fonte: Eurostat (2014).\nTradução dos autores.') +
# theme_ipea(legend.position = 'none', expand_x_limit = F,
# include_x_text_title = F,include_y_text_title = F)
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico6.png"), width=724, height=546)
# print(graf6)
# dev.off()
#
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico6.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico7.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# base_graf7<- melt(base_graf7, id=c("pais"))
#
# graf7 <- ggplot(data=base_graf7, aes(x=pais, y=value, group=variable, fill=variable)) +
# geom_bar(position='dodge',stat="identity") +
# coord_flip()+
# labs(fill = "",
# title="GRÁFICO 7",
# subtitle="Mudanças nos níveis de desigualdade do BRICS, calculadas pelo coeficiente\nGini, entre o início da década de 1990 e o final da década de 2000",
# caption = '') +
# theme_ipea(legend.position = 'bottom',
# include_x_text_title = F,include_y_text_title = F) +
# scale_fill_ipea()
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico7.png"), width=724, height=546)
# print(graf7)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico7.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico8.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# ######## GRAFICO 8
# base_graf8_aux <- base_graf8[,c(1,4)]
# base_graf8_aux$n <- 1:nrow(base_graf8_aux)
# base_graf8_new <- base_graf8[,-4]
# base_graf8_new<- melt(base_graf8_new, id=c("pais"))
#
# base_graf8_new <- base_graf8_new %>%
# group_by(variable) %>%
# mutate(n = 1:n())
#
# graf8 <-
# ggplot() +
# geom_bar(data=base_graf8_new, aes(x = reorder(pais, n), y=value,
# group=variable, fill=variable),
# stat="identity", width = 0.5) +
# labs(fill = "",
# title="GRÁFICO 8",
# subtitle="Crescimento médio real do PIB em PPC (2011-2050) (Em %)",
# caption = 'Fonte: PwC (2014).\nTradução dos autores') +
# geom_line(data=base_graf8_aux, aes(x = reorder(pais, n) ,y=`crescimento do PIB (ppc)_perct`, group = 1),
# color = 'gray') +
# scale_fill_ipea() +
# theme_ipea(legend.position = 'bottom', x_text_angle = 90) +
# coord_cartesian(clip = "off")
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico8.png"), width=724, height=546)
# print(graf8)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico8.png"))
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## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
eval = identical(tolower(Sys.getenv("NOT_CRAN")), "true"),
out.width = "100%"
)
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# # Leitura de bibliotecas
# library(ipeaplot)
# library(ggplot2)
# library(dplyr)
# library(data.table)
# library(abjData)
# library(geobr)
# library(reshape)
# library(knitr)
#
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# # Leitura dos dados
# ## Gráfico 1
# Ano <- factor(c(2000,2005,2010,2015,2020,2025,2030,2035,2040,2045,2050))
# Populacao <- c(6.1,6.5,6.9,7.3,7.7,8.0,8.3,8.6,8.9,9.1,9.3)
# labels <- as.character(Populacao)
# labels <- gsub("." , "," , labels, fixed=T)
# base_graf1 <- data.frame(Ano,Populacao,labels)
#
# ## Gráfico 2
# Ano <- factor(c(1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958,
# 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967,
# 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976,
# 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985,
# 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994,
# 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
# 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012,
# 2013, 2014))
# Populacao<- c( 1.850116458, 1.791417471, 1.760491225, 1.751060624,
# 1.757374206, 1.773968217, 1.795950884, 1.81926587,
# 1.840930397, 1.860403495, 1.879485845, 1.90178203,
# 1.931384556, 1.96968284 , 2.011263472, 2.052385316,
# 2.083875031, 2.098137208, 2.091095193, 2.06831928,
# 2.043373483, 2.018775478, 1.985792138, 1.944170268,
# 1.898407101, 1.850171278, 1.807798778, 1.779963926,
# 1.770930519, 1.77532254 , 1.778741317, 1.77934085,
# 1.787498884, 1.803957627, 1.823106379, 1.844715108,
# 1.856490979, 1.844087147, 1.801286156, 1.7376904,
# 1.669804195, 1.607655387, 1.548374095, 1.4949701,
# 1.447065626, 1.399607643, 1.354384982, 1.318725392,
# 1.294773864, 1.279786607, 1.268049775, 1.257045807,
# 1.248951736, 1.243210965, 1.239058923, 1.236026043,
# 1.23309632, 1.229128787, 1.223387196, 1.215887987,
# 1.207869122, 1.198749205, 1.186540058, 1.170622969,
# 1.151783904)
# labels <- as.character(Populacao)
# labels <- gsub("." , "," , labels, fixed=T)
# base_graf2<- data.frame(Ano,Populacao, labels)
#
# ## Gráfico 3
# # Valores Hipoteticos
# Pais <- factor(c("Ìndia","Japão","Alemanha","Reino Unido","França",
# "Arábia Saudita","Rússia","China","Estados Unidos"))
# Gasto <- c(40,50,50,60,70,40,90,207,640)
# base_graf3<- data.frame(Pais,Gasto)
# base_graf3$pos <- ifelse(base_graf3$Pais == 'Estados Unidos',2,1)
#
# library(dplyr)
# base_graf3 <- base_graf3 %>%
# group_by(pos) %>%
# mutate(total = sum(Gasto))
#
# ## Gráfico 4
# Ano <- seq(2009,2020,1)
# Exabytes <- c(130,360,750,1400,3100,6000,10000,14000,19000,25000,31500,40000)
#
# base_graf4 <- data.frame(Ano,Exabytes)
#
# ## Gráfico 5
#
# Ano <- seq(2004,2013,1)
# Mundo <- c(4.2,3.8,4.1,4,1.5,-2,4,2.9,2.4,2.1)
# UE <- c(2.6,2.2,3.4,3.2,0.6,-4.6,2.1,1.7,-0.4,0)
#
# base_graf5 <- data.frame(Ano,Mundo,UE)
# base_graf5<- melt(base_graf5, id=c("Ano"))
#
# ## Gráfico 6
# pais <- c("Áustria","Bélgica","Bulgária","Croácia","Chipre","República Tcheca",
# "Dinamarca","Estônia","Finlândia","França","Alemanha","Grécia",
# "Hungria","Irlanda","Itália","Letônia","Lituânia","Luxemburgo",
# "Malta","Holanda","Polônia","Portugal","România",
# "Eslováquia","Eslovênia","Espanha","Suécia","Reino Unido")
#
# petroleo <- c(90,100,97,72,104,96,-37,60,90,97,96,100,
# 81,102,89,104,90,98,98,97,96,98,52,89,107,96,95,38)
#
# base_graf6 <- data.frame(pais,petroleo)
#
# ## Gráfico 7
# pais <- c("África do Sul","Brasil","Federação Russa",
# "China","Índia","OCDE")
#
# final <- c(0.695,0.55,0.43,0.413,0.38,0.315)
#
# inicio <- c(0.67,0.61,0.4,0.33,0.32,0.297)
#
# base_graf7 <- data.frame(pais,final,inicio)
#
# ## Gráfico 8
# # link <- 'https://github.com/ipeadata-lab/ipeaplot/files'
# # base_graf8 <- data.table::fread(paste0(link,'/12239277/dados_grafico9.csv'),
# # dec = ",", encoding = 'Latin-1')
#
# base_graf8 <- data.table(pais = c("Nigéria", "Vietnã", "Índia", "Indonésia",
# "Malásia", "China", "Arábia Saudita", "África do Sul", "México",
# "Turquia", "Brasil", "Argentina", "Austrália", "Rússia", "Polônia",
# "Canadá", "USA", "Fraça", "Reino Unido", "Espanha", "Coreia do Sul",
# "Itália", "Japão", "Alemanha"),
# `crescimento medio do PIB per capita_perct` = c(2,0.5, 0.8, 0.5, 1, 0.1, 1.1, 0.4, 0.5, 0.5, 0.3, 0.5, 0.7, -0.2,
# -0.1, 0.5, 0.5, 0.3, 0.32, 0.3, 0.12, 0.1, -0.1, 0),
# `crescimento populacional medio_perct` = c(3.9,5.3, 4.6, 4.2, 3.65, 4.2, 3.1, 3.62, 3.46, 3.3, 3.4, 3.1, 2.5,
# 3.37, 3.1, 2.2, 2.2, 2.2, 2.18, 2.1, 2.28, 1.9, 2.1, 1.8),
# `crescimento do PIB (ppc)_perct` = c(5.9,5.8, 5.4, 4.7, 4.65, 4.3, 4.2, 4.02, 3.96, 3.8, 3.7, 3.6, 3.2,
# 3.17, 3, 2.7, 2.7, 2.5, 2.5, 2.4, 2.4, 2, 2, 1.8))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico1.png"))
# #{fig-align="center", width='80%'}
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# graf1 <- ggplot(data=base_graf1, aes(x=as.numeric(as.character(Ano)), y=Populacao)) +
# geom_bar(stat="identity", fill = '#015f96', width=2) +
# geom_rug(aes(x = as.numeric(as.character(Ano)) - 2.5),
# outside = TRUE, sides = "b", length = unit(2, "mm"), linewidth = 0.25) +
# coord_cartesian(expand = TRUE, clip = "off") +
# labs(fill = "",
# title="GRÁFICO 1",
# subtitle="Evolução do crescimento da população mundial 2000-2050\n(Em bilhões)",
# caption = 'Fonte: United Nations (2012a).\nTradução dos autores.') +
# theme_ipea(x_breaks = 11,include_ticks = F,
# include_x_text_title = F,include_y_text_title = F) +
# geom_text(aes(label = gsub("\\.", ",",round(Populacao,1))),
# hjust = 0.5, vjust = -0.5)
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico1.png"), width=724, height=546)
# print(graf1)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico1.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico2.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# base_graf2$Ano <- as.numeric(as.character(base_graf2$Ano))
# ref <- (subset(base_graf2,substr(Ano,4,4) %in% c('5','0')))
#
# graf2 <- ggplot(base_graf2, aes(x=Ano, y=Populacao, group = 1))+
# geom_line(color = '#015f96') +
# labs(fill = "",
# title="GRÁFICO 2",
# subtitle="Taxa de crescimento da população mundial (Em %)",
# caption = 'Elaboração dos autores.') +
# theme_ipea(x_breaks = 14, x_text_angle = 90, include_ticks = F,expand_y_limit = T,
# include_x_text_title = F,include_y_text_title = F) +
# geom_rug(data = ref, aes(x = Ano+2),inherit.aes = FALSE,
# outside = TRUE, sides = "b", length = unit(2, "mm"), linewidth = 0.25) +
# coord_cartesian(clip = "off")
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico2.png"), width=724, height=546)
# print(graf2)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico2.png"))
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico3.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# temp <- base_graf3 %>% distinct(pos, .keep_all = T)
#
#
# graf3 <- ggplot(base_graf3, aes(x= as.character(pos), y=Gasto, fill=Pais,
# label = Pais))+
# geom_bar(width = 0.5, stat = "identity", color= NA) +
# labs(y="Gastos com defesa",
# fill = "",
# title="GRÁFICO 3",
# subtitle="Gastos com defesa (Em bilhões de dólares)",
# caption = 'Fonte: Peter G. Peterson Foundation (2013).\nTradução dos autores.') +
# scale_fill_ipea() +
# geom_text( position = position_stack(vjust = 0.5), color = 'white') +
# geom_text(data = temp, aes(y = total ,label = paste0("U$ ",total)), vjust = -.5) +
# theme_ipea(legend.position="none",
# include_x_text_title = F) +
# theme(axis.ticks.x = ggplot2::element_blank(),
# axis.text.x = ggplot2::element_blank())
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico3.png"), width=724, height=546)
# print(graf3)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico3.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico4.png"))
## ----eval=FALSE, message=FALSE------------------------------------------------
# graf4 <- ggplot(base_graf4, aes(x=Ano)) +
# geom_ribbon(aes(ymin=0, ymax=Exabytes), fill = "#015f96")+
# labs(fill = "",
# title="GRÁFICO 4",
# subtitle="Evolução do volume de informação digital até 2020",
# caption = 'Fonte: IDC’s Digital Universe Study (Gantz e Reinsel, 2012).') +
# theme_ipea(legend.position="none",expand_x_limit = F,
# x_breaks = 10, y_breaks = 4,
# include_x_text_title = F,include_y_text_title = F)
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico4.png"), width=724, height=546)
# print(graf4)
# dev.off()
#
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico4.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico5.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# graf5 <- ggplot(base_graf5, aes(Ano, value, group=variable, color=variable))+
# geom_line(linewidth=1)+
# geom_point(aes(shape=variable, fill = variable),
# size=3, stroke=1.5, show.legend = F)+
# labs(color = "",
# title="GRÁFICO 5",
# subtitle="Crescimento anual do PIB da União Europeia (2004-2013) (Em %)",
# caption = 'Fonte: World Bank (2014).\nTradução dos autores.\nObs.: Os dados foram coletados no sítio do Banco Mundial.\nDisponível em: <http://goo.gl/IvtZ1a>. Acesso em: 26 set. 2014.') +
# theme_ipea(x_breaks = 10, y_breaks = 10, legend.position = 'bottom',
# expand_y_limit = T,expand_x_limit = F,
# include_x_text_title = F,include_y_text_title = F) +
# scale_color_ipea(palette_direction = -1, ) +
# scale_shape_manual(values = c(19, 21)) +
# scale_fill_manual(values = c(NA,"white"))
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico5.png"), width=724, height=546)
# print(graf5)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico5.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico6.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# base_graf6$pais<- factor(base_graf6$pais, levels=rev(sort(base_graf6$pais)))
# graf6 <- ggplot(data=base_graf6, aes(x=pais, y=petroleo)) +
# geom_bar(stat="identity", fill = '#015f96') +
# coord_flip() +
# labs(fill = "",
# title="GRÁFICO 6",
# subtitle="Importações de energia em termos do consumo total\nde energia dos países da União Europeia",
# caption = 'Fonte: Eurostat (2014).\nTradução dos autores.') +
# theme_ipea(legend.position = 'none', expand_x_limit = F,
# include_x_text_title = F,include_y_text_title = F)
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico6.png"), width=724, height=546)
# print(graf6)
# dev.off()
#
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico6.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico7.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# base_graf7<- melt(base_graf7, id=c("pais"))
#
# graf7 <- ggplot(data=base_graf7, aes(x=pais, y=value, group=variable, fill=variable)) +
# geom_bar(position='dodge',stat="identity") +
# coord_flip()+
# labs(fill = "",
# title="GRÁFICO 7",
# subtitle="Mudanças nos níveis de desigualdade do BRICS, calculadas pelo coeficiente\nGini, entre o início da década de 1990 e o final da década de 2000",
# caption = '') +
# theme_ipea(legend.position = 'bottom',
# include_x_text_title = F,include_y_text_title = F) +
# scale_fill_ipea()
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico7.png"), width=724, height=546)
# print(graf7)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico7.png"))
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", fig.width=6, fig.height=6----
# knitr::include_graphics(paste0(getwd(),"/prints_original/grafico8.png"))
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# ######## GRAFICO 8
# base_graf8_aux <- base_graf8[,c(1,4)]
# base_graf8_aux$n <- 1:nrow(base_graf8_aux)
# base_graf8_new <- base_graf8[,-4]
# base_graf8_new<- melt(base_graf8_new, id=c("pais"))
#
# base_graf8_new <- base_graf8_new %>%
# group_by(variable) %>%
# mutate(n = 1:n())
#
# graf8 <-
# ggplot() +
# geom_bar(data=base_graf8_new, aes(x = reorder(pais, n), y=value,
# group=variable, fill=variable),
# stat="identity", width = 0.5) +
# labs(fill = "",
# title="GRÁFICO 8",
# subtitle="Crescimento médio real do PIB em PPC (2011-2050) (Em %)",
# caption = 'Fonte: PwC (2014).\nTradução dos autores') +
# geom_line(data=base_graf8_aux, aes(x = reorder(pais, n) ,y=`crescimento do PIB (ppc)_perct`, group = 1),
# color = 'gray') +
# scale_fill_ipea() +
# theme_ipea(legend.position = 'bottom', x_text_angle = 90) +
# coord_cartesian(clip = "off")
## ----eval=FALSE, message=FALSE, warning=FALSE, results='hide'-----------------
# png(paste0(getwd(),"/prints_ipeaplot/grafico8.png"), width=724, height=546)
# print(graf8)
# dev.off()
#
## ---- echo=FALSE, message=FALSE, warning=FALSE, fig.align="center", out.width = "100%"----
# knitr::include_graphics(paste0(getwd(),"/prints_ipeaplot/grafico8.png"))
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