Covid-19

[Fonte dos dados]:
https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_time_series 
http://www.citypopulation.de/en/china/cities/hubei/
https://www.worldometers.info/coronavirus/#countries
https://www.worldometers.info/geography/countries-of-the-world/
https://www.worldometers.info/world-population/population-by-region/

#variáveis
#Brazil_c   China_c France_c    Germany_c   Iran_c  Italy_c Korea_South_c   Spain_c Switzerland_c   United_Kingdom_c    US_c Brazil_c_1Mpop China_c_1Mpop France_c_1Mpop    Germany_c_1Mpop Iran_c_1Mpop    Italy_c_1Mpop   Korea_South_c_1Mpop Spain_c_1Mpop   Switzerland_c_1Mpop United_Kingdom_c_1Mpop  US_c_1Mpop Brazil_c_ac  China_c_ac  France_c_ac Germany_c_ac    Iran_c_ac   Italy_c_ac  Korea_South_c_ac    Spain_c_ac  Switzerland_c_ac    United_Kingdom_c_ac US_c_ac Brazil_c_d  China_c_d   France_c_d  Germany_c_d Iran_c_d    Italy_c_d   Korea_South_c_d Spain_c_d   Switzerland_c_d United_Kingdom_c_d  US_c_d Brazil_m China_m France_m    Germany_m   Iran_m  Italy_m Korea_South_m   Spain_m Switzerland_m   United_Kingdom_m    US_m Brazil_m_1Mpop China_m_1Mpop   France_m_1Mpop  Germany_m_1Mpop Iran_m_1Mpop    Italy_m_1Mpop   Korea_South_m_1Mpop Spain_m_1Mpop   Switzerland_m_1Mpop United_Kingdom_m_1Mpop  US_m_1Mpop Brazil_m_ac  China_m_ac  France_m_ac Germany_m_ac    Iran_m_ac   Italy_m_ac  Korea_South_m_ac    Spain_m_ac  Switzerland_m_ac    United_Kingdom_m_ac US_m_ac Brazil_m_d  China_m_d   France_m_d  Germany_m_d Iran_m_d    Italy_m_d   Korea_South_m_d Spain_m_d   Switzerland_m_d United_Kingdom_m_d  US_m_d
    
#Legenda: 
#    _c confirmado
#    _c_ac  confirmado acumulado
#    _m morte
#    _m_ac  morte acumulada
#    _c_d   confirmado/densidade
#    _m_d   morte/densidade
#    _c_1Mpop   confirmado acumulado por M de hab (omiti _ac para preservar o tamanho da variável)                  
#    _m_1Mpop   morte acumulada por M de hab (omiti _ac para preservar o tamanho da variável)           
#    _cd_1Mpop confirmado por dia por M de hab

#   Roteiro:
#    1) Top 10 + Brasil
#    2) Graf Novos casos por dia e Mortos por dia
#    3) Matriz
#    a) Faixa etária? (idade média)
#    b) densidade demog.
#    c) início do isolamento social
#    d) primeiro caso de corona confirmado   

library(tidyverse)
library(readr)
library(scales)
library(ggthemes)
library(reshape2)

library(readxl)
covid <- read_excel("covid19.xlsx", sheet = "r") 

#covid %>% slice(86) %>% select(contains("_ac"))

# Bases The Center for Systems Science and Engineering (CSSE) at Johns Hopkins University - Baltimore, MD

covid19_confirmed_global
covid19_deaths_global

Casos Confirmados

# Brazil_c  China_c France_c    Germany_c   Iran_c  Italy_c Korea_South_c   Spain_c Switzerland_c   United_Kingdom_c    US_c

ggplot(covid, aes(as.Date(Data))) +  
  theme(axis.text.x = element_text(angle=90))  + 
  theme_bw(base_size = 14,)+ theme(legend.position = "bottom")+ 
  ylab("covid19 - Casos Confirmados") + xlab("dia")+
  geom_point(aes(y = Brazil_c, color = "Brazil_c"), size=3)+ 
  geom_line(aes(y = China_c, color = "China_c"), size=1)+
#  geom_line(aes(y = France_c, color = "France_c"))+
#  geom_line(aes(y = Germany_c, color = "Germany_c"))+
#  geom_line(aes(y = Iran_c, color = "Iran_c"))+
  geom_line(aes(y = Italy_c, color = "Italy_c"), size=1)+
  geom_line(aes(y = Korea_South_c, color = "Korea_South_c"), size=1)+
  geom_line(aes(y = Spain_c, color = "Spain_c"), size=1)+
#  geom_line(aes(y = Switzerland_c, color = "Switzerland_c"))+
#  geom_line(aes(y = United_Kingdom_c, color = "United_Kingdom_c"))+
  geom_line(aes(y = US_c, color = "US_c"), size=1)+
  scale_x_date(date_labels = "%d-%b-%Y") 

NA
NA
NA
NA

Mortes

ggplot(covid, aes(as.Date(Data)))+ 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Mortes") + xlab("dia")+
    theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  geom_point(aes(y = Brazil_m, colour = "Brazil_m"), size=2)+
  geom_line(aes(y = China_m, colour = "China_m"), size=1)+
#  geom_line(aes(y = France_m, colour = "France_m"))+
#  geom_line(aes(y = Germany_m, colour = "Germany_m"))+
#  geom_line(aes(y = Iran_m, colour = "Iran_m"))+
  geom_line(aes(y = Italy_m, colour = "Italy_m"), size=1)+
  geom_line(aes(y = Korea_South_m, colour = "Korea_South_m"), size=1)+
  geom_line(aes(y = Spain_m, colour = "Spain_m"), size=1)+
#  geom_line(aes(y = Switzerland_m, colour = "Switzerland_m"))+
#  geom_line(aes(y = United_Kingdom_m, colour = "United_Kingdom_m"))+
  geom_line(aes(y = US_m, colour = "US_m"), size=1)+
  scale_x_date(date_labels = "%d-%b-%Y") 

Casos confirmados (acumulado) por M hab

# Brazil_c_1Mpop    China_c_1Mpop   France_c_1Mpop  Germany_c_1Mpop Iran_c_1Mpop    Italy_c_1Mpop   Korea_South_c_1Mpop Spain_c_1Mpop   Switzerland_c_1Mpop United_Kingdom_c_1Mpop  US_c_1Mpop

ggplot(covid, aes(as.Date(Data))) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Casos confirmados (acumulado) por M hab") + xlab("dia")+
    theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  geom_point(aes(y = Brazil_c_1Mpop, colour = "Brazil_c_1Mpop"), size=2)+
  geom_line(aes(y = China_c_1Mpop, colour = "China_c_1Mpop"), size=1)+
 # geom_line(aes(y = France_c_1Mpop, colour = "France_c_1Mpop"))+
#  geom_line(aes(y = Germany_c_1Mpop, colour = "Germany_c_1Mpop"))+
#  geom_line(aes(y = Iran_c_1Mpop, colour = "Iran_c_1Mpop"))+
  geom_line(aes(y = Italy_c_1Mpop, colour = "Italy_c_1Mpop"), size=1)+
  geom_line(aes(y = Korea_South_c_1Mpop, colour = "Korea_South_c_1Mpop"), size=1)+
  geom_line(aes(y = Spain_c_1Mpop, colour = "Spain_c_1Mpop"), size=1)+
#  geom_line(aes(y = Switzerland_c_1Mpop, colour = "Switzerland_c_1Mpop"))+
#  geom_line(aes(y = United_Kingdom_c_1Mpop, colour = "United_Kingdom_c_1Mpop"))+
  geom_line(aes(y = US_c_1Mpop, colour = "US_c_1Mpop"), size=1)+
  scale_x_date(date_labels = "%d-%b-%Y") 

Casos confirmados (acumulado)

# Brazil_c_ac   China_c_ac  France_c_ac Germany_c_ac    Iran_c_ac   Italy_c_ac  Korea_South_c_ac    Spain_c_ac  Switzerland_c_ac    United_Kingdom_c_ac US_c_ac


ggplot(covid, aes(as.Date(Data))) + 
  theme(axis.text.x = element_text(angle=90)) +  #scale_y_log10 () +
  ylab("covid19 - Casos confirmados (acumulado)") + xlab("dia")+ 
  theme_bw(base_size = 16)+ theme(legend.position = "bottom") + 
  geom_point(aes(y = Brazil_c_ac, colour = "Brazil_c_ac"), size=2)+
  geom_line(aes(y = China_c_ac, colour = "China_c_ac"), size=1)+
 # geom_line(aes(y = France_c_ac, colour = "France_c_ac"))+
#  geom_line(aes(y = Germany_c_ac, colour = "Germany_c_ac"))+
#  geom_line(aes(y = Iran_c_ac, colour = "Iran_c_ac"))+
  geom_line(aes(y = Italy_c_ac, colour = "Italy_c_ac"), size=1)+
  geom_line(aes(y = Korea_South_c_ac, colour = "Korea_South_c_ac"), size=1)+
  geom_line(aes(y = Spain_c_ac, colour = "Spain_c_ac"), size=1)+
#  geom_line(aes(y = Switzerland_c_ac, colour = "Switzerland_c_ac"))+
#  geom_line(aes(y = United_Kingdom_c_ac, colour = "United_Kingdom_c_ac"))+
  geom_line(aes(y = US_c_ac, colour = "US_c_ac"), size=1)+
  scale_x_date(date_labels = "%d-%b-%Y") 

Casos confirmados (acumulado) - a partir de março

# Brazil_c_ac   China_c_ac  France_c_ac Germany_c_ac    Iran_c_ac   Italy_c_ac  Korea_South_c_ac    Spain_c_ac  Switzerland_c_ac    United_Kingdom_c_ac US_c_ac
covid_s <- slice(covid, 40:1000)

ggplot(covid_s, aes(as.Date(Data))) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+# scale_y_log10 () +
  ylab("covid19 - Casos confirmados (acumulado)") + xlab("dia")+
  theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  geom_point(aes(y = Brazil_c_ac, colour = "Brazil_c_ac"), size=3)+
  geom_line(aes(y = China_c_ac, colour = "China_c_ac"), size=1)+
 # geom_line(aes(y = France_c_ac, colour = "France_c_ac"), size=1)+
#  geom_line(aes(y = Germany_c_ac, colour = "Germany_c_ac"), size=1)+
#  geom_line(aes(y = Iran_c_ac, colour = "Iran_c_ac"), size=1)+
  geom_line(aes(y = Italy_c_ac, colour = "Italy_c_ac"), size=1)+
  geom_line(aes(y = Korea_South_c_ac, colour = "Korea_South_c_ac"), size=1)+
  geom_line(aes(y = Spain_c_ac, colour = "Spain_c_ac"), size=1)+
#  geom_line(aes(y = Switzerland_c_ac, colour = "Switzerland_c_ac"), size=1)+
#  geom_line(aes(y = United_Kingdom_c_ac, colour = "United_Kingdom_c_ac"), size=1)+
  geom_line(aes(y = US_c_ac, colour = "US_c_ac"), size=1)+
  scale_x_date(date_labels = "%d-%b-%Y") 

Casos Confirmados - a partir de março

# Brazil_c  China_c France_c    Germany_c   Iran_c  Italy_c Korea_South_c   Spain_c Switzerland_c   United_Kingdom_c    US_c

ggplot(covid_s, aes(as.Date(Data))) +  
  theme(axis.text.x = element_text(angle=90)) + theme_bw() +#  scale_y_log10 () +
  theme_bw(base_size = 14,)+ theme(legend.position = "bottom")+ 
  ylab("covid19 - Casos Confirmados") + xlab("dia")+
  geom_point(aes(y = Brazil_c, color = "Brazil_c"), size=3)+ 
  geom_line(aes(y = China_c, color = "China_c"), size=1)+
 # geom_line(aes(y = France_c, color = "France_c"), size=1)+
#  geom_line(aes(y = Germany_c, color = "Germany_c"), size=1)+
#  geom_line(aes(y = Iran_c, color = "Iran_c"), size=1)+
  geom_line(aes(y = Italy_c, color = "Italy_c"), size=1)+
  geom_line(aes(y = Korea_South_c, color = "Korea_South_c"), size=1)+
  geom_line(aes(y = Spain_c, color = "Spain_c"), size=1)+
#  geom_line(aes(y = Switzerland_c, color = "Switzerland_c"), size=1)+
#  geom_line(aes(y = United_Kingdom_c, color = "United_Kingdom_c"), size=1)+
  geom_line(aes(y = US_c, color = "US_c"), size=1)+
  scale_x_date(date_labels = "%d-%b-%Y") 

  
#ggplot(covid, aes(x=Data, y=Brazil_m)) +  geom_point()+stat_smooth(method=loess) +  theme_bw() 

Casos confirmados (diário) por M hab - a partir de março

covid_d <- slice(covid, 40:1000)
ggplot(covid_d, aes(as.Date(Data))) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Casos confirmados (diário) por M Hab") + xlab("dia")+
  theme_bw(base_size = 14)+ theme(legend.position = "bottom") +
  geom_point(aes(y = Brazil_cd_1Mpop, colour = "Brazil_cd_1Mpop"), size=4, shape=1)+
  geom_line(aes(y = China_cd_1Mpop, colour = "China_cd_1Mpop"), size=1)+
#  geom_line(aes(y = France_cd_1Mpop, colour = "France_cd_1Mpop"), size=1)+
 # geom_line(aes(y = Germany_cd_1Mpop, colour = "Germany_cd_1Mpop"), size=1)+
#  geom_line(aes(y = Iran_cd_1Mpop, colour = "Iran_cd_1Mpop"), size=1)+
  geom_line(aes(y = Italy_cd_1Mpop, colour = "Italy_cd_1Mpop"), size=1)+
  geom_line(aes(y = Korea_South_cd_1Mpop, colour = "Korea_South_cd_1Mpop"), size=1)+
  geom_line(aes(y = Spain_cd_1Mpop, colour = "Spain_cd_1Mpop"), size=1)+
#  geom_line(aes(y = Switzerland_cd_1Mpop, colour = "Switzerland_cd_1Mpop"), size=1)+
#  geom_line(aes(y = United_Kingdom_cd_1Mpop, colour = "United_Kingdom_cd_1Mpop"), size=1)+
  geom_line(aes(y = US_cd_1Mpop, colour = "US_cd_1Mpop"), size=1)+
  scale_x_date(date_labels = "%d-%b-%Y") 

Casos confirmados (acumulado) a partir do 1º dia com 100 casos

# Brazil_c_ac   China_c_ac  France_c_ac Germany_c_ac    Iran_c_ac   Italy_c_ac  Korea_South_c_ac    Spain_c_ac  Switzerland_c_ac    United_Kingdom_c_ac US_c_ac


# a apartir de 100 casos 

conf <- read_excel("covid19.xlsx", sheet = "conf_100") 


ggplot(conf, aes(dias)) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Casos confirmados (acumulado)") + xlab("dia")+
  theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  geom_point(aes(y = Brazil_c, colour = "Brazil_c"), size=1, shape=10)+
  geom_line(aes(y = China_c, colour = "China_c"), size=1)+
 # geom_line(aes(y = France_c, colour = "France_c"), size=1)+
#  geom_line(aes(y = Germany_c, colour = "Germany_c"), size=1)+
#  geom_line(aes(y = Iran_c, colour = "Iran_c"), size=1)+
  geom_line(aes(y = Italy_c, colour = "Italy_c"), size=1)+
  geom_line(aes(y = Korea_South_c, colour = "Korea_South_c"), size=1)+
  geom_line(aes(y = Spain_c, colour = "Spain_c"), size=1)+
#  geom_line(aes(y = Switzerland_c, colour = "Switzerland_c"), size=1)+
#  geom_line(aes(y = United_Kingdom_c, colour = "United_Kingdom_c"), size=1)+
  geom_line(aes(y = US_c, colour = "US_c"), size=1)

Morte acumulada por M de hab

# Brazil_m_1Mpop    China_m_1Mpop   France_m_1Mpop  Germany_m_1Mpop Iran_m_1Mpop    Italy_m_1Mpop   Korea_South_m_1Mpop Spain_m_1Mpop   Switzerland_m_1Mpop United_Kingdom_m_1Mpop  US_m_1Mpop
ggplot(covid, aes(as.Date(Data))) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Morte acumulada por M de hab ") + xlab("dia")+
  geom_point(aes(y = Brazil_m_1Mpop, colour = "Brazil_m_1Mpop"), size=1)+
  geom_line(aes(y = China_m_1Mpop, colour = "China_m_1Mpop"), size=1)+
#  geom_line(aes(y = France_m_1Mpop, colour = "France_m_1Mpop"))+
#  geom_line(aes(y = Germany_m_1Mpop, colour = "Germany_m_1Mpop"))+
#  geom_line(aes(y = Iran_m_1Mpop, colour = "Iran_m_1Mpop"))+
  geom_line(aes(y = Italy_m_1Mpop, colour = "Italy_m_1Mpop"), size=1)+
  geom_line(aes(y = Korea_South_m_1Mpop, colour = "Korea_South_m_1Mpop"), size=1)+
  geom_line(aes(y = Spain_m_1Mpop, colour = "Spain_m_1Mpop"), size=1)+
#  geom_line(aes(y = Switzerland_m_1Mpop, colour = "Switzerland_m_1Mpop"))+
#  geom_line(aes(y = United_Kingdom_m_1Mpop, colour = "United_Kingdom_m_1Mpop"))+
  geom_line(aes(y = US_m_1Mpop, colour = "US_m_1Mpop"), size=1)+
    theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  scale_x_date(date_labels = "%d-%b-%Y") 

Morte acumulada

# Brazil_m_ac   China_m_ac  France_m_ac Germany_m_ac    Iran_m_ac   Italy_m_ac  Korea_South_m_ac    Spain_m_ac  Switzerland_m_ac    United_Kingdom_m_ac US_m_ac

ggplot(covid, aes(as.Date(Data))) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Morte acumulada") + xlab("dia")+
  geom_point(aes(y = Brazil_m_ac, colour = "Brazil_m_ac"), size=1)+
  geom_line(aes(y = China_m_ac, colour = "China_m_ac"), size=1)+
#  geom_line(aes(y = France_m_ac, colour = "France_m_ac"))+
#  geom_line(aes(y = Germany_m_ac, colour = "Germany_m_ac"))+
#  geom_line(aes(y = Iran_m_ac, colour = "Iran_m_ac"))+
  geom_line(aes(y = Italy_m_ac, colour = "Italy_m_ac"), size=1)+
  geom_line(aes(y = Korea_South_m_ac, colour = "Korea_South_m_ac"), size=1)+
  geom_line(aes(y = Spain_m_ac, colour = "Spain_m_ac"), size=1)+
#  geom_line(aes(y = Switzerland_m_ac, colour = "Switzerland_m_ac"))+
#  geom_line(aes(y = United_Kingdom_m_ac, colour = "United_Kingdom_m_ac"))+
  geom_line(aes(y = US_m_ac, colour = "US_m_ac"), size=1)+
    theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  scale_x_date(date_labels = "%d-%b-%Y") 

Morte por densidade demográfica

# Brazil_m_d    China_m_d   France_m_d  Germany_m_d Iran_m_d    Italy_m_d   Korea_South_m_d Spain_m_d   Switzerland_m_d United_Kingdom_m_d  US_m_d
ggplot(covid, aes(as.Date(Data))) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Morte por densidade demográfica") + xlab("dia")+
  geom_point(aes(y = Brazil_m_d, colour = "Brazil_m_d"), size=1)+
  geom_line(aes(y = China_m_d, colour = "China_m_d"), size=1)+
 # geom_line(aes(y = France_m_d, colour = "France_m_d"))+
#  geom_line(aes(y = Germany_m_d, colour = "Germany_m_d"))+
#  geom_line(aes(y = Iran_m_d, colour = "Iran_m_d"))+
  geom_line(aes(y = Italy_m_d, colour = "Italy_m_d"), size=1)+
  geom_line(aes(y = Korea_South_m_d, colour = "Korea_South_m_d"), size=1)+
  geom_line(aes(y = Spain_m_d, colour = "Spain_m_d"), size=1)+
#  geom_line(aes(y = Switzerland_m_d, colour = "Switzerland_m_d"))+
#  geom_line(aes(y = United_Kingdom_m_d, colour = "United_Kingdom_m_d"))+
  geom_line(aes(y = US_m_d, colour = "US_m_d"), size=1)+
    theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  scale_x_date(date_labels = "%d-%b-%Y") 

library(readxl)





covid3 <- read_excel("covid19.xlsx", sheet = "r2", 
    col_types = c("text", "numeric", "date", 
        "date", "numeric", "numeric", "text", 
        "numeric", "numeric", "numeric", 
        "numeric", "numeric", "numeric"))



#covid3

# Tempo de Isolamento após registro do 1º caso x mortos x densidade
#Fonte de dados: [https://www.worldometers.info/coronavirus/#countries]

#covid3 <-na.exclude(covid3)
#ggplot(covid3, aes(x=pais)) + 
#  theme(axis.text.x = element_text(angle=90)) + theme_hc()+
#  ylab("covid19 - Tempo de Isolamento após registro do 1º caso") + xlab("País")+
#  geom_point(aes(y = tempo_1_caso_isolamento, size = mortos_28_03, colour = pais))
 

#ggplot(covid3, aes(x=pais)) + 
#  theme(axis.text.x = element_text(angle=90)) + theme_hc()+
#  ylab("covid19 - Tempo de Isolamento após registro do 1º caso") + xlab("País")+ theme_calc()+
#  geom_point(aes(y = tempo_1_caso_isolamento, size = mortos_28_03, colour = densidade))

Casos confirmados (acumulado) x Tempos de Isolamento Social

#x: tempo acumulado em isolamento
#y: casos conf acumum 

# US_t  Italy_t China_t Spain_t Germany_t   France_t    United_Kingdom_t    Korea_South_t   Brazil_t

ggplot(covid, aes(x=China_t)) +  theme(axis.text.x = element_text(angle=90)) +  
#  scale_color_brewer(palette = "Accent") +
  theme_bw(base_size = 14)+ theme(legend.position = "bottom") +
  ylab("Covid19 - Casos confirmados (acumulado)") +
  ggtitle("A linha pontilhada indica quando cada país iniciou o isolamento social") +
  xlab("Tempo em isolamento da China")+
  geom_point(aes(y = Brazil_c_ac, color = "Brazil_c_ac"), shape=0, size=2) + 
  geom_point(aes(y = China_c_ac, colour = "China_c_ac"), shape=1, size=2)+ 
#  geom_point(aes(y = France_c_ac, colour = "France_c_ac"), shape=2, size=2)+
#  geom_point(aes(y = Germany_c_ac, colour = "Germany_c_ac"), shape=3, size=2)+
  geom_point(aes(y = Italy_c_ac, colour = "Italy_c_ac"), shape=4, size=2)+
  geom_point(aes(y = Korea_South_c_ac, colour = "Korea_South_c_ac"), shape=5, size=2)+
  geom_point(aes(y = Spain_c_ac, colour = "Spain_c_ac"), shape=6, size=2)+
#  geom_point(aes(y = United_Kingdom_c_ac, colour = "United_Kingdom_c_ac"), shape=7, size=2)+
  geom_point(aes(y = US_c_ac, colour = "US_c_ac"), shape=8, size=2) +  geom_text(aes(xx, yy, label=pais))+
  geom_segment(aes(x=33, y=0,yend=100000,xend =33), size=1, linetype=8)+
  geom_segment(aes(x=0, y=0 ,yend=103000,xend =0), size=1, linetype=8)+
    geom_segment(aes(x=9, y=0 ,yend=100000,xend =9), size=1, linetype=8)+ 
    geom_segment(aes(x=5, y=0 ,yend=97000 ,xend =5), size=1, linetype=8)+
    geom_segment(aes(x=1, y=0 ,yend=109000,xend =1), size=1, linetype=8)+
    geom_segment(aes(x=-2, y=0,yend=100000,xend =-2), size=1, linetype=8)+
    geom_segment(aes(x=3, y=0 ,yend=115000,xend =3), size=1, linetype=8)+
    geom_segment(aes(x=55, y=0,yend=100000,xend =55), size=1, linetype=8)+
    geom_segment(aes(x=40, y=0,yend=100000,xend =40), size=1, linetype=8)

NA
NA

Casos confirmados (acumulado) x Tempos de Isolamento Social

#x: tempo acumulado em isolamento
#y: casos conf acumum 

# US_t  Italy_t China_t Spain_t Germany_t   France_t    United_Kingdom_t    Korea_South_t   Brazil_t

# BASE DE DADOS CHAMADA isolam - COM DADOS SOMENTE DO INÍCIO DE ISOLAM DE CADA PAÍS


grafico_isolam <- read_excel("covid19.xlsx", sheet = "isolam") 

ggplot(grafico_isolam, aes(x=China_t)) +  theme(axis.text.x = element_text(angle=90)) +  
#  scale_color_brewer(palette = "Accent") +
  theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  ylab("Covid19 - Casos confirmados (acumulado)") +
  ggtitle("Tempo acumulado em isolamento social x Casos confirmados (acumulado) ") +
  xlab("Tempo acumulado em isolamento social")+
  geom_point(aes(y = Brazil_c_ac, color = "Brazil_c_ac"), size=4) + 
  geom_line(aes(y = China_c_ac, colour = "China_c_ac"), size=1)+ 
#  geom_point(aes(y = France_c_ac, colour = "France_c_ac"), shape=2, size=2)+
#  geom_point(aes(y = Germany_c_ac, colour = "Germany_c_ac"), shape=3, size=2)+
  geom_line(aes(y = Italy_c_ac, colour = "Italy_c_ac"), size=1)+
  geom_line(aes(y = Korea_South_c_ac, colour = "Korea_South_c_ac"), size=1)+
  geom_line(aes(y = Spain_c_ac, colour = "Spain_c_ac"), size=1)+
#  geom_point(aes(y = United_Kingdom_c_ac, colour = "United_Kingdom_c_ac"), shape=7, size=2)+
  geom_line(aes(y = US_c_ac, colour = "US_c_ac"), size=1)

Mortes - Box-plot

library(stringr)
covid2 <-covid[,c(1:109)]
covid2 <- stack(covid2)
covid2 <-filter(covid2,str_detect(ind, "_m"))
covid2 <-filter(covid2,str_detect(ind,"_m(?!_ac)"))
covid2 <-filter(covid2,str_detect(ind,"_m(?!_1Mpop)"))
covid2 <-filter(covid2,str_detect(ind,"_m(?!_d)"))

covid2 <- arrange(covid2,values)

ggplot(covid2, aes(x = ind, y = values )) + geom_boxplot(aes(fill = ind))+ theme_bw()+
  ylab("covid19 - Mortes") + xlab("País") + theme(axis.text.x = element_text(angle=90)) +
 theme(legend.position = "bottom") 

ggplot(covid2, aes(x = ind, y = values )) + 
  geom_dotplot(aes(color = ind), binaxis="y", stackdir='centerwhole', fill = "white",dotsize=0.5) + theme_bw()+
  ylab("covid19 - Mortes") + xlab("País") + theme(axis.text.x = element_text(angle=90)) +
 theme(legend.position = "bottom") 

Casos Confirmados - Box-plot

library(stringr)
covid2 <-covid[,c(1:109)]
covid2 <- stack(covid2)
covid2 <-filter(covid2,str_detect(ind, "_c"))
covid2 <-filter(covid2,str_detect(ind,"_c(?!_ac)"))
covid2 <-filter(covid2,str_detect(ind,"_c(?!_1Mpop)"))
covid2 <-filter(covid2,str_detect(ind,"_c(?!_d)"))
covid2 <- arrange(covid2,values)

ggplot(covid2, aes(x = ind, y = values )) + geom_boxplot(aes(fill = ind))+ theme_bw()+
  ylab("covid19 - Casos Confirmados") + xlab("País") + theme(axis.text.x = element_text(angle=90)) +
 theme(legend.position = "bottom") 

ggplot(covid2, aes(x = ind, y = values )) + 
  geom_dotplot(aes(color = ind), binaxis="y", stackdir='centerwhole', fill = "white",dotsize=0.5) + theme_bw()+
  ylab("covid19 - Casos Confirmados") + xlab("País") + theme(axis.text.x = element_text(angle=90)) +
  theme(legend.position = "bottom") 

Mortes (acumuladas) desde a 1º morte em cada país

#Italy_m_ac Spain_m_ac  China_m_ac  US_m_ac Korea_South_m_ac    Brazil_m_ac dia

desconto=3000
x=65

covid_1dia <- read_excel("covid19.xlsx", sheet = "1morte") 

ggplot(covid_1dia, aes(Dia)) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Mortes (acumulada)") + xlab("dia")+
  theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  geom_point(aes(y = Brazil_m_ac, colour = "Brazil_m_ac"), size=2, shape=10)+
  geom_line(aes(y = China_m_ac, colour = "China_m_ac"), size=1)+
 # geom_line(aes(y = France_m_ac, colour = "France_m_ac"), size=1)+
#  geom_line(aes(y = Germany_m_ac, colour = "Germany_m_ac"), size=1)+
#  geom_line(aes(y = Iran_m_ac, colour = "Iran_m_ac"), size=1)+
  geom_line(aes(y = Italy_m_ac, colour = "Italy_m_ac"), size=1)+
  geom_line(aes(y = Korea_South_m_ac, colour = "Korea_South_m_ac"), size=1)+
  geom_line(aes(y = Spain_m_ac, colour = "Spain_m_ac"), size=1)+
#  geom_line(aes(y = Switzerland_m_ac, colour = "Switzerland_m_ac"), size=1)+
#  geom_line(aes(y = United_Kingdom_m_ac, colour = "United_Kingdom_m_ac"), size=1)+
  geom_line(aes(y = US_m_ac, colour = "US_m_ac"), size=1)+
  geom_vline(aes(xintercept=30),size=1,linetype="dashed", color="blue" )#+

#    geom_text(aes(label = covid_1dia$Brazil_m_ac[30],     x=x+20, y=10000+desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$China_m_ac[30],      x=x+20, y=10000+2*desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$Italy_m_ac[30],      x=x+20, y=10000+3*desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$Korea_South_m_ac[30],x=x+20, y=10000+4*desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$Spain_m_ac[30],      x=x+20, y=10000+5*desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$US_m_ac[30],         x=x+20, y=10000+6*desconto), color="black", size=7)+
  #geom_text(aes(label = "Mortes no 30º Dia",     x=15, y=10000+6*desconto), color="blue", size=7)+
  #geom_text(aes(label = "desde a 1º morte",     x=15, y=10000+6*desconto-2500), color="blue", size=7)+
  #geom_text(aes(label = "em cada país",     x=15, y=10000+6*desconto-5000), color="blue", size=7)+
 #   geom_text(aes(label = "Brazil",     x=x, y=10000+desconto), color="black", size=7,nudge_x=0)+
#    geom_text(aes(label = "China",      x=x, y=10000+2*desconto), color="black", size=7,nudge_x=0)+
 #   geom_text(aes(label = "Italy",      x=x, y=10000+3*desconto), color="black", size=7,nudge_x=-1)+
#    geom_text(aes(label = "Korea_South", x=x, y=10000+4*desconto), color="black", size=7,nudge_x=5)+
 #   geom_text(aes(label = "Spain",      x=x, y=10000+5*desconto), color="black", size=7,nudge_x=0)+
#    geom_text(aes(label = "US",         x=x, y=10000+6*desconto), color="black", size=7,nudge_x=-1)

Mortes (acumuladas) desde o 1º caso confirmado em cada país

#Italy_m_ac Spain_m_ac  China_m_ac  US_m_ac Korea_South_m_ac    Brazil_m_ac dia

covid_1dia <- read_excel("covid19.xlsx", sheet = "1caso") 

ggplot(covid_1dia, aes(Dia)) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Mortes (acumulada)") + xlab("dia")+
  theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  geom_point(aes(y = Brazil_m_ac, colour = "Brazil_m_ac"), size=2, shape=10)+
  geom_line(aes(y = China_m_ac, colour = "China_m_ac"), size=1)+
 # geom_line(aes(y = France_m_ac, colour = "France_m_ac"), size=1)+
#  geom_line(aes(y = Germany_m_ac, colour = "Germany_m_ac"), size=1)+
#  geom_line(aes(y = Iran_m_ac, colour = "Iran_m_ac"), size=1)+
  geom_line(aes(y = Italy_m_ac, colour = "Italy_m_ac"), size=1)+
  geom_line(aes(y = Korea_South_m_ac, colour = "Korea_South_m_ac"), size=1)+
  geom_line(aes(y = Spain_m_ac, colour = "Spain_m_ac"), size=1)+
#  geom_line(aes(y = Switzerland_m_ac, colour = "Switzerland_m_ac"), size=1)+
#  geom_line(aes(y = United_Kingdom_m_ac, colour = "United_Kingdom_m_ac"), size=1)+
  geom_line(aes(y = US_m_ac, colour = "US_m_ac"), size=1)+
 geom_vline(aes(xintercept=50),size=1,linetype="dashed", color="blue" )#+

#    geom_text(aes(label = covid_1dia$Brazil_m_ac[50],     x=x+20, y=10000+desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$China_m_ac[50],      x=x+20, y=10000+2*desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$Italy_m_ac[50],      x=x+20, y=10000+3*desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$Korea_South_m_ac[50],x=x+20, y=10000+4*desconto), color="black", size=7)+
#    geom_text(aes(label = covid_1dia$Spain_m_ac[50],      x=x+20, y=10000+5*desconto), color="black", size=7)+
##    geom_text(aes(label = covid_1dia$US_m_ac[50],         x=x+20, y=10000+6*desconto), color="black", size=7)+
#  geom_text(aes(label = "Mortes no 50º Dia",     x=15, y=10000+6*desconto), color="blue", size=7)+
#  geom_text(aes(label = "desde o 1º caso",     x=15, y=10000+6*desconto-2500), color="blue", size=7)+
#  geom_text(aes(label = "em cada país",     x=15, y=10000+6*desconto-5000), color="blue", size=7)+
#    geom_text(aes(label = "Brazil",     x=x, y=10000+desconto), color="black", size=7,nudge_x=0)+
##    geom_text(aes(label = "China",      x=x, y=10000+2*desconto), color="black", size=7,nudge_x=0)+
#    geom_text(aes(label = "Italy",      x=x, y=10000+3*desconto), color="black", size=7,nudge_x=-1)+
#    geom_text(aes(label = "Korea_South", x=x, y=10000+4*desconto), color="black", size=7,nudge_x=3)+
#    geom_text(aes(label = "Spain",      x=x, y=10000+5*desconto), color="black", size=7,nudge_x=0)+
#    geom_text(aes(label = "US",         x=x, y=10000+6*desconto), color="black", size=7,nudge_x=-1)

Mortes (acumuladas) por M hab desde o 1º caso confirmado em cada país

#   Italy_m_ac_1Mpop    Spain_m_ac_1Mpop    China_m_ac_1Mpop    US_m_ac_1Mpop   Korea_South_m_ac_1Mpop  Brazil_m_ac_1Mpop

desconto=50
x=75
covid_1dia <- read_excel("covid19.xlsx", sheet = "1caso") 

ggplot(covid_1dia, aes(Dia)) + 
  theme(axis.text.x = element_text(angle=90)) + theme_bw()+
  ylab("covid19 - Mortes (acumulada) por M hab") + xlab("dia")+
  theme_bw(base_size = 16)+ theme(legend.position = "bottom") +
  geom_point(aes(y = Brazil_m_ac_1Mpop, colour = "Brazil_m_ac_1Mpop"), size=2, shape=10)+
  geom_line(aes(y = China_m_ac_1Mpop, colour = "China_m_ac_1Mpop"), size=1)+
 # geom_line(aes(y = France_m_ac_1Mpop, colour = "France_m_ac_1Mpop"), size=1)+
#  geom_line(aes(y = Germany_m_ac_1Mpop, colour = "Germany_m_ac_1Mpop"), size=1)+
#  geom_line(aes(y = Iran_m_ac_1Mpop, colour = "Iran_m_ac_1Mpop"), size=1)+
  geom_line(aes(y = Italy_m_ac_1Mpop, colour = "Italy_m_ac_1Mpop"), size=1)+
  geom_line(aes(y = Korea_South_m_ac_1Mpop, colour = "Korea_South_m_ac_1Mpop"), size=1)+
  geom_line(aes(y = Spain_m_ac_1Mpop, colour = "Spain_m_ac_1Mpop"), size=1)+
#  geom_line(aes(y = Switzerland_m_ac_1Mpop, colour = "Switzerland_m_ac_1Mpop"), size=1)+
#  geom_line(aes(y = United_Kingdom_m_ac_1Mpop, colour = "United_Kingdom_m_ac_1Mpop"), size=1)+
  geom_line(aes(y = US_m_ac_1Mpop, colour = "US_m_ac_1Mpop"), size=1)+
 geom_vline(aes(xintercept=50),size=1,linetype="dashed", color="blue" )#+

#    geom_text(aes(label = round(covid_1dia$Brazil_m_ac_1Mpop[50],2),     x=x+25, y=1+desconto), color="black", size=7)+
#    geom_text(aes(label = round(covid_1dia$China_m_ac_1Mpop[50],2),      x=x+25, y=1+1.5*desconto), color="black", size=7)+
#    geom_text(aes(label = round(covid_1dia$Italy_m_ac_1Mpop[50],2),      x=x+25, y=1+2*desconto), color="black", size=7)+
#    geom_text(aes(label = round(covid_1dia$Korea_South_m_ac_1Mpop[50],2),x=x+25, y=1+2.5*desconto), color="black", size=7)+
#    geom_text(aes(label = round(covid_1dia$Spain_m_ac_1Mpop[50],2),      x=x+25, y=1+3*desconto), color="black", size=7)+
#    geom_text(aes(label = round(covid_1dia$US_m_ac_1Mpop[50],2),         x=x+25, y=1+3.5*desconto), color="black", size=7)+
#  geom_text(aes(label = "Mortes no 50º Dia",     x=15, y=1+6*desconto), color="blue", size=7)+
#  geom_text(aes(label = "desde o 1º caso",     x=15, y=1+5*desconto), color="blue", size=7)+
#  geom_text(aes(label = "por M Hab em cada país",     x=15, y=1+4*desconto), color="blue", size=7)+
#    geom_text(aes(label = "Brazil",     x=x, y=1+desconto), color="black", size=7,nudge_x=0)+
#    geom_text(aes(label = "China",      x=x, y=1+1.5*desconto), color="black", size=7,nudge_x=0)+
#    geom_text(aes(label = "Italy",      x=x, y=1+2*desconto), color="black", size=7,nudge_x=-1)+
#    geom_text(aes(label = "Korea_South", x=x, y=1+2.5*desconto), color="black", size=7,nudge_x=3)+
#    geom_text(aes(label = "Spain",      x=x, y=1+3*desconto), color="black", size=7,nudge_x=0)+
#    geom_text(aes(label = "US",         x=x, y=1+3.5*desconto), color="black", size=7,nudge_x=-1)