R/Tabelas.R

In maxlemes/MyPortfolio: What the Package Does (One Line, Title Case)

myCota <- readRDS("data/myCota.rds")

df1 <- xts::apply.monthly(myCota, apply, 2, xts::last)
df2 <- xts::apply.monthly(myCota, apply, 2, prod)

df1 <- df1[, c(1,7,8,10)]
df2 <- df2[, c(9,12)]
df <- merge(df1, df2)
df[1,6] <- 1.0444

df$diff <- df$varRet/df$rIBOVPerc

df <- data.table::as.data.table(df)

df$retCota <-(paste(round(100*(df$varRet-1),2), "%"))
df$retIBOV <- (paste(round(100*(df$rIBOVPerc-1),2), "%"))
df$retdiff <- (paste(round(100*(df$diff-1),2), "%"))

df1 <- df[,c(1,9,10,11)]
df1$Ano <- lubridate::year(as.Date(df1$index))
df1$Mês <- lubridate::month(as.Date(df1$index))
df1 <- df1[, c(5,6,2,3,4)]
colnames(df1) <- c("Ano", "Mês", "Cota", "IBOV", "Diferença")

dfcota <-  tidyr::spread(df1[,c(1,2,3)], "Mês", "Cota")
dfcota$Indice <- "Cota"
dfIBOV <-  tidyr::spread(df1[,c(1,2,4)], "Mês", "IBOV")
dfIBOV$Indice <- "IBOV"
dfDiff <-  tidyr::spread(df1[,c(1,2,5)], "Mês", "Diferença")
dfDiff$Indice <- "Diferença"

df <- rbind(dfcota, dfIBOV, dfDiff)
colnames(df) <- c("Ano", "Jan", "Fev", "Mar", "Abr", "Mai", "Jun", "Jul", "Ago", "Set", "Out", "Nov", "Dez", "Índice")

save(df, file = "data/TableRetMes.rda")

#------------------------------------------------

df1 <- xts::apply.yearly(myCota, apply, 2, xts::last)
df2 <- xts::apply.yearly(myCota, apply, 2, prod)

df1 <- df1[, c(1,7,8,10)]
df2 <- df2[, c(9,12)]
df <- merge(df1, df2)
df[1,6] <- 1.1604

df$diff <- df$varRet/df$rIBOVPerc
df$rend <- df$cota
df[2,8] <- exp(log(df[2,2])/2)
df[3,8] <- exp(log(df[3,2])/3)
df[4,8] <- exp(log(df[4,2])/4)


df <- data.table::as.data.table(df)

df$retCota <-(paste(round(100*(df$varRet-1),2), "%"))
df$retIBOV <- (paste(round(100*(df$rIBOVPerc-1),2), "%"))
df$retdiff <- (paste(round(100*(df$diff-1),2), "%"))
df$acumCota <- (paste(round(100*(df$cota-1),2), "%"))
df$acumIBOV <- (paste(round(100*(df$IBOV-1),2), "%"))
df$MedCota <- (paste(round(100*(df$rend-1),2), "%"))



df <- df[,c(1,10:15)]
df$Ano <- lubridate::year(as.Date(df$index))
df <- df[, c(8,2:7)]
colnames(df) <- c("Ano", "Cota", "IBOV", "Diferença", "Acum. Cota", "Acum. IBOV", "Média da Cota (a.a)")


save(df, file = "data/TableRetAnual.rda")


df <- readRDS("data/myPortfolio.rds")

df <- xts::apply.yearly(df, apply, 2, xts::last)

df <- df[,1:(ncol(df)-1)]

df <- as.data.frame(t(df))
df <- cbind(df, row.names(df))



df <- df[,c(5,2)]
colnames(df) <- c("ticker", "valor")

df <- df[df[,2] != 0,]
df <- df[order(-df$valor),]

require(highcharter)


highchart() %>%
  hc_title(text = "Portifólio Atual") %>%
  hc_add_series(df, type = "pie", hcaes(name = df$ticker, y = df$valor))%>%
  hc_tooltip(crosshairs = TRUE, borderWidth = 5, sort = TRUE, shared = TRUE, table = TRUE,
             pointFormat = paste(': <b>{point.percentage:.1f}%</b>')
  )

saveRDS(df, file = "data/myPortfolio2020.rds")

library(highcharter)

highcharter::highchart(type = "pie") %>%
  highcharter::hc_title(text = "Cota da Minha Carteira de Investimentos") %>%
  hightcharter::hchart(round(df[1,],2), "pie") %>%
  hightcharter::hc_add_theme(hc_theme_538())


df <- apply(df,1, function(X){round(X/X[ncol(df)],4)})

df <- df[1:(nrow(df)-1),]
colnames(df) <- c("2017", "2018", "2019", "2020")

df$names <- tibble::rownames_to_column(tibble::as.tibble(df))