1 Plots

1.1 Line Plots

1.1.1 Basic Line Plot

#bookdown::render_book("index.Rmd")

#```{r setup, include=FALSE}
#knitr::opts_chunk$set(echo = TRUE)
#library(tidyverse)
#```

#library(tidyverse)

#####################################################################################################
### Create sample dataframe and prepare for plotting                                                                     
#####################################################################################################

df <- tibble(
  date = seq(as.Date('2016-09-01'), as.Date('2021-08-31'), by = 'quarter')-1,
  gdp = 3 + round(runif(20, min=-0.10, max=0.20),2),
  pceCore = c(1.21, 1.25, 1.30, 1.40, 1.50, 1.61, 1.65, 1.75, 1.67, 1.71, 1.80, 1.90, 1.95, 2.40, 2.30, 2.15, 2.25, 2.05, 1.95, 2.10),
  pce = pceCore + round(runif(20, min=-1, max=0.5),2),
  us10y = c(1.5, 1.55, 1.57, 1.60, 1.68, 1.65, 1.69, 1.75, 1.81,1.79, 1.74, 1.71, 1.66,1.70, 1.75, 1.73, 1.69, 1.61, 1.59, 1.55),
  us2y = us10y -0.05 + round(runif(20, min=-0.075, max=0.075),2)
)

df <- pivot_longer(df, #create longer dataframe, dplyr 
                   -date,
                   names_to = "variable",
                   values_to = "values")

variables = c("pce", "pceCore")

plotData <- df %>%
  filter(variable %in% variables)

#####################################################################################################
### Plot                                                                    
#####################################################################################################
#Set color palette
color_palette <- c("blue2", "darkgreen", "darkgoldenrod1", "brown1", "azure4", 
              "darkorchid3", "coral1", "#8E9CA3", "#556670", "#000000")

plot <- ggplot(plotData, aes(x = date, y = values, group = variable, color = variable)) + 
  geom_line(size = 1)+
  geom_hline(yintercept = 2, linetype = "dashed")+
  theme_minimal() +
  scale_colour_manual(values = color_palette)+
  theme(legend.position="bottom",
        legend.title = element_blank(),
        plot.caption=element_text(hjust=0),
        plot.subtitle=element_text(face="italic"),
        plot.title=element_text(size=16,face="bold"))+
  theme(panel.grid.minor = element_line(colour = "white"))+
  labs(x="Date",y="Percent",
       title="PCE",
       subtitle="PCE and Core PCE",
       caption="Source: Random numbers")

plot

1.3 Bar Charts

Bar Chart with different colors for positive and negative numbers

#library(tidyverse)
#####################################################################################################
### Create sample dataframe                                                                       
#####################################################################################################
df <- tibble(
  timeToMaturity = c(1,2,3,4,5,7,10,20,30),
  bondName = paste("UST", timeToMaturity, sep=""),
  rate = c(1.5,1.45,1.25,1.35,1.60,1.75,1.80,2.15,2.2),
  relativeValue = round(runif(9, min=-2, max=2),2)
) 
df <- df %>%
  mutate(pos = relativeValue > 0) #Add for showing different colors for neg or pos

#####################################################################################################
### Plot                                                                    
#####################################################################################################
plot <- ggplot(df, 
              mapping = aes(x = timeToMaturity, y = relativeValue, fill = pos)) + 
  geom_col() + guides(fill = FALSE) +
  theme_minimal() +
  geom_hline(yintercept = 0, linetype = "dashed")+
  theme(legend.position="bottom",
        legend.title = element_blank(),
        plot.caption=element_text(hjust=0),
        plot.subtitle=element_text(face="italic"),
        plot.title=element_text(size=16,face="bold"))+
  labs(x="Time to Maturity",y="Basispoints",
       title="US Treasury Relative value",
       subtitle="Bonds trading cheap (green) vs expensive (red)",
       caption="Source: Random numbers")+
      scale_fill_manual(values = c("brown3", "darkgreen"), guide = FALSE)+ #Setting colors for bars
  scale_y_continuous(limits=c(-max(abs(df$relativeValue)),max(abs(df$relativeValue)))) ##Keep pos and neg y axis same length

plot