Streamchart (uneven data)

Macrobond R API is available for users with Data+ and Legacy license (the latter without searching and revision history functions). Examples were tested on Macrobond version 1.27, Macrobond API for R version 1.2-8 and R 4.3.0.

See below how to construct streamchart with packages ggplot2 + ggstream. Example is presented on China's electricity generation data from China National Bureau of Statistics (NBS). Jump to the code.

Images from code for plot 1, plot 2 (proportional type) and plot 3 (ridge type).

With ggplot2 + ggstream packages

library(MacrobondAPI)
library(tidyverse)
library(ggstream)

#create list of series from Macrobond database
list_of_series<-c("cnprod0168", "cnprod0169", "cnprod0272", "cnprod0291", "cnprod0816")
#note, series in this example have uneven history 

#create empty vectors
dates<-NULL
descriptions_short<-NULL
values<-NULL

#get dates
for (i in list_of_series){
  dates<-append(dates, getDatesAtStartOfPeriod(FetchOneTimeSeries(i)))
}

#get names
#to get the neat description AND right number of descriptions for data frame you need additional steps:
#1.download series description metadata with MacrobondAPI
#2.remove unwanted string from it with str_remove
#3.download all dates from that series with MacrobondAPI and calculate length of such vector
#4.use the number in rep(x, length)
#append(reproduce(shorten_it(name), length(number of dates)))
for (i in list_of_series){
  descriptions_short<-append(descriptions_short, rep(str_remove(getMetadataValues(getMetadata(FetchOneTimeSeries(i)), "Description"), "Electricity Generation, "),length(getDatesAtStartOfPeriod(FetchOneTimeSeries(i)))))
}

#get values 
for (i in list_of_series){
  values<-append(values, getValues(FetchOneTimeSeries(i)))
}

#create data frame
data <- data.frame(year=dates, name=descriptions_short, value=values) %>%
  mutate(value=na.approx(value)) %>% #fill NA with interpolated values
  mutate(name=factor(name, levels=c("Solar Power","Wind Power", "Nuclear Power", "Hydro Power","Thermal Power"))) #for ggplot2 you need to select order of factor levels, otherwise it will be alphabetical

#colors
colors <- c("#f8d623", "#d5f0f0", "#a80092", "#43a2e2","#1c0606")

#plot 1
ggplot(data, aes(x = year, y = value, fill = name)) +
  geom_stream()+ 
  scale_fill_manual(values = colors)+ #colors
  theme_minimal()+ #theme
  guides(fill=guide_legend(title="China's Energy Mix"))+ #legend's title
  xlim(limits = as.Date(c("1990-01-01", NA))) #shorten x-axis

#plot 2
ggplot(data, aes(x = year, y = value, fill = name)) +
  geom_stream(type = "proportional")+ #type of streamchart
  scale_fill_manual(values = colors)+ #colors
  theme_minimal()+ #theme
  guides(fill=guide_legend(title="China's Energy Mix"))+ #legend's title
  xlim(limits = as.Date(c("1990-01-01", NA))) #shorten x-axis

#plot 3
ggplot(data, aes(x = year, y = value, fill = name)) +
geom_stream(type = "ridge")+ #type of streamchart
scale_fill_manual(values = colors)+ #colors
theme_minimal()+ #theme
guides(fill=guide_legend(title="China's Energy Mix"))+ #legend's title
xlim(limits = as.Date(c("1990-01-01", NA))) #shorten x-axis
Tags: streamstreamchart