knitr::opts_chunk$set( collapse = TRUE, comment = "#>", dev = "png", # fig.path = "figures/viz-", fig.height = 5, fig.width = 7 )
You can install the development version from GitHub with:
# install.packages("devtools") devtools::install_github("ahaeusser/tscv")
# Load relevant packages library(tscv) library(tidyverse) library(tsibble)
Sys.setlocale("LC_TIME", "C")
series_id = "bidding_zone" value_id = "value" index_id = "time" context <- list( series_id = series_id, value_id = value_id, index_id = index_id ) # Prepare data set main_frame <- elec_price %>% filter(bidding_zone %in% c("DE", "FR", "NO1", "SE1")) main_frame
# Example 1 ------------------------------------------------------------------- main_frame %>% plot_line( x = time, y = value, color = bidding_zone, facet_var = bidding_zone, title = "Day-ahead Electricity Spot Price", subtitle = "2019-01-01 to 2020-12-31", xlab = "Time", ylab = "[EUR/MWh]", caption = "Data: ENTSO-E Transparency" ) # Example 2 ------------------------------------------------------------------- main_frame %>% plot_line( x = time, y = value, color = bidding_zone, title = "Day-ahead Electricity Spot Price", subtitle = "2019-01-01 to 2020-12-31", xlab = "Time", ylab = "[EUR/MWh]", caption = "Data: ENTSO-E Transparency" )
# Estimate sample partial autocorrelation function corr_pacf <- estimate_pacf( .data = main_frame, context = context, lag_max = 30 ) corr_pacf # Visualize PACF as correlogram corr_pacf %>% plot_bar( x = lag, y = value, color = sign, facet_var = bidding_zone, position = "dodge", title = "Sample autocorrelation function", xlab = "Lag", ylab = "Correlation", caption = "Data: ENTSO-E Transparency" )
# Example 1 ------------------------------------------------------------------- main_frame %>% plot_histogram( x = value, color = bidding_zone, title = "Day-ahead Electricity Spot Price", xlab = "[EUR/MWh]", ylab = "Frequency", caption = "Data: ENTSO-E Transparency" ) # Example 2 ------------------------------------------------------------------- main_frame %>% plot_histogram( x = value, color = bidding_zone, facet_var = bidding_zone, facet_nrow = 1, title = "Day-ahead Electricity Spot Price", xlab = "[EUR/MWh]", ylab = "Frequency", caption = "Data: ENTSO-E Transparency" )
# Example 1 ------------------------------------------------------------------- main_frame %>% plot_density( x = value, color = bidding_zone, title = "Day-ahead Electricity Spot Price", xlab = "[EUR/MWh]", ylab = "Density", caption = "Data: ENTSO-E Transparency" ) # Example 2 ------------------------------------------------------------------- main_frame %>% plot_density( x = value, color = bidding_zone, facet_var = bidding_zone, facet_nrow = 1, title = "Day-ahead Electricity Spot Price", xlab = "[EUR/MWh]", ylab = "Density", caption = "Data: ENTSO-E Transparency" )
# Example 1 ------------------------------------------------------------------- main_frame %>% plot_qq( x = value, color = bidding_zone, title = "Day-ahead Electricity Spot Price", xlab = "Theoretical Quantile", ylab = "Sample Quantile", caption = "Data: ENTSO-E Transparency" ) # Example 2 ------------------------------------------------------------------- main_frame %>% plot_qq( x = value, color = bidding_zone, facet_var = bidding_zone, title = "Day-ahead Electricity Spot Price", xlab = "Theoretical Quantile", ylab = "Sample Quantile", caption = "Data: ENTSO-E Transparency" )
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