11.1 Overlapping

11.1.1 Goal

Plot a seasonal plot as described in Hyndman and Athanasopoulos (2014, chapter 2.4):

Figure 11.2: Seasonal Plot Overlapping per Month over 10 Years

11.1.2 Data Basis

Figure 11.3: Raw Data for Seasonal Plot Overlapping

11.1.3 Solution

Create a new script, copy/paste the following code and run it:

library(forecast)
library(dplyr)
library(plotly)
library(htmlwidgets)
library(ggthemes)
library(viridis)
library(lubridate)

# load csv file
df <- read.csv2("https://github.com/hslu-ige-laes/edar/raw/master/sampleData/flatHeatAndHotWater.csv",
                stringsAsFactors=FALSE)

# filter flat
df <- df %>% select(timestamp, Adr02_energyHeat)

colnames(df) <- c("timestamp", "meterValue")

# calculate consumption value per month
# pay attention, the value of 2010-02-01 00:00:00 represents the meter reading on february first,
# so the consumption for february first is value(march) - value(february)!
df <- df %>% dplyr::mutate(value = lead(meterValue) - meterValue)

# remove counter value column and calculate consumption per day instead of month
df <- df %>% 
  select(-meterValue) %>% 
  mutate(value = value /lubridate::days_in_month(timestamp))

# value correction (outlier because of commissioning)
df[1,2] <- 19

# create time series object for ggseanplot function
df.ts <- ts(df %>% select(value) %>% na.omit(), frequency = 12, start = min(year(df$timestamp)))

# create x/y plot
numYears = length(unique(year(df$timestamp))) # used for colours

plot <- ggseasonplot(df.ts,
                     col = viridis(numYears),
                     main = "Seasonal Plot x/y per Month over 10 years",
                     ylab = "Average Daily Energy Consumption per Month \n(kWh/day)\n"
                     )

# show static plot (uncomment it if you want a static plot)
#plot

# change theme (optional)
plot <- plot + ggthemes::theme_economist()

# make plot interactive (optional)
plotly <- plotly::ggplotly(plot)

# show plot interactive plot (optional)
plotly

# save static plot as png (optional)
ggsave("images/plotSeasonalXY.png", plot)

# save interactive plot as html (optional)
library(htmlwidgets)
htmlwidgets::saveWidget(plotly, "plotlySeasonalXY.html")

11.1.4 Discussion

A seasonal plot allows the underlying seasonal pattern to be seen more clearly, and is especially useful in identifying years in which the pattern changes.

Hints:

Double click on a specific year in the legend to display only that year
Click once to activate/deactivate an element