fill_missing_data {oRaklE} | R Documentation |
Replace missing values in the load data set
Description
This function substitutes missing values with the corresponding values at the same hour exactly one week prior. For example, if there is no load value available for May 12th at 20:00, the value recorded on May 7th at 20:00 will be used as a replacement.
This function is primarily designed to handle minor gaps in the dataset acquired using get_entsoE_data
. To use this function with other datasets, it is important that the input data frame adheres to the required column naming conventions.
Usage
fill_missing_data(load_data, data_directory = tempdir())
Arguments
load_data |
Data Frame with load data. Data Frame must contain the following columns:
|
data_directory |
The path to the directory where the data will be saved. The default is set to a temporary directory. |
Value
Data Frame with completed load values, date, unit, year, time resolution, ISO2C Country Code
Examples
suppressWarnings(
library(ggplot2)
)
example_demand_data_filled <- fill_missing_data(example_demand_data)
example_df <- as.data.frame(seq.POSIXt(
example_demand_data$date[841],
example_demand_data$date[870], "hour"
))
example_df$before <- NA
example_df$before[example_df[, 1] %in% example_demand_data$date] <-
example_demand_data$load[example_demand_data$date %in% example_df[, 1]]
example_df$after <- example_demand_data_filled$load[example_demand_data_filled$date
%in% example_df[, 1]]
ggplot(example_df, aes(x = example_df[, 1])) +
geom_line(aes(y = after, colour = "after data filling")) +
geom_line(aes(y = before, colour = "before data filling")) +
xlab("\nHour") +
ylab("Load [MW]\n") +
theme(legend.title = element_blank()) +
scale_x_continuous(
breaks = c(example_df[1, 1], example_df[25, 1]),
labels = c(as.Date(example_df[1, 1]), as.Date(example_df[25, 1]))
)