Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup--------------------------------------------------------------------
library(timeSeriesDataSets)
library(ggplot2)
## -----------------------------------------------------------------------------
# Install the package from CRAN
# install.packages("timeSeriesDataSets")
# Load the package
library(timeSeriesDataSets)
## ----AirPassengers------------------------------------------------------------
# Load the dataset
data("AirPassengers_ts")
# Check the class of the dataset
class(AirPassengers_ts)
# Display the first few rows of the dataset
head(AirPassengers_ts)
## ----ggplot2------------------------------------------------------------------
# Convert AirPassengers to a data frame for use with ggplot2
air_df <- data.frame(
Month = time(AirPassengers_ts),
Passengers = as.numeric(AirPassengers_ts)
)
# Time series plot
ggplot(air_df, aes(x = Month, y = Passengers)) +
geom_line(color = "blue") +
labs(title = "International Airline Passengers (1949-1960)",
x = "Date", y = "Number of Passengers") +
theme_minimal()
## ----trend_airpassengers------------------------------------------------------
# Decompose the time series
decomposed_ap <- decompose(AirPassengers_ts)
# Extract trend and seasonality
trend <- decomposed_ap$trend
seasonal <- decomposed_ap$seasonal
# Create a data frame for ggplot2
decomposed_df <- data.frame(
Month = time(AirPassengers_ts),
Passengers = as.numeric(AirPassengers_ts),
Trend = trend,
Seasonal = seasonal
)
# Plot trend and seasonality
ggplot(decomposed_df, aes(x = Month)) +
geom_line(aes(y = Passengers), color = "blue", alpha = 0.6) +
geom_line(aes(y = Trend), color = "red", linetype = "dashed") +
geom_line(aes(y = Seasonal + mean(Passengers)), color = "green", linetype = "dotted") +
labs(title = "Trend and Seasonality in AirPassengers Dataset",
x = "Date", y = "Number of Passengers") +
theme_minimal()
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