Time series decomposition and plot

Source: R/ts_plot.R

Convert a dataframe into a time series object, decompose it into trend, seasonality/cyclicity and noise/remainder/error and plot the raw data and the decomposed components. If the time series can't be decomposed, the function will just return the line chart of the raw data.

ts_plot(data, col, frequency)

Arguments

data

dataframe: should be data.frame or tibble
col

str: the column to be analyzed
frequency

int: should choose from 1, 4, 12, 52

Value

ggplot Object

Examples

time <- c("1950 Q1", "1950 Q2", "1950 Q3", "1950 Q4",
          "1951 Q1", "1951 Q2", "1951 Q3", "1951 Q4")
earnings <- c(0.71, 0.63, 0.82, 0.91, 0.71, 0.63, 0.82, 0.91)
ts_data <- tibble::tibble(time, earnings)
ts_plot(data=ts_data, col="earnings", frequency=4)
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#>   as.zoo.data.frame zoo