Analyze time series data split by date within years

Analyze time series data split by date within years

Usage

anlz_splitdata(
  df,
  date_split,
  date_col = "date",
  value_col = "value",
  stats = list(avg = mean)
)

Arguments

df

data frame containing date and value columns

date_split

date to split analysis into annual periods

date_col

name of the date column

value_col

name of the value column

stats

list of functions to apply to values, default: list(avg = mean)

Value

A tibble summarizing data for annual periods "before" and "after" the split date

Examples

# Create sample data
data <- data.frame(
  date = seq.Date(as.Date("2010-01-01"), as.Date("2020-12-31"), by = "month"),
  value = rnorm(132, mean = 10, sd = 2))

# Basic analysis with default statistics
split_date <- as.Date("2015-06-15")
anlz_splitdata(data, split_date, "date", "value")
#> # A tibble: 12 × 3
#>     year period   avg
#>    <dbl> <ord>  <dbl>
#>  1  2010 before  9.39
#>  2  2011 before  9.33
#>  3  2012 before  9.73
#>  4  2013 before 10.2 
#>  5  2014 before 10.4 
#>  6  2015 before  9.99
#>  7  2016 after  10.5 
#>  8  2017 after  10.4 
#>  9  2018 after  10.8 
#> 10  2019 after   9.00
#> 11  2020 after  11.2 
#> 12  2021 after   9.90