calc_monthly_stats {fasstr}

Calculate monthly summary statistics

Description

Calculates means, medians, maximums, minimums, and percentiles for each month of all years of flow values from a daily streamflow data set. Calculates statistics from all values, unless specified. Returns a tibble with statistics.

Usage

calc_monthly_stats(
  data,
  dates = Date,
  values = Value,
  groups = STATION_NUMBER,
  station_number,
  percentiles = c(10, 90),
  roll_days = 1,
  roll_align = "right",
  water_year_start = 1,
  start_year,
  end_year,
  exclude_years,
  months = 1:12,
  transpose = FALSE,
  spread = FALSE,
  complete_years = FALSE,
  ignore_missing = FALSE,
  allowed_missing = ifelse(ignore_missing, 100, 0)
)

Arguments

data

Data frame of daily data that contains columns of dates, flow values, and (optional) groups (e.g. station numbers). Leave blank or set to NULL if using station_number argument.

dates

Name of column in data that contains dates formatted YYYY-MM-DD. Only required if dates column name is not 'Date' (default). Leave blank or set to NULL if using station_number argument.

values

Name of column in data that contains numeric flow values, in units of cubic metres per second. Only required if values column name is not 'Value' (default). Leave blank if using station_number argument.

groups

Name of column in data that contains unique identifiers for different data sets, if applicable. Only required if groups column name is not 'STATION_NUMBER'. Function will automatically group by a column named 'STATION_NUMBER' if present. Remove the 'STATION_NUMBER' column beforehand to remove this grouping. Leave blank if using station_number argument.

station_number

Character string vector of seven digit Water Survey of Canada station numbers (e.g. "08NM116") of which to extract daily streamflow data from a HYDAT database. Requires tidyhydat package and a HYDAT database. Leave blank if using data argument.

percentiles

Numeric vector of percentiles to calculate. Set to NA if none required. Default c(10,90).

roll_days

Numeric value of the number of days to apply a rolling mean. Default 1.

roll_align

Character string identifying the direction of the rolling mean from the specified date, either by the first ('left'), last ('right'), or middle ('center') day of the rolling n-day group of observations. Default 'right'.

water_year_start

Numeric value indicating the month (1 through 12) of the start of water year for analysis. Default 1.

start_year

Numeric value of the first year to consider for analysis. Leave blank or set well before start date (i.e. 1800) to use from the first year of the source data.

end_year

Numeric value of the last year to consider for analysis. Leave blank or set well after end date (i.e. 2100) to use up to the last year of the source data.

exclude_years

Numeric vector of years to exclude from analysis. Leave blank or set to NULL to include all years.

months

Numeric vector of months to include in analysis. For example, 3 for March, 6:8 for Jun-Aug or c(10:12,1) for first four months (Oct-Jan) when water_year_start = 10 (Oct). Default summarizes all months (1:12).

transpose

Logical value indicating if each month statistic should be individual rows. Default FALSE.

spread

Logical value indicating if each month statistic should be the column name. Default FALSE.

complete_years

Logical values indicating whether to include only years with complete data in analysis. Default FALSE.

ignore_missing

Logical value indicating whether dates with missing values should be included in the calculation. If TRUE then a statistic will be calculated regardless of missing dates. If FALSE then only those statistics from time periods with no missing dates will be returned. Default FALSE.

allowed_missing

Numeric value between 0 and 100 indicating the percentage of missing dates allowed to be included to calculate a statistic (0 to 100 percent). If 'ignore_missing = FALSE' then it defaults to 0 (zero missing dates allowed), if 'ignore_missing = TRUE' then it defaults to 100 (any missing dates allowed); consistent with ignore_missing usage. Supersedes ignore_missing when used.

Value

A tibble data frame with the following columns:

Year

calendar or water year selected

Month

month of the year

Mean

mean of all daily flows for a given month and year

Median

median of all daily flows for a given month and year

Maximum

maximum of all daily flows for a given month and year

Minimum

minimum of all daily flows for a given month and year

P'n'

each n-th percentile selected for a given month and year

Default percentile columns:

P10

10th percentile of all daily flows for a given month and year

P90

90th percentile of all daily flows for a given month and year

Transposing data creates a column of 'Statistics' for each month, labeled as 'Month-Statistic' (ex "Jan-Mean"), and subsequent columns for each year selected. Spreading data creates columns of Year and subsequent columns of Month-Statistics (ex 'Jan-Mean').

Examples

# Run if HYDAT database has been downloaded (using tidyhydat::download_hydat())
if (file.exists(tidyhydat::hy_downloaded_db())) {

# Calculate statistics using a data frame and data argument with defaults
flow_data <- tidyhydat::hy_daily_flows(station_number = "08NM116")
calc_monthly_stats(data = flow_data,
                   start_year = 1980)

# Calculate statistics using station_number argument with defaults
calc_monthly_stats(station_number = "08NM116",
                   start_year = 1980)

# Calculate statistics regardless if there is missing data for a given year
calc_monthly_stats(station_number = "08NM116",
                   ignore_missing = TRUE)
                  
# Calculate statistics for water years starting in October
calc_monthly_stats(station_number = "08NM116",
                   start_year = 1980,
                   water_year_start = 10)
                  
# Calculate statistics with custom years and percentiles
calc_monthly_stats(station_number = "08NM116",
                   start_year = 1981,
                   end_year = 2010,
                   exclude_years = c(1991,1993:1995),
                   percentiles = c(25,75))
                   
}