Calculates means, medians, maximums, minimums, and percentiles for each year from all years of a daily streamflow data set. Calculates statistics from all values, unless specified. Returns a tibble with statistics.
calc_annual_stats(
data,
dates = Date,
values = Value,
groups = STATION_NUMBER,
station_number,
roll_days = 1,
roll_align = "right",
percentiles = c(10, 90),
water_year_start = 1,
start_year,
end_year,
exclude_years,
months = 1:12,
transpose = FALSE,
complete_years = FALSE,
ignore_missing = FALSE,
allowed_missing = ifelse(ignore_missing, 100, 0)
)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.
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.
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.
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.
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.
Numeric value of the number of days to apply a rolling mean. Default 1.
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'.
Numeric vector of percentiles to calculate. Set to NA if none required. Default c(10,90).
Numeric value indicating the month (1 through 12) of the start of water year for
analysis. Default 1.
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.
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.
Numeric vector of years to exclude from analysis. Leave blank or set to NULL to include all years.
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).
Logical value indicating whether to transpose rows and columns of results. Default FALSE.
Logical values indicating whether to include only years with complete data in analysis. Default FALSE.
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.
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.
A tibble data frame with the following columns:
calendar or water year selected
annual mean of all daily flows for a given year
annual median of all daily flows for a given year
annual maximum of all daily flows for a given year
annual minimum of all daily flows for a given year
each annual n-th percentile selected of all daily flows
Default percentile columns:
annual 10th percentile of all daily flows for a given year
annual 90th percentile of all daily flows for a given year
Transposing data creates a column of "Statistics" and subsequent columns for each year selected.
# Run if HYDAT database has been downloaded (using tidyhydat::download_hydat())
if (file.exists(tidyhydat::hy_downloaded_db())) {
# Calculate annual statistics from a data frame using the data argument
flow_data <- tidyhydat::hy_daily_flows(station_number = "08NM116")
calc_annual_stats(data = flow_data)
# Calculate annual statistics using station_number argument
calc_annual_stats(station_number = "08NM116")
# Calculate annual statistics regardless if there
# is missing data for a given year
calc_annual_stats(station_number = "08NM116",
ignore_missing = TRUE)
# Calculate annual statistics for water years starting in October
calc_annual_stats(station_number = "08NM116",
water_year_start = 10)
# Calculate annual statistics for 7-day flows for July-September
# months only, with 25 and 75th percentiles
calc_annual_stats(station_number = "08NM116",
roll_days = 7,
months = 7:9,
percentiles = c(25,75))
}
#> Warning: One or more calculations included missing values and NA's were produced. If desired, filter data for complete years or months, or use the 'ignore_missing' or 'allowed_missing' arguments (if applicable) to ignore or allow some missing values.
#> Warning: One or more calculations included missing values and NA's were produced. If desired, filter data for complete years or months, or use the 'ignore_missing' or 'allowed_missing' arguments (if applicable) to ignore or allow some missing values.
#> Warning: One or more calculations included missing values and NA's were produced. If desired, filter data for complete years or months, or use the 'ignore_missing' or 'allowed_missing' arguments (if applicable) to ignore or allow some missing values.
#> Warning: One or more calculations included missing values and NA's were produced. If desired, filter data for complete years or months, or use the 'ignore_missing' or 'allowed_missing' arguments (if applicable) to ignore or allow some missing values.
#> # A tibble: 72 × 8
#> STATION_NUMBER Year Mean Median Maximum Minimum P25 P75
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 08NM116 1949 1.52 1.32 4.29 0.838 1.09 1.64
#> 2 08NM116 1950 2.71 1.36 16.6 0.714 0.860 2.10
#> 3 08NM116 1951 2.21 1.23 8.80 0.629 0.758 2.01
#> 4 08NM116 1952 2.85 1.93 12.9 1.11 1.32 2.56
#> 5 08NM116 1953 4.77 2.24 24.1 0.821 1.32 7.29
#> 6 08NM116 1954 7.65 4.34 30.5 1.98 3.14 8.88
#> 7 08NM116 1955 4.82 2.35 19.9 0.396 1.21 4.97
#> 8 08NM116 1956 2.25 1.29 8.21 0.784 0.998 2.33
#> 9 08NM116 1957 2.36 1.92 6.23 0.916 1.29 2.84
#> 10 08NM116 1958 1.71 1.23 5.51 0.578 0.880 2.04
#> # … with 62 more rows