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
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.- 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'`

.- percentiles
Numeric vector of percentiles to calculate. Set to

`NA`

if none required. Default`c(10,90)`

.- 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 whether to transpose rows and columns of results. 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.

A tibble data frame with the following columns:

- Year
calendar or water year selected

- Mean
annual mean of all daily flows for a given year

- Median
annual median of all daily flows for a given year

- Maximum
annual maximum of all daily flows for a given year

- Minimum
annual minimum of all daily flows for a given year

- P'n'
each annual n-th percentile selected of all daily flows

Default percentile columns:

- P10
annual 10th percentile of all daily flows for a given year

- P90
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
```