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.

```
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)
)
```

- 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.

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').

```
# 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))
}
#> Warning: One or more calculations included missing values and NA's were produced. Some months in some years have no data to summarize.
#> 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: 360 × 9
#> STATION_NUMBER Year Month Mean Median Maximum Minimum P25 P75
#> <chr> <dbl> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 08NM116 1981 Jan 1.99 1.93 4.11 0.850 1.39 2.34
#> 2 08NM116 1981 Feb 1.51 1.56 2.18 0.680 1.10 1.93
#> 3 08NM116 1981 Mar 1.75 1.75 2.23 1.33 1.62 1.86
#> 4 08NM116 1981 Apr 5.04 2.20 17.8 1.81 2.04 5.91
#> 5 08NM116 1981 May 28.8 22.5 60.6 12.6 16.6 38.0
#> 6 08NM116 1981 Jun 23.9 25.0 34.8 12.4 18.2 28.6
#> 7 08NM116 1981 Jul 14.2 14.6 27.3 6 9.59 17.4
#> 8 08NM116 1981 Aug 3.38 2.99 6.26 1.89 2.42 3.90
#> 9 08NM116 1981 Sep 2.76 2.75 6.19 0.398 1.58 3.53
#> 10 08NM116 1981 Oct 3.12 3 5.43 1.79 2.27 3.81
#> # … with 350 more rows
```