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Daily frequency table

daily_frequency_table.Rd

Calculates the historical max, mean, minimum, and number of available points for each day of the year

Usage

daily_frequency_table(
  gw_level_dv,
  gwl_data,
  parameter_cd = NA,
  date_col = NA,
  value_col = NA,
  approved_col = NA,
  stat_cd = NA
)

Arguments

gw_level_dv

data frame, daily groundwater level data from readNWISdv

gwl_data

data frame returned from dataRetrieval::readNWISgwl, or data frame with mandatory columns lev_dt (representing date), lev_age_cd (representing approval code), and a column representing the measured value (either lev_va, sl_lev_va, or value).

parameter_cd

If data in gw_level_dv comes from NWIS, the parameter_cd can be used to define the value_col. If the data doesn't come directly from NWIS services, this can be set to NA,and this argument will be ignored.

date_col

the heading of the date column. The default is NA, which the code will try to get the column name automatically.

value_col

name of value column. The default is NA, which the code will try to get the column name automatically.

approved_col

name of column to get provisional/approved status.

stat_cd

If data in gw_level_dv comes from NWIS, the stat_cd can be used to help define the value_col.

Value

a data frame giving the max, mean, min, and number of available days of data for each day of the year.

Examples


# site <- "263819081585801"
p_code_dv <- "62610"
statCd <- "00001"
# gw_level_dv <- dataRetrieval::readNWISdv(site, p_code_dv, statCd = statCd)
gw_level_dv <- L2701_example_data$Daily
daily_frequency_table(gw_level_dv,
                      NULL,
                      parameter_cd = "62610")
#> # A tibble: 366 × 5
#>      DOY   max  mean   min points
#>    <dbl> <dbl> <dbl> <dbl>  <int>
#>  1     1 -5.29 -22.5 -41.4     41
#>  2     2 -5.24 -22.5 -40.1     41
#>  3     3 -5.3  -22.6 -40.2     41
#>  4     4 -5.55 -22.6 -41.6     41
#>  5     5 -5.48 -22.7 -40.5     41
#>  6     6 -5.71 -22.7 -40.6     41
#>  7     7 -5.64 -22.8 -42.2     41
#>  8     8 -5.75 -22.7 -41.4     41
#>  9     9 -5.52 -22.5 -40.5     42
#> 10    10 -5.3  -22.6 -40.6     42
#> # ℹ 356 more rows

gwl_data <- L2701_example_data$Discrete
daily_frequency_table(gw_level_dv,
                      gwl_data,
                      parameter_cd = "62610")
#> # A tibble: 366 × 5
#>      DOY   max  mean   min points
#>    <dbl> <dbl> <dbl> <dbl>  <int>
#>  1     1 -5.29 -22.5 -41.4     41
#>  2     2 -5.24 -22.5 -40.1     41
#>  3     3 -5.3  -22.6 -40.2     41
#>  4     4 -5.55 -22.6 -41.6     41
#>  5     5 -5.48 -23.0 -40.5     43
#>  6     6 -5.71 -22.7 -40.6     41
#>  7     7 -5.64 -22.8 -42.2     41
#>  8     8 -5.75 -22.6 -41.4     42
#>  9     9 -5.52 -22.5 -40.5     43
#> 10    10 -5.3  -22.6 -40.6     42
#> # ℹ 356 more rows