Descriptive summaries by group

Computes basic descriptive statistics (mean, median, sd) for all numeric columns in df, grouped by one or more keys.

Usage

resume_wq(df, by = c("ponto", "mes"), funs = c("mean", "median", "sd"))

Arguments

df

A data frame or tibble.

by

Character vector with grouping column names (default c("ponto","mes")). Any names not present in df are ignored.

funs

Deprecated (kept for compatibility; ignored). The function always computes mean, median and sd with na.rm = TRUE.

Value

A tibble with the grouping keys and one column per statistic/variable, named as {var}_{stat} (e.g., od_mean, od_median, od_sd).

Details

• Grouping columns not found in df are silently dropped.

• If no grouping columns remain, an error is thrown.

• Only numeric columns are summarized; if none exist, an error is thrown.

• Missing values are ignored (na.rm = TRUE).

See also

dplyr::summarise(), dplyr::across()

Examples

# \donttest{
# Using the demo dataset shipped with the package
d <- wq_demo
# Example: group by point (ponto)
s1 <- resume_wq(d, by = "ponto")
head(s1)
#> # A tibble: 4 × 34
#>   ponto       ph_mean ph_median ph_sd od_mean od_median od_sd turbidez_mean
#>   <chr>         <dbl>     <dbl> <dbl>   <dbl>     <dbl> <dbl>         <dbl>
#> 1 FBS-BRH-250    7.41      7.55 0.664    6.44      6.13 0.671          41.7
#> 2 FBS-BRH-300    7.19      7.08 1.12     6.84      6.7  0.550          47.4
#> 3 FBS-BRH-450    7.47      7.57 0.591    6.42      6.05 1.02           14.4
#> 4 FBS-BRH-950    7.09      7.18 0.271    6.91      6.1  2.19           14.5
#> # ℹ 26 more variables: turbidez_median <dbl>, turbidez_sd <dbl>,
#> #   dbo_mean <dbl>, dbo_median <dbl>, dbo_sd <dbl>, coliformes_mean <dbl>,
#> #   coliformes_median <dbl>, coliformes_sd <dbl>, p_total_mean <dbl>,
#> #   p_total_median <dbl>, p_total_sd <dbl>, nt_total_mean <dbl>,
#> #   nt_total_median <dbl>, nt_total_sd <dbl>, temperatura_mean <dbl>,
#> #   temperatura_median <dbl>, temperatura_sd <dbl>, tds_mean <dbl>,
#> #   tds_median <dbl>, tds_sd <dbl>, lat_mean <dbl>, lat_median <dbl>, …

# Example: group by point and month (if 'mes' exists in your data)
# s2 <- resume_wq(d, by = c("ponto", "mes"))
# }