# Summary method for the explore function

Source: `R/explore.R`
`summary.explore.Rd`

Summary method for the explore function

    # S3 method for explore
    summary(object, dec = 3, ...)

## Arguments

object

  Return value from `explore`

dec

  Number of decimals to show

...

  further arguments passed to or from other methods

## Details

See https://radiant-rstats.github.io/docs/data/explore.html for an example in Radiant

## See also

`explore` to generate summaries

## Examples

    result <- explore(diamonds, "price:x")
    summary(result)
    #> Explore
    #> Data        : diamonds
    #> Functions   : mean, sd
    #> Top         : Function
    #>
    #>  variable      mean        sd
    #>     price 3,907.186 3,956.915
    #>     carat     0.794     0.474
    #>   clarity     0.013     0.115
    #>       cut     0.034     0.180
    #>     color     0.127     0.333
    #>     depth    61.753     1.446
    #>     table    57.465     2.241
    #>         x     5.722     1.124
    result <- explore(diamonds, "price", byvar = "cut", fun = c("n_obs", "skew"))
    summary(result)
    #> Explore
    #> Data        : diamonds
    #> Grouped by  : cut
    #> Functions   : n_obs, skew
    #> Top         : Function
    #>
    #>        cut variable n_obs  skew
    #>       Fair    price   101 1.574
    #>       Good    price   275 1.489
    #>  Very Good    price   677 1.601
    #>    Premium    price   771 1.413
    #>      Ideal    price 1,176 1.799
    explore(diamonds, "price:x", byvar = "color") %>% summary()
    #> Explore
    #> Data        : diamonds
    #> Grouped by  : color
    #> Functions   : mean, sd
    #> Top         : Function
    #>
    #>  color variable      mean        sd
    #>      D    price 3,217.003 3,278.276
    #>      D    carat     0.665     0.365
    #>      D  clarity     0.010     0.102
    #>      D      cut     0.039     0.194
    #>      D    depth    61.705     1.452
    #>      D    table    57.438     2.269
    #>      D        x     5.437     0.943
    #>      E    price 3,284.596 3,610.872
    #>      E    carat     0.679     0.391
    #>      E  clarity     0.009     0.095
    #>      E      cut     0.025     0.157
    #>      E    depth    61.768     1.391
    #>      E    table    57.548     2.262
    #>      E        x     5.455     0.999
    #>      F    price 3,654.492 3,779.511
    #>      F    carat     0.728     0.405
    #>      F  clarity     0.019     0.138
    #>      F      cut     0.030     0.171
    #>      F    depth    61.686     1.396
    #>      F    table    57.428     2.275
    #>      F        x     5.590     1.016
    #>      G    price 3,970.573 4,002.082
    #>      G    carat     0.774     0.451
    #>      G  clarity     0.008     0.091
    #>      G      cut     0.027     0.162
    #>      G    depth    61.669     1.404
    #>      G    table    57.341     2.133
    #>      G        x     5.686     1.094
    #>      H    price 4,250.302 4,063.648
    #>      H    carat     0.880     0.503
    #>      H  clarity     0.018     0.132
    #>      H      cut     0.046     0.210
    #>      H    depth    61.841     1.463
    #>      H    table    57.464     2.208
    #>      H        x     5.914     1.186
    #>      I    price 4,869.190 4,570.572
    #>      I    carat     1.001     0.573
    #>      I  clarity     0.018     0.132
    #>      I      cut     0.039     0.193
    #>      I    depth    61.938     1.620
    #>      I    table    57.446     2.160
    #>      I        x     6.163     1.251
    #>      J    price 5,642.012 4,574.576
    #>      J    carat     1.193     0.602
    #>      J  clarity     0.012     0.110
    #>      J      cut     0.043     0.203
    #>      J    depth    61.779     1.549
    #>      J    table    57.863     2.563
    #>      J        x     6.578     1.237