Summarizing overview information

print and summary method for "overview" class.

# S3 method for overview
summary(object, html = FALSE, ...)

Arguments

object	an object of class "overview", usually, a result of a call to overview().
html	logical. whether to send summary results to html. The default is FALSE, which prints to the R console.
...	further arguments passed to or from other methods.

Details

summary.overview() tries to be smart about formatting 14 information of overview.

See also

overview, plot.overview.

Examples

# \donttest{
ov <- overview(jobchange)
ov
#>      division               metrics   value
#> 1        size          observations   19158
#> 2        size             variables      14
#> 3        size                values  268212
#> 4        size           memory size 2318464
#> 5  duplicated duplicate observation       0
#> 6     missing  complete observation    8955
#> 7     missing   missing observation   10203
#> 8     missing     missing variables       8
#> 9     missing        missing values   20733
#> 10  data type              numerics       1
#> 11  data type              integers       1
#> 12  data type       factors/ordered      11
#> 13  data type            characters       1
#> 14  data type                others       0

summary(ov)
#> ── Data Scale ──────────────────────────────────────────────
#> • Number of observations            :     19,158
#> • Number of variables               :         14
#> • Number of values                  :    268,212
#> • Size of located memory(bytes)     :  2,318,464
#> 
#> ── Duplicated Data ─────────────────────────────────────────
#> • Number of duplicated observations :          0 (0%)
#> 
#> ── Missing Data ────────────────────────────────────────────
#> • Number of completed observations  :      8,955
#> • Number of observations with NA    :     10,203 (53.26%)
#> • Number of variables with NA       :          8
#> • Number of NA                      :     20,733
#> 
#> ── Data Type ───────────────────────────────────────────────
#> • Number of numeric variables       :          1
#> • Number of integer variables       :          1
#> • Number of factors variables       :         11
#> • Number of character variables     :          1
#> • Number of other variables         :          0
#> 
#> ── Individual variables ────────────────────────────────────
#>              Variables Data Type
#> 1          enrollee_id character
#> 2                 city    factor
#> 3       city_dev_index   numeric
#> 4               gender    factor
#> 5  relevent_experience    factor
#> 6  enrolled_university    factor
#> 7      education_level   ordered
#> 8     major_discipline    factor
#> 9           experience   ordered
#> 10        company_size   ordered
#> 11        company_type    factor
#> 12        last_new_job   ordered
#> 13      training_hours   integer
#> 14           job_chnge    factor
# }