Visualize a plot by attribute of `overview` class. Visualize the data type, number of observations, and number of missing values for each variable.
an object of class "overview", usually, a result of a call to overview().
character. method of order of bars(variables).
logical. Whether to apply focuses on typographic elements to ggplot2 visualization. The default is TRUE. if TRUE provides a base theme that focuses on typographic elements using hrbrthemes package.
character. The name of the base font family to use for the visualization. If not specified, the font defined in dlookr is applied. (See details)
further arguments to be passed from or to other methods.
A ggplot2 object.
The base_family is selected from "Roboto Condensed", "Liberation Sans Narrow", "NanumSquare", "Noto Sans Korean". If you want to use a different font, use it after loading the Google font with import_google_font().
# \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 Dates 0
#> 15 data type POSIXcts 0
#> 16 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 Date variables : 0
#> • Number of POSIXct variables : 0
#> • 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
plot(ov)
# sort by name of variables
plot(ov, order_type = "name")
# sort by data type of variables
plot(ov, order_type = "type")
# }