Base transport
Create fake transport sondage
Details
id_individu Unique identification of people with "ID-AAAA-1111" pattern
sexe. sex. c("F" = "Female", "M" = "Male", "O" = "Other"). Some are missing
age age. Some are missing
region. some regions have NA values that may be fill with left_join with fra_sf dataset. Some regions are more represented than others
id_departement. number identifying French department
nom_departement. Name of the department. Some departement have NA values that may be fill using id_departement.
question_date. Date/hour when questionnaire has been answered.
year. year extracted from question_date
3 types for each individuals: travail, commerces, loisirs
distance_km. Average distance (km) to target location. Distance is related to age.
transport. Mean of transport to go to target location. Depends on distance.
time_travel_hours. Average duration (hours) to target location. Depends on distance and transport.
Examples
fake_survey_people(10)
#> # A tibble: 10 × 8
#> id_individu age sexe region id_departement nom_departement
#> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 ID-NYDZ-010 NA NA Rhône-Alpes 69 Rhône
#> 2 ID-PWLB-009 71 F Franche-Comté 70 Haute-Saône
#> 3 ID-NMQG-001 42 M Rhône-Alpes 07 NA
#> 4 ID-RJXN-002 71 O Rhône-Alpes 01 Ain
#> 5 ID-MROK-007 41 M Franche-Comté 25 Doubs
#> 6 ID-VMKS-004 33 O Alsace 68 Haut-Rhin
#> 7 ID-XEMZ-003 81 O Poitou-Charentes 79 Deux-Sèvres
#> 8 ID-EUDQ-005 44 M Poitou-Charentes 16 Charente
#> 9 ID-DCIZ-008 92 O Auvergne 63 Puy-de-Dôme
#> 10 ID-KPUS-006 57 O Auvergne 43 Haute-Loire
#> # ℹ 2 more variables: question_date <dttm>, year <dbl>
answers <- fake_sondage_answers()
#> Warning: fake_survey_answers() is deprecated.
#> Use fake_survey_answers() instead.
if (FALSE){
ggplot(answers) +
aes(age, log(distance_km), colour = type) +
geom_point() +
geom_smooth() +
facet_wrap(~type, scales = "free_y")
}
