train 0.89 #> 10 ID-RJXN-002 travail 6.18 mobylette 0.75 #> # … with 20 more rowsĪnswers # A tibble: 90 × 12 #> id_individu age sexe region id_departement nom_departement #> #> 1 ID-MROK-007 NA M 16 #> 2 ID-MROK-007 NA M 16 #> 3 ID-MROK-007 NA M 16 #> 4 ID-NYDZ-010 49 M Rhône-Alpes 07 Ardèche #> 5 ID-NYDZ-010 49 M Rhône-Alpes 07 Ardèche #> 6 ID-NYDZ-010 49 M Rhône-Alpes 07 Ardèche #> 7 ID-HXOG-015 50 M 39 Jura #> 8 ID-HXOG-015 50 M 39 Jura #> 9 ID-HXOG-015 50 M 39 Jura #> 10 ID-MZNB-024 70 F 51 Marne #> # … with 80 more rows, and 6 more variables: question_date, year, #> # type, distance_km, transport, #> # temps_trajet_en_heures ggplot ( answers ) + aes ( age, log ( distance_km ), colour = type ) + geom_point ( ) + geom_smooth ( ) + facet_wrap ( ~ type, scales = "free_y" ) #> Warning: Removed 6 rows containing non-finite values (stat_smooth). Ronal… Astro… 30 Langue… 48 Lozère #> 9 9 Miss Alond… Occup… 18 Franch… 25 Doubs Diners Clu… #> 10 10 Vernice Ondri… Clini… 19 Bourgo… 58 Nièvre #> # … with 190 more rows, and 5 more variables: name, entry_date, #> # fidelity_points, priority_encoded, priority #> #> $tickets #> # A tibble: 100 × 10 #> ref num_client year month day timestamp supported type state #> #> 1 DOSS-GFEL-011 27 Non Insta… Term… #> 2 DOSS-UWYV-09 18 Non Insta… Atte… #> 3 DOSS-DKFC-010 23 Non Insta… Term… #> 4 DOSS-SAYJ-011 7 Non Box Atte… #> 5 DOSS-GSMZ-011 24 Oui Insta… Inte… #> 6 DOSS-UIOZ-012 6 Oui Insta… Atte… #> 7 DOSS-DSMI-01 3 Non Ligne Atte… #> 8 DOSS-JOYV-02 23 Non Box Atte… #> 9 DOSS-WPSG-03 1 Non En c… #> 10 DOSS-NHFG-03 18 Non Insta… Atte… #> # … with 90 more rows, and 1 more variable: source_call ggplot ( tickets_db $ clients ) + aes ( entry_date, fidelity_points ) + geom_point ( ) + geom_smooth ( )įake_sondage_answers (n = 10, split = TRUE ) #> $individus #> # A tibble: 10 × 8 #> id_individu age sexe region id_departement nom_departement #> #> 1 ID-NYDZ-010 NA Pays de la Loire 49 Maine-et-Loire #> 2 ID-PWLB-009 71 F Basse-Normandie 14 Calvados #> 3 ID-NMQG-001 42 M Bourgogne 58 Nièvre #> 4 ID-RJXN-002 71 O Centre 41 Loir-et-Cher #> 5 ID-MROK-007 41 M Languedoc-Roussillon 48 Lozère #> 6 ID-VMKS-004 33 O Poitou-Charentes 86 Vienne #> 7 ID-XEMZ-003 81 O 77 Seine-et-Marne #> 8 ID-EUDQ-005 44 M Champagne-Ardenne 51 #> 9 ID-DCIZ-008 92 O Picardie 60 Oise #> 10 ID-KPUS-006 57 O Picardie 60 Oise #> # … with 2 more variables: question_date, year #> #> $answers #> # A tibble: 30 × 5 #> id_individu type distance_km transport temps_trajet_en_heures #> #> 1 ID-NYDZ-010 travail 12.2 voiture 0.15 #> 2 ID-NYDZ-010 commerces 9.61 bus 1.01 #> 3 ID-NYDZ-010 loisirs 549. Tickets_db $clients #> # A tibble: 200 × 14 #> num_client first last job age region id_dpt departement cb_provider #> * #> 1 1 Solomon Heaney Civil… 53 Rhône-… 73 Savoie Diners Clu… #> 2 2 Karma Willi… Scien… 81 Centre 41 Loir-et-Ch… VISA 13 di… #> 3 3 Press Kulas Anima… NA 01 Ain #> 4 4 Laken McDer… NA Centre 18 Cher #> 5 5 Sydnie Jasko… Horti… 30 Basse-… 50 #> 6 6 Clayton Runol… Commi… NA Bretag… 56 Morbihan Diners Clu… #> 7 7 Roberta Purdy… Finan… 60 69 Rhône #> 8 8 Dr. Library ( fakir ) fake_ticket_client (vol = 10 ) #> # A tibble: 10 × 25 #> ref num_client first last job age region id_dpt departement #> #> 1 DOSS-AMQN-002 79 Jovan O'Ke… Gene… 22 Langu… 30 Gard #> 2 DOSS-NCKJ-010 69 Miss Lean… Emer… 68 Île-d… 78 Yvelines #> 3 DOSS-GPBE-009 120 Odell Stok… Engi… 24 Auver… 15 Cantal #> 4 DOSS-GRLN-001 31 Loren Lars… NA Midi-… 81 Tarn #> 5 DOSS-LEPJ-004 59 Maybelle Maye… Furt… 18 Franc… 70 Haute-Saône #> 6 DOSS-DUCL-005 118 Jamarion Ober… Engi… 18 Breta… 22 Côtes-d'Ar… #> 7 DOSS-OCED-003 77 Lee Scha… Admi… NA Corse 2A Corse-du-S… #> 8 DOSS-KXSJ-007 65 Demetric Auer Cont… 21 Bourg… 71 Saône-et-L… #> 9 DOSS-UITD-006 141 Wilfrid Harv… Educ… 53 Prove… 13 Bouches-du… #> 10 DOSS-SHKL-008 182 Addyson Nien… Earl… 65 Bourg… 21 #> # … with 16 more variables: cb_provider, name, entry_date, #> # fidelity_points, priority_encoded, priority, #> # timestamp, year, month, day, supported, #> # supported_encoded, type, type_encoded, state, #> # source_call
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