Valeurs Foncières 2019 - dvf_2019

Data

~/data/

• Demande de Valeur Foncière. html

nature_mutation

dvf_2019 %>%
  group_by(nature_mutation) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) print_table(.) else .}

nature_mutation	Nobs
Adjudication	4819
Echange	27127
Expropriation	2059
Vente	2308539
Vente en l’état futur d’achèvement	185441
Vente terrain à bâtir	7806

code_departement

dvf_2019 %>%
  group_by(code_departement) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Code postal, Commune, Code departement, Code commune

dvf_2019 %>%
  group_by(code_postal, nom_commune, code_departement, code_commune) %>%
  summarise(Nobs = n()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Prix/m2 par code postal

dvf_2019 %>%
  select(6, 8, 5, 10, 12, lot1_surface_carrez, lot2_surface_carrez) %>%
  filter(lot1_surface_carrez != 0) %>%
  mutate(metre_carre = round(valeur_fonciere / lot1_surface_carrez)) %>%
  filter(!is.na(metre_carre),
         # Valeurs mètre carré absurde
         metre_carre < 50000,
         metre_carre > 1000) %>%
  group_by(code_postal, nom_commune) %>%
  summarise(Nobs = n(),
            metre_carre_mean = metre_carre %>% mean %>% round,
            metre_carre_sd = metre_carre %>% sd %>% round,
            metre_carre_max = metre_carre %>% max %>% round,
            metre_carre_min = metre_carre %>% min %>% round) %>%
  filter(Nobs > 100) %>%
  arrange(-metre_carre_mean) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Paris 5

dvf_2019 %>%
  filter(code_postal == 75005) %>%
  select(6, 8, 5, lot1_surface_carrez, lot2_surface_carrez) %>%
  filter(lot1_surface_carrez != 0) %>%
  mutate(metre_carre = round(valeur_fonciere / lot1_surface_carrez)) %>%
  filter(!is.na(metre_carre),
         # Valeurs mètre carré absurde
         metre_carre < 50000,
         metre_carre > 1000) %>%
  arrange(-metre_carre) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Paris 7

dvf_2019 %>%
  filter(code_postal == 75007) %>%
  select(6, 8, 5, lot1_surface_carrez, lot2_surface_carrez) %>%
  filter(lot1_surface_carrez != 0) %>%
  mutate(metre_carre = round(valeur_fonciere / lot1_surface_carrez)) %>%
  filter(!is.na(metre_carre),
         # Valeurs mètre carré absurde
         metre_carre < 50000,
         metre_carre > 1000) %>%
  arrange(-metre_carre) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Paris 6

dvf_2019 %>%
  filter(code_postal == 75006) %>%
  select(6, 8, 5, lot1_surface_carrez, lot2_surface_carrez) %>%
  filter(lot1_surface_carrez != 0) %>%
  mutate(metre_carre = round(valeur_fonciere / lot1_surface_carrez)) %>%
  filter(!is.na(metre_carre),
         # Valeurs mètre carré absurde
         metre_carre < 50000,
         metre_carre > 1000) %>%
  arrange(-metre_carre) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Paris 14

dvf_2019 %>%
  filter(code_postal == 75014) %>%
  select(6, 8, 5, lot1_surface_carrez, lot2_surface_carrez) %>%
  filter(lot1_surface_carrez != 0) %>%
  mutate(metre_carre = round(valeur_fonciere / lot1_surface_carrez)) %>%
  filter(!is.na(metre_carre),
         # Valeurs mètre carré absurde
         metre_carre < 50000,
         metre_carre > 1000) %>%
  arrange(-metre_carre) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}