pacman::p_load(
here, # file locator
tidyverse, # data management and ggplot2 graphics
skimr, # get overview of data
janitor, # produce and adorn tabulations and cross-tabulations
tsibble,
imputeTS
)GOOGLE data
Load packages:
The data published by Google offers information related to mobility using the Google ecosystem application services such as Android. The dataset information is available worldwide link, but in our case, only the information relating to Spain was extracted.
It provides detail information about:
CA: autonomous communities codes.
province: province names.
iso_3166_2_code: province iso code
fecha: date.
mob_grocery_pharmacy: Mobility trends for places like grocery markets, food warehouses, farmers markets, specialty food shops, drug, stores, and pharmacies.
mob_parks: Mobility trends for places like national parks, public beaches, marinas, dog parks, plazas, and public garden.
mob_residential: Mobility trends for places of residence.
mob_retail_recreation: Mobility trends for places like restaurants, cafes, shopping centers, theme parks, museums, libraries, and movie theaters.
mob_transit_stations: Mobility trends for places like public transport hubs such as subway, bus, and train stations.
mob_workplaces: Mobility trends for places of work.
# List local google raw files
google_files <- list.files(
path = here("data", "raw"),
recursive = TRUE,
full.names = TRUE,
pattern = "*Region_Mobility_Report.csv"
)google_data <- map_dfr(
.x = google_files,
.f = ~read_csv(.x, show_col_types = FALSE)
)
google_data# A tibble: 50,702 × 15
country_region_code country_region sub_region_1 sub_region_2 metro_area
<chr> <chr> <chr> <chr> <lgl>
1 ES Spain <NA> <NA> NA
2 ES Spain <NA> <NA> NA
3 ES Spain <NA> <NA> NA
4 ES Spain <NA> <NA> NA
5 ES Spain <NA> <NA> NA
6 ES Spain <NA> <NA> NA
7 ES Spain <NA> <NA> NA
8 ES Spain <NA> <NA> NA
9 ES Spain <NA> <NA> NA
10 ES Spain <NA> <NA> NA
# … with 50,692 more rows, and 10 more variables: iso_3166_2_code <chr>,
# census_fips_code <lgl>, place_id <chr>, date <date>,
# retail_and_recreation_percent_change_from_baseline <dbl>,
# grocery_and_pharmacy_percent_change_from_baseline <dbl>,
# parks_percent_change_from_baseline <dbl>,
# transit_stations_percent_change_from_baseline <dbl>,
# workplaces_percent_change_from_baseline <dbl>, …skim(google_data)| Name | google_data |
| Number of rows | 50702 |
| Number of columns | 15 |
| _______________________ | |
| Column type frequency: | |
| character | 6 |
| Date | 1 |
| logical | 2 |
| numeric | 6 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| country_region_code | 0 | 1.00 | 2 | 2 | 0 | 1 | 0 |
| country_region | 0 | 1.00 | 5 | 5 | 0 | 1 | 0 |
| sub_region_1 | 805 | 0.98 | 5 | 19 | 0 | 19 | 0 |
| sub_region_2 | 16087 | 0.68 | 4 | 22 | 0 | 43 | 0 |
| iso_3166_2_code | 805 | 0.98 | 4 | 5 | 0 | 62 | 0 |
| place_id | 0 | 1.00 | 27 | 27 | 0 | 63 | 0 |
Variable type: Date
| skim_variable | n_missing | complete_rate | min | max | median | n_unique |
|---|---|---|---|---|---|---|
| date | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
Variable type: logical
| skim_variable | n_missing | complete_rate | mean | count |
|---|---|---|---|---|
| metro_area | 50702 | 0 | NaN | : |
| census_fips_code | 50702 | 0 | NaN | : |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| retail_and_recreation_percent_change_from_baseline | 56 | 1.00 | -24.20 | 25.84 | -97 | -34 | -20 | -9 | 100 | ▂▇▇▁▁ |
| grocery_and_pharmacy_percent_change_from_baseline | 845 | 0.98 | 2.55 | 26.92 | -96 | -7 | 5 | 15 | 258 | ▁▇▁▁▁ |
| parks_percent_change_from_baseline | 305 | 0.99 | 16.83 | 57.82 | -94 | -14 | 8 | 36 | 569 | ▇▂▁▁▁ |
| transit_stations_percent_change_from_baseline | 1410 | 0.97 | -16.74 | 28.68 | -100 | -31 | -15 | -1 | 177 | ▂▇▁▁▁ |
| workplaces_percent_change_from_baseline | 42 | 1.00 | -20.91 | 19.27 | -92 | -29 | -16 | -9 | 70 | ▁▂▇▁▁ |
| residential_percent_change_from_baseline | 387 | 0.99 | 5.77 | 7.49 | -12 | 1 | 4 | 8 | 48 | ▂▇▁▁▁ |
There are some discrepancies between the NA data.
sub_region_1 and iso_3166_2_code has a total of 98,4% of completness while sub_region_2 has only 68,3%. One of the reasons could be that some sub_regions in Spain are considered both Autonomous Communities (AC)/Autonomous Cities (C) and Provinces (Pr).
For those cases, sub_region_2 contains missing values.
# Fix sub_region_2 missing data
google_data <- google_data %>%
mutate(
sub_region_2 = case_when(
sub_region_1 == "Asturias" ~ "Asturias",
sub_region_1 == "Balearic Islands" ~ "Baleares",
sub_region_1 == "Cantabria" ~ "Cantabria",
sub_region_1 == "Ceuta" ~ "Ceuta",
sub_region_1 == "Community of Madrid" ~ "Madrid",
sub_region_1 == "La Rioja" ~ "Rioja",
sub_region_1 == "Melilla" ~ "Melilla",
sub_region_1 == "Navarre" ~ "Navarra",
sub_region_1 == "Region of Murcia" ~ "Murcia",
TRUE ~ sub_region_2
)
)google_data %>%
tabyl(sub_region_1) %>%
adorn_pct_formatting() sub_region_1 n percent valid_percent
Andalusia 7245 14.3% 14.5%
Aragon 3220 6.4% 6.5%
Asturias 805 1.6% 1.6%
Balearic Islands 805 1.6% 1.6%
Basque Country 3220 6.4% 6.5%
Canary Islands 2415 4.8% 4.8%
Cantabria 805 1.6% 1.6%
Castile and León 8050 15.9% 16.1%
Castile-La Mancha 4830 9.5% 9.7%
Catalonia 4025 7.9% 8.1%
Ceuta 798 1.6% 1.6%
Community of Madrid 805 1.6% 1.6%
Extremadura 2415 4.8% 4.8%
Galicia 4025 7.9% 8.1%
La Rioja 805 1.6% 1.6%
Melilla 799 1.6% 1.6%
Navarre 805 1.6% 1.6%
Region of Murcia 805 1.6% 1.6%
Valencian Community 3220 6.4% 6.5%
<NA> 805 1.6% -table(google_data$sub_region_2)
A Coruña Álava Albacete
805 805 805
Alicante Almería Asturias
805 805 805
Ávila Badajoz Baleares
805 805 805
Barcelona Biscay Burgos
805 805 805
Cáceres Cádiz Cantabria
805 805 805
Castellón Ceuta Ciudad Real
805 798 805
Córdoba Cuenca Gipuzkoa
805 805 805
Girona Granada Guadalajara
805 805 805
Huelva Huesca Jaén
805 805 805
Las Palmas León Lleida
805 805 805
Lugo Madrid Málaga
805 805 805
Melilla Murcia Navarra
799 805 805
Palencia Pontevedra Province of Ourense
805 805 805
Rioja Salamanca Santa Cruz de Tenerife
805 805 805
Segovia Seville Soria
805 805 805
Tarragona Teruel Toledo
805 805 805
Valencia Valladolid Zamora
805 805 805
Zaragoza
805 To clean the data, the following actions will be taken:
- NA data from sub_region_1 and 2 will be eliminated.
- Some columns do not add usefull information for our analysis shuch as “country_region_code”, “metro_area”, “census_fips_code” and “place_id”. So, they will be eliminated from the dataset
- Column names are too longer and contain redundant information. We are going to rename them.
google_data <- google_data %>%
drop_na(sub_region_1, sub_region_2) %>%
select(-country_region, -country_region_code, -metro_area, -census_fips_code, -place_id) %>%
rename(
"CA" = sub_region_1,
"province" = sub_region_2,
"fecha" = date,
"retail_recreation" = retail_and_recreation_percent_change_from_baseline,
"grocery_pharmacy" = grocery_and_pharmacy_percent_change_from_baseline,
"parks" = parks_percent_change_from_baseline,
"transit_stations" = transit_stations_percent_change_from_baseline,
"workplaces" = workplaces_percent_change_from_baseline,
"residential" = residential_percent_change_from_baseline
)
google_data# A tibble: 41,847 × 10
CA province iso_3166_2_code fecha retail_recreati… grocery_pharmacy
<chr> <chr> <chr> <date> <dbl> <dbl>
1 Andalu… Almería ES-AL 2020-02-15 5 -3
2 Andalu… Almería ES-AL 2020-02-16 -2 0
3 Andalu… Almería ES-AL 2020-02-17 0 -2
4 Andalu… Almería ES-AL 2020-02-18 -3 -3
5 Andalu… Almería ES-AL 2020-02-19 -1 -3
6 Andalu… Almería ES-AL 2020-02-20 1 -2
7 Andalu… Almería ES-AL 2020-02-21 2 -1
8 Andalu… Almería ES-AL 2020-02-22 4 -1
9 Andalu… Almería ES-AL 2020-02-23 1 4
10 Andalu… Almería ES-AL 2020-02-24 1 0
# … with 41,837 more rows, and 4 more variables: parks <dbl>,
# transit_stations <dbl>, workplaces <dbl>, residential <dbl>skim(google_data)| Name | google_data |
| Number of rows | 41847 |
| Number of columns | 10 |
| _______________________ | |
| Column type frequency: | |
| character | 3 |
| Date | 1 |
| numeric | 6 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| CA | 0 | 1 | 5 | 19 | 0 | 19 | 0 |
| province | 0 | 1 | 4 | 22 | 0 | 52 | 0 |
| iso_3166_2_code | 0 | 1 | 4 | 5 | 0 | 52 | 0 |
Variable type: Date
| skim_variable | n_missing | complete_rate | min | max | median | n_unique |
|---|---|---|---|---|---|---|
| fecha | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| retail_recreation | 56 | 1.00 | -23.70 | 26.35 | -97 | -34 | -20 | -8 | 100 | ▂▇▇▁▁ |
| grocery_pharmacy | 473 | 0.99 | 3.12 | 27.63 | -96 | -7 | 5 | 16 | 258 | ▁▇▁▁▁ |
| parks | 305 | 0.99 | 18.24 | 60.28 | -94 | -14 | 9 | 38 | 569 | ▇▂▁▁▁ |
| transit_stations | 1410 | 0.97 | -16.01 | 29.57 | -100 | -32 | -15 | 1 | 177 | ▂▇▂▁▁ |
| workplaces | 42 | 1.00 | -20.59 | 19.36 | -92 | -29 | -16 | -8 | 70 | ▁▂▇▁▁ |
| residential | 387 | 0.99 | 5.76 | 7.47 | -12 | 1 | 4 | 8 | 48 | ▂▇▁▁▁ |
At this point, only the numeric variables contains NAs. As this information is embedded in time series, it will be possible to impute missing values.
Missing values are presented in all the provinces but mostly in Ceuta and Melilla.
google_data %>%
pivot_longer(cols = 5:10, names_to = "variables") %>%
filter(is.na(value)) %>%
pull(province) %>%
table() %>%
sort(decreasing = TRUE).
Ceuta Melilla Soria Asturias
1054 623 146 103
Murcia Teruel Palencia Cuenca
96 59 53 52
Ávila Huesca Zamora Rioja
51 49 49 45
Burgos Segovia Province of Ourense Cantabria
37 35 29 28
Lugo Huelva Cáceres Guadalajara
28 25 22 21
Lleida León Ciudad Real Albacete
17 15 10 8
Navarra Álava Jaén Salamanca
7 3 3 3
Madrid Valladolid
1 1 To impute missing data, we will convert the data to time series:
google_TimeS <- google_data %>%
pivot_longer(cols = 5:10, names_to = "variables") %>%
as_tsibble(index = fecha, key = c(variables, province))For the imputation of missing values the procedure to be followed will be as follows:
- First, we separate (group) by the source of mobility (pharmacy, etc…)
- Secondly, we will interpolate missing data
- Finally, we will combine the data again
The interpolation uses either linear, spline or stineman interpolation to replace missing values. In our case, we will use the linear one.
As an example, we will show how interpolation works for “grocery_pharmacy” data in Asturias.
imp <- google_TimeS %>%
filter(variables == "grocery_pharmacy") %>%
select(-variables) %>%
group_by(province) %>%
na_interpolation() %>%
rename("mob_grocery_pharmacy" = value) %>%
filter(province == "Asturias")interpolation_test <- google_TimeS %>%
filter(variables == "grocery_pharmacy") %>%
select(-variables) %>%
rename("mob_grocery_pharmacy" = value) %>%
filter(province == "Asturias")ggplot_na_imputations(interpolation_test$mob_grocery_pharmacy, imp$mob_grocery_pharmacy)
The interpolation works fine, so we will proceed to impute missing data for the rest of provinces/variables.
grocery_pharmacy_data <- google_TimeS %>%
filter(variables == "grocery_pharmacy") %>%
select(-variables) %>%
group_by(province) %>%
na_interpolation() %>%
rename("mob_grocery_pharmacy" = value)grocery_parks_data <- google_TimeS %>%
filter(variables == "parks") %>%
select(-variables) %>%
group_by(province) %>%
na_interpolation() %>%
rename("mob_parks" = value)grocery_residential_data <- google_TimeS %>%
filter(variables == "residential") %>%
select(-variables) %>%
group_by(province) %>%
na_interpolation() %>%
rename("mob_residential" = value)grocery_retail_recreation_data <- google_TimeS %>%
filter(variables == "retail_recreation") %>%
select(-variables) %>%
group_by(province) %>%
na_interpolation() %>%
rename("mob_retail_recreation" = value)grocery_transit_stations_data <- google_TimeS %>%
filter(variables == "transit_stations") %>%
select(-variables) %>%
group_by(province) %>%
na_interpolation() %>%
rename("mob_transit_stations" = value)grocery_workplaces_data <- google_TimeS %>%
filter(variables == "workplaces") %>%
select(-variables) %>%
group_by(province) %>%
na_interpolation() %>%
rename("mob_workplaces" = value)Once imputed missing data, we can combine the data again
google_TimeS_imputed <- grocery_pharmacy_data %>%
inner_join(grocery_parks_data, by=c("CA", "province", "iso_3166_2_code", "fecha")) %>%
inner_join(grocery_residential_data, by=c("CA", "province", "iso_3166_2_code", "fecha")) %>%
inner_join(grocery_retail_recreation_data, by=c("CA", "province", "iso_3166_2_code", "fecha")) %>%
inner_join(grocery_transit_stations_data, by=c("CA", "province", "iso_3166_2_code", "fecha")) %>%
inner_join(grocery_workplaces_data, by=c("CA", "province", "iso_3166_2_code", "fecha"))
google_TimeS_imputed# A tibble: 41,847 × 10
# Groups: province [52]
CA province iso_3166_2_code fecha mob_grocery_pharmacy mob_parks
<chr> <chr> <chr> <date> <dbl> <dbl>
1 Galicia A Coruña ES-C 2020-02-15 -2 -15
2 Galicia A Coruña ES-C 2020-02-16 -19 -27
3 Galicia A Coruña ES-C 2020-02-17 4 28
4 Galicia A Coruña ES-C 2020-02-18 0 21
5 Galicia A Coruña ES-C 2020-02-19 0 22
6 Galicia A Coruña ES-C 2020-02-20 3 17
7 Galicia A Coruña ES-C 2020-02-21 -1 27
8 Galicia A Coruña ES-C 2020-02-22 -4 32
9 Galicia A Coruña ES-C 2020-02-23 10 29
10 Galicia A Coruña ES-C 2020-02-24 13 71
# … with 41,837 more rows, and 4 more variables: mob_residential <dbl>,
# mob_retail_recreation <dbl>, mob_transit_stations <dbl>,
# mob_workplaces <dbl>Apart from missing data, there are also some gaps in the data for Ceuta and Melilla.
google_TimeS_imputed %>%
pivot_longer(cols = 5:10, names_to = "variables") %>%
as_tsibble(index = fecha, key = c(variables, province)) %>%
has_gaps(.full = TRUE) %>%
filter(.gaps == TRUE)# A tibble: 12 × 3
variables province .gaps
<chr> <chr> <lgl>
1 mob_grocery_pharmacy Ceuta TRUE
2 mob_grocery_pharmacy Melilla TRUE
3 mob_parks Ceuta TRUE
4 mob_parks Melilla TRUE
5 mob_residential Ceuta TRUE
6 mob_residential Melilla TRUE
7 mob_retail_recreation Ceuta TRUE
8 mob_retail_recreation Melilla TRUE
9 mob_transit_stations Ceuta TRUE
10 mob_transit_stations Melilla TRUE
11 mob_workplaces Ceuta TRUE
12 mob_workplaces Melilla TRUE google_gaps <- google_TimeS_imputed %>%
pivot_longer(cols = 5:10, names_to = "variables") %>%
as_tsibble(index = fecha, key = c(variables, province)) %>%
count_gaps(.full = TRUE)
google_gaps# A tibble: 42 × 5
variables province .from .to .n
<chr> <chr> <date> <date> <int>
1 mob_grocery_pharmacy Ceuta 2020-08-22 2020-08-23 2
2 mob_grocery_pharmacy Ceuta 2020-08-29 2020-08-30 2
3 mob_grocery_pharmacy Ceuta 2020-09-02 2020-09-02 1
4 mob_grocery_pharmacy Ceuta 2020-09-05 2020-09-06 2
5 mob_grocery_pharmacy Melilla 2020-08-22 2020-08-23 2
6 mob_grocery_pharmacy Melilla 2020-08-29 2020-08-30 2
7 mob_grocery_pharmacy Melilla 2020-09-05 2020-09-06 2
8 mob_parks Ceuta 2020-08-22 2020-08-23 2
9 mob_parks Ceuta 2020-08-29 2020-08-30 2
10 mob_parks Ceuta 2020-09-02 2020-09-02 1
# … with 32 more rowsSince in further analysis we will not use “Ceuta” or “Melilla” data, we chose to eliminate them rather than to impute the missing values.
google_TimeS_imputed <- google_TimeS_imputed %>%
filter(!province %in% c("Ceuta", "Melilla"))
google_TimeS_imputed# A tibble: 40,250 × 10
# Groups: province [50]
CA province iso_3166_2_code fecha mob_grocery_pharmacy mob_parks
<chr> <chr> <chr> <date> <dbl> <dbl>
1 Galicia A Coruña ES-C 2020-02-15 -2 -15
2 Galicia A Coruña ES-C 2020-02-16 -19 -27
3 Galicia A Coruña ES-C 2020-02-17 4 28
4 Galicia A Coruña ES-C 2020-02-18 0 21
5 Galicia A Coruña ES-C 2020-02-19 0 22
6 Galicia A Coruña ES-C 2020-02-20 3 17
7 Galicia A Coruña ES-C 2020-02-21 -1 27
8 Galicia A Coruña ES-C 2020-02-22 -4 32
9 Galicia A Coruña ES-C 2020-02-23 10 29
10 Galicia A Coruña ES-C 2020-02-24 13 71
# … with 40,240 more rows, and 4 more variables: mob_residential <dbl>,
# mob_retail_recreation <dbl>, mob_transit_stations <dbl>,
# mob_workplaces <dbl>skim(google_TimeS_imputed)| Name | google_TimeS_imputed |
| Number of rows | 40250 |
| Number of columns | 10 |
| _______________________ | |
| Column type frequency: | |
| character | 2 |
| Date | 1 |
| numeric | 6 |
| ________________________ | |
| Group variables | province |
Variable type: character
| skim_variable | province | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|---|
| CA | A Coruña | 0 | 1 | 7 | 7 | 0 | 1 | 0 |
| CA | Álava | 0 | 1 | 14 | 14 | 0 | 1 | 0 |
| CA | Albacete | 0 | 1 | 17 | 17 | 0 | 1 | 0 |
| CA | Alicante | 0 | 1 | 19 | 19 | 0 | 1 | 0 |
| CA | Almería | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Asturias | 0 | 1 | 8 | 8 | 0 | 1 | 0 |
| CA | Ávila | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Badajoz | 0 | 1 | 11 | 11 | 0 | 1 | 0 |
| CA | Baleares | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Barcelona | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Biscay | 0 | 1 | 14 | 14 | 0 | 1 | 0 |
| CA | Burgos | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Cáceres | 0 | 1 | 11 | 11 | 0 | 1 | 0 |
| CA | Cádiz | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Cantabria | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Castellón | 0 | 1 | 19 | 19 | 0 | 1 | 0 |
| CA | Ciudad Real | 0 | 1 | 17 | 17 | 0 | 1 | 0 |
| CA | Córdoba | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Cuenca | 0 | 1 | 17 | 17 | 0 | 1 | 0 |
| CA | Gipuzkoa | 0 | 1 | 14 | 14 | 0 | 1 | 0 |
| CA | Girona | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Granada | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Guadalajara | 0 | 1 | 17 | 17 | 0 | 1 | 0 |
| CA | Huelva | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Huesca | 0 | 1 | 6 | 6 | 0 | 1 | 0 |
| CA | Jaén | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Las Palmas | 0 | 1 | 14 | 14 | 0 | 1 | 0 |
| CA | León | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Lleida | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Lugo | 0 | 1 | 7 | 7 | 0 | 1 | 0 |
| CA | Madrid | 0 | 1 | 19 | 19 | 0 | 1 | 0 |
| CA | Málaga | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Murcia | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Navarra | 0 | 1 | 7 | 7 | 0 | 1 | 0 |
| CA | Palencia | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Pontevedra | 0 | 1 | 7 | 7 | 0 | 1 | 0 |
| CA | Province of Ourense | 0 | 1 | 7 | 7 | 0 | 1 | 0 |
| CA | Rioja | 0 | 1 | 8 | 8 | 0 | 1 | 0 |
| CA | Salamanca | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Santa Cruz de Tenerife | 0 | 1 | 14 | 14 | 0 | 1 | 0 |
| CA | Segovia | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Seville | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Soria | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Tarragona | 0 | 1 | 9 | 9 | 0 | 1 | 0 |
| CA | Teruel | 0 | 1 | 6 | 6 | 0 | 1 | 0 |
| CA | Toledo | 0 | 1 | 17 | 17 | 0 | 1 | 0 |
| CA | Valencia | 0 | 1 | 19 | 19 | 0 | 1 | 0 |
| CA | Valladolid | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Zamora | 0 | 1 | 16 | 16 | 0 | 1 | 0 |
| CA | Zaragoza | 0 | 1 | 6 | 6 | 0 | 1 | 0 |
| iso_3166_2_code | A Coruña | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Álava | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Albacete | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Alicante | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Almería | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Asturias | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Ávila | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Badajoz | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Baleares | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Barcelona | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Biscay | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Burgos | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Cáceres | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Cádiz | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Cantabria | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Castellón | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Ciudad Real | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Córdoba | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Cuenca | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Gipuzkoa | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Girona | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Granada | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Guadalajara | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Huelva | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Huesca | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Jaén | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Las Palmas | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | León | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Lleida | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Lugo | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Madrid | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Málaga | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Murcia | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Navarra | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Palencia | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Pontevedra | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Province of Ourense | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Rioja | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Salamanca | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Santa Cruz de Tenerife | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Segovia | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Seville | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Soria | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Tarragona | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Teruel | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Toledo | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Valencia | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
| iso_3166_2_code | Valladolid | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Zamora | 0 | 1 | 5 | 5 | 0 | 1 | 0 |
| iso_3166_2_code | Zaragoza | 0 | 1 | 4 | 4 | 0 | 1 | 0 |
Variable type: Date
| skim_variable | province | n_missing | complete_rate | min | max | median | n_unique |
|---|---|---|---|---|---|---|---|
| fecha | A Coruña | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Álava | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Albacete | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Alicante | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Almería | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Asturias | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Ávila | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Badajoz | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Baleares | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Barcelona | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Biscay | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Burgos | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Cáceres | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Cádiz | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Cantabria | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Castellón | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Ciudad Real | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Córdoba | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Cuenca | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Gipuzkoa | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Girona | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Granada | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Guadalajara | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Huelva | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Huesca | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Jaén | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Las Palmas | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | León | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Lleida | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Lugo | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Madrid | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Málaga | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Murcia | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Navarra | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Palencia | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Pontevedra | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Province of Ourense | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Rioja | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Salamanca | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Santa Cruz de Tenerife | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Segovia | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Seville | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Soria | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Tarragona | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Teruel | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Toledo | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Valencia | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Valladolid | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Zamora | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
| fecha | Zaragoza | 0 | 1 | 2020-02-15 | 2022-04-29 | 2021-03-23 | 805 |
Variable type: numeric
| skim_variable | province | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|
| mob_grocery_pharmacy | A Coruña | 0 | 1 | 2.47 | 24.83 | -95 | -3 | 7.00 | 14.0 | 120 | ▁▁▇▁▁ |
| mob_grocery_pharmacy | Álava | 0 | 1 | -0.58 | 22.24 | -93 | -6 | 4.00 | 11.0 | 59 | ▁▁▃▇▁ |
| mob_grocery_pharmacy | Albacete | 0 | 1 | 4.12 | 28.57 | -95 | -4 | 5.00 | 18.0 | 160 | ▁▇▇▁▁ |
| mob_grocery_pharmacy | Alicante | 0 | 1 | 4.62 | 30.23 | -91 | -5 | 5.00 | 17.0 | 157 | ▁▇▆▁▁ |
| mob_grocery_pharmacy | Almería | 0 | 1 | 2.66 | 28.81 | -92 | -7 | 2.00 | 14.0 | 141 | ▁▆▇▁▁ |
| mob_grocery_pharmacy | Asturias | 0 | 1 | -0.76 | 19.96 | -94 | -3 | 3.00 | 9.0 | 42 | ▁▁▁▇▁ |
| mob_grocery_pharmacy | Ávila | 0 | 1 | 16.14 | 36.19 | -93 | 2 | 17.00 | 31.0 | 207 | ▂▇▃▁▁ |
| mob_grocery_pharmacy | Badajoz | 0 | 1 | 4.24 | 26.47 | -92 | -5 | 5.00 | 17.0 | 158 | ▁▇▇▁▁ |
| mob_grocery_pharmacy | Baleares | 0 | 1 | 1.27 | 24.34 | -87 | -8 | 2.00 | 13.0 | 99 | ▁▂▇▁▁ |
| mob_grocery_pharmacy | Barcelona | 0 | 1 | -4.14 | 20.77 | -91 | -10 | 0.00 | 9.0 | 58 | ▁▁▆▇▁ |
| mob_grocery_pharmacy | Biscay | 0 | 1 | 2.48 | 23.59 | -94 | -4 | 8.00 | 16.0 | 59 | ▁▁▂▇▁ |
| mob_grocery_pharmacy | Burgos | 0 | 1 | 8.83 | 29.66 | -94 | 1 | 11.00 | 22.0 | 173 | ▂▇▇▁▁ |
| mob_grocery_pharmacy | Cáceres | 0 | 1 | 1.42 | 24.30 | -93 | -5 | 4.00 | 14.0 | 101 | ▁▁▇▁▁ |
| mob_grocery_pharmacy | Cádiz | 0 | 1 | 5.02 | 30.70 | -92 | -4 | 6.00 | 15.0 | 179 | ▁▇▂▁▁ |
| mob_grocery_pharmacy | Cantabria | 0 | 1 | 10.71 | 33.37 | -92 | -1 | 10.00 | 22.0 | 205 | ▁▇▂▁▁ |
| mob_grocery_pharmacy | Castellón | 0 | 1 | 11.81 | 32.86 | -93 | 0 | 13.00 | 27.0 | 179 | ▂▇▇▁▁ |
| mob_grocery_pharmacy | Ciudad Real | 0 | 1 | -0.50 | 26.79 | -95 | -6 | 1.00 | 8.0 | 162 | ▁▇▃▁▁ |
| mob_grocery_pharmacy | Córdoba | 0 | 1 | 0.96 | 25.85 | -93 | -9 | 4.00 | 13.0 | 164 | ▁▇▅▁▁ |
| mob_grocery_pharmacy | Cuenca | 0 | 1 | 3.81 | 28.39 | -95 | -7 | 5.00 | 18.0 | 180 | ▁▇▃▁▁ |
| mob_grocery_pharmacy | Gipuzkoa | 0 | 1 | -1.58 | 21.61 | -92 | -7 | 2.00 | 10.0 | 52 | ▁▁▂▇▁ |
| mob_grocery_pharmacy | Girona | 0 | 1 | 13.96 | 30.71 | -86 | 2 | 15.00 | 27.0 | 129 | ▁▂▇▂▁ |
| mob_grocery_pharmacy | Granada | 0 | 1 | -8.29 | 22.15 | -93 | -14 | -5.00 | 3.0 | 100 | ▁▂▇▁▁ |
| mob_grocery_pharmacy | Guadalajara | 0 | 1 | 4.96 | 24.11 | -93 | -1 | 9.00 | 15.0 | 91 | ▁▁▇▂▁ |
| mob_grocery_pharmacy | Huelva | 0 | 1 | 18.61 | 38.20 | -89 | 3 | 18.00 | 29.0 | 258 | ▁▇▁▁▁ |
| mob_grocery_pharmacy | Huesca | 0 | 1 | 18.73 | 35.94 | -92 | 3 | 19.00 | 34.0 | 185 | ▁▇▇▁▁ |
| mob_grocery_pharmacy | Jaén | 0 | 1 | 6.35 | 30.42 | -95 | -4 | 8.00 | 19.0 | 213 | ▁▇▁▁▁ |
| mob_grocery_pharmacy | Las Palmas | 0 | 1 | -9.23 | 20.16 | -88 | -18 | -8.00 | 5.0 | 61 | ▁▂▇▅▁ |
| mob_grocery_pharmacy | León | 0 | 1 | 5.59 | 29.61 | -96 | -2 | 8.00 | 18.0 | 182 | ▁▇▃▁▁ |
| mob_grocery_pharmacy | Lleida | 0 | 1 | 5.27 | 24.38 | -90 | -5 | 8.00 | 20.0 | 69 | ▁▁▅▇▁ |
| mob_grocery_pharmacy | Lugo | 0 | 1 | 11.99 | 29.07 | -93 | 3 | 15.00 | 26.0 | 131 | ▁▂▇▁▁ |
| mob_grocery_pharmacy | Madrid | 0 | 1 | -6.40 | 19.37 | -87 | -13 | -3.00 | 6.0 | 50 | ▁▁▆▇▁ |
| mob_grocery_pharmacy | Málaga | 0 | 1 | 2.88 | 30.53 | -91 | -8 | 4.00 | 14.0 | 156 | ▁▇▆▁▁ |
| mob_grocery_pharmacy | Murcia | 0 | 1 | 0.33 | 20.13 | -92 | -4 | 3.00 | 13.0 | 53 | ▁▁▂▇▁ |
| mob_grocery_pharmacy | Navarra | 0 | 1 | 6.88 | 23.15 | -92 | 1 | 11.00 | 18.0 | 74 | ▁▁▅▇▁ |
| mob_grocery_pharmacy | Palencia | 0 | 1 | 3.54 | 25.36 | -94 | -3 | 8.00 | 17.0 | 102 | ▁▂▇▂▁ |
| mob_grocery_pharmacy | Pontevedra | 0 | 1 | 7.17 | 26.29 | -94 | 2 | 10.00 | 18.0 | 154 | ▁▃▇▁▁ |
| mob_grocery_pharmacy | Province of Ourense | 0 | 1 | 3.39 | 25.50 | -95 | -4 | 6.00 | 17.0 | 113 | ▁▁▇▁▁ |
| mob_grocery_pharmacy | Rioja | 0 | 1 | 3.17 | 23.32 | -90 | -3 | 6.00 | 16.0 | 125 | ▁▂▇▁▁ |
| mob_grocery_pharmacy | Salamanca | 0 | 1 | -1.33 | 24.82 | -94 | -8 | 4.00 | 13.0 | 90 | ▁▁▇▂▁ |
| mob_grocery_pharmacy | Santa Cruz de Tenerife | 0 | 1 | -9.84 | 18.64 | -89 | -16 | -6.00 | 2.0 | 43 | ▁▁▅▇▁ |
| mob_grocery_pharmacy | Segovia | 0 | 1 | 18.64 | 31.83 | -93 | 9 | 22.00 | 34.0 | 124 | ▁▁▇▂▁ |
| mob_grocery_pharmacy | Seville | 0 | 1 | -4.90 | 22.74 | -91 | -12 | -1.00 | 7.0 | 117 | ▁▃▇▁▁ |
| mob_grocery_pharmacy | Soria | 0 | 1 | -0.86 | 25.35 | -94 | -10 | 4.00 | 12.0 | 72 | ▁▂▇▇▁ |
| mob_grocery_pharmacy | Tarragona | 0 | 1 | 12.37 | 28.75 | -88 | 2 | 15.00 | 26.0 | 126 | ▁▂▇▁▁ |
| mob_grocery_pharmacy | Teruel | 0 | 1 | 5.79 | 26.99 | -95 | -2 | 8.00 | 19.0 | 104 | ▁▁▇▂▁ |
| mob_grocery_pharmacy | Toledo | 0 | 1 | 3.19 | 24.38 | -94 | -2 | 5.00 | 15.0 | 125 | ▁▁▇▁▁ |
| mob_grocery_pharmacy | Valencia | 0 | 1 | -1.41 | 24.09 | -94 | -7 | 1.00 | 11.0 | 92 | ▁▁▇▁▁ |
| mob_grocery_pharmacy | Valladolid | 0 | 1 | 1.92 | 30.18 | -95 | -8 | 5.00 | 14.0 | 199 | ▁▇▁▁▁ |
| mob_grocery_pharmacy | Zamora | 0 | 1 | 2.46 | 26.15 | -94 | -2 | 5.00 | 13.0 | 150 | ▁▅▇▁▁ |
| mob_grocery_pharmacy | Zaragoza | 0 | 1 | -1.55 | 21.95 | -90 | -9 | 3.00 | 11.0 | 88 | ▁▁▇▂▁ |
| mob_parks | A Coruña | 0 | 1 | 33.56 | 59.36 | -87 | 1 | 26.00 | 58.0 | 303 | ▂▇▂▁▁ |
| mob_parks | Álava | 0 | 1 | 5.60 | 32.65 | -89 | -11 | 8.00 | 26.0 | 136 | ▁▅▇▁▁ |
| mob_parks | Albacete | 0 | 1 | 18.94 | 43.99 | -88 | -6 | 18.00 | 46.0 | 191 | ▂▇▆▁▁ |
| mob_parks | Alicante | 0 | 1 | 20.31 | 54.89 | -93 | -13 | 12.00 | 44.0 | 203 | ▂▇▃▂▁ |
| mob_parks | Almería | 0 | 1 | 23.56 | 56.80 | -90 | -11 | 11.00 | 46.0 | 216 | ▂▇▂▁▁ |
| mob_parks | Asturias | 0 | 1 | 45.19 | 71.02 | -88 | 5 | 33.00 | 70.0 | 333 | ▂▇▂▁▁ |
| mob_parks | Ávila | 0 | 1 | 54.73 | 84.95 | -85 | 3 | 36.00 | 88.0 | 569 | ▇▅▁▁▁ |
| mob_parks | Badajoz | 0 | 1 | -7.12 | 25.91 | -83 | -18 | -4.00 | 8.0 | 104 | ▁▆▇▁▁ |
| mob_parks | Baleares | 0 | 1 | 48.81 | 74.65 | -92 | 2 | 29.00 | 93.0 | 294 | ▂▇▃▂▁ |
| mob_parks | Barcelona | 0 | 1 | -10.48 | 23.79 | -93 | -19 | -6.00 | 5.0 | 33 | ▁▁▃▇▃ |
| mob_parks | Biscay | 0 | 1 | 9.17 | 39.06 | -93 | -13 | 10.00 | 35.0 | 140 | ▂▅▇▂▁ |
| mob_parks | Burgos | 0 | 1 | 45.82 | 59.50 | -81 | 10 | 35.00 | 78.0 | 260 | ▂▇▃▁▁ |
| mob_parks | Cáceres | 0 | 1 | 16.81 | 40.82 | -83 | -3 | 14.00 | 37.0 | 261 | ▂▇▂▁▁ |
| mob_parks | Cádiz | 0 | 1 | 18.41 | 58.67 | -92 | -16 | 7.00 | 41.0 | 202 | ▂▇▃▂▁ |
| mob_parks | Cantabria | 0 | 1 | 63.89 | 109.13 | -92 | 1 | 36.00 | 92.0 | 543 | ▇▆▁▁▁ |
| mob_parks | Castellón | 0 | 1 | 40.49 | 80.06 | -92 | -8 | 19.00 | 66.0 | 360 | ▅▇▂▁▁ |
| mob_parks | Ciudad Real | 0 | 1 | 5.66 | 34.59 | -87 | -11 | 8.00 | 26.0 | 165 | ▂▇▇▁▁ |
| mob_parks | Córdoba | 0 | 1 | -11.88 | 25.20 | -88 | -23 | -8.00 | 3.0 | 133 | ▁▇▃▁▁ |
| mob_parks | Cuenca | 0 | 1 | 21.96 | 56.06 | -87 | -12 | 14.00 | 49.0 | 360 | ▆▇▂▁▁ |
| mob_parks | Gipuzkoa | 0 | 1 | 11.01 | 51.29 | -94 | -20 | 4.00 | 35.0 | 210 | ▂▇▃▁▁ |
| mob_parks | Girona | 0 | 1 | 64.72 | 117.50 | -90 | -4 | 22.00 | 99.0 | 539 | ▇▃▂▁▁ |
| mob_parks | Granada | 0 | 1 | -6.72 | 34.01 | -91 | -26 | -5.00 | 13.0 | 129 | ▂▇▇▁▁ |
| mob_parks | Guadalajara | 0 | 1 | 19.32 | 43.40 | -85 | -4 | 14.00 | 47.0 | 220 | ▂▇▃▁▁ |
| mob_parks | Huelva | 0 | 1 | 37.97 | 60.11 | -78 | 0 | 27.00 | 63.0 | 228 | ▂▇▃▂▁ |
| mob_parks | Huesca | 0 | 1 | 56.50 | 97.50 | -86 | -5 | 29.00 | 88.0 | 489 | ▇▆▂▁▁ |
| mob_parks | Jaén | 0 | 1 | -1.66 | 28.52 | -87 | -16 | 0.00 | 15.0 | 120 | ▁▅▇▁▁ |
| mob_parks | Las Palmas | 0 | 1 | -25.66 | 22.06 | -93 | -37 | -22.00 | -10.0 | 30 | ▁▁▇▇▁ |
| mob_parks | León | 0 | 1 | 49.33 | 65.41 | -83 | 13 | 37.00 | 79.0 | 355 | ▂▇▂▁▁ |
| mob_parks | Lleida | 0 | 1 | 38.19 | 64.32 | -80 | 2 | 24.00 | 63.0 | 329 | ▃▇▂▁▁ |
| mob_parks | Lugo | 0 | 1 | 26.86 | 55.44 | -77 | -6 | 16.00 | 45.0 | 261 | ▃▇▂▁▁ |
| mob_parks | Madrid | 0 | 1 | -9.83 | 28.19 | -92 | -22 | -6.00 | 10.0 | 77 | ▁▂▇▃▁ |
| mob_parks | Málaga | 0 | 1 | 6.13 | 43.88 | -92 | -18 | 2.00 | 27.0 | 152 | ▂▇▆▂▁ |
| mob_parks | Murcia | 0 | 1 | 6.97 | 38.29 | -92 | -14 | 6.00 | 27.0 | 135 | ▁▆▇▂▁ |
| mob_parks | Navarra | 0 | 1 | 12.19 | 37.84 | -88 | -8 | 10.00 | 36.0 | 134 | ▁▅▇▂▁ |
| mob_parks | Palencia | 0 | 1 | 51.64 | 61.15 | -80 | 16 | 43.00 | 83.0 | 294 | ▂▇▃▁▁ |
| mob_parks | Pontevedra | 0 | 1 | 33.11 | 66.75 | -89 | -3 | 21.00 | 54.0 | 315 | ▃▇▂▁▁ |
| mob_parks | Province of Ourense | 0 | 1 | 14.79 | 40.34 | -83 | -8 | 14.00 | 37.0 | 168 | ▂▇▆▁▁ |
| mob_parks | Rioja | 0 | 1 | 5.99 | 37.34 | -90 | -15 | 5.00 | 27.6 | 138 | ▂▇▇▂▁ |
| mob_parks | Salamanca | 0 | 1 | 9.45 | 40.39 | -89 | -10 | 9.00 | 29.0 | 207 | ▂▇▃▁▁ |
| mob_parks | Santa Cruz de Tenerife | 0 | 1 | -19.53 | 23.72 | -92 | -30 | -16.00 | -4.0 | 64 | ▁▃▇▂▁ |
| mob_parks | Segovia | 0 | 1 | 11.20 | 50.98 | -93 | -19 | 10.00 | 39.0 | 333 | ▅▇▁▁▁ |
| mob_parks | Seville | 0 | 1 | -17.95 | 25.70 | -93 | -30 | -13.00 | -3.0 | 95 | ▁▅▇▁▁ |
| mob_parks | Soria | 0 | 1 | 54.93 | 80.96 | -89 | 7 | 36.00 | 88.0 | 414 | ▅▇▂▁▁ |
| mob_parks | Tarragona | 0 | 1 | 51.91 | 89.18 | -90 | -2 | 21.00 | 94.0 | 369 | ▅▇▂▁▁ |
| mob_parks | Teruel | 0 | 1 | 19.36 | 63.73 | -92 | -18 | 11.00 | 44.0 | 387 | ▇▇▁▁▁ |
| mob_parks | Toledo | 0 | 1 | -8.53 | 31.77 | -89 | -25 | -6.00 | 9.0 | 166 | ▂▇▂▁▁ |
| mob_parks | Valencia | 0 | 1 | 5.68 | 39.02 | -93 | -16 | 5.00 | 25.0 | 106 | ▁▃▇▃▁ |
| mob_parks | Valladolid | 0 | 1 | 15.60 | 37.75 | -90 | -3 | 19.00 | 40.0 | 140 | ▁▃▇▂▁ |
| mob_parks | Zamora | 0 | 1 | 30.29 | 59.94 | -82 | -2 | 19.00 | 52.0 | 377 | ▆▇▁▁▁ |
| mob_parks | Zaragoza | 0 | 1 | 16.17 | 33.00 | -87 | 1 | 19.00 | 36.0 | 222 | ▁▇▃▁▁ |
| mob_residential | A Coruña | 0 | 1 | 6.35 | 7.96 | -7 | 1 | 4.00 | 9.0 | 46 | ▇▇▁▁▁ |
| mob_residential | Álava | 0 | 1 | 6.21 | 8.39 | -10 | 2 | 4.00 | 8.0 | 46 | ▃▇▁▁▁ |
| mob_residential | Albacete | 0 | 1 | 4.59 | 7.92 | -10 | 0 | 2.00 | 6.0 | 43 | ▅▇▁▁▁ |
| mob_residential | Alicante | 0 | 1 | 6.36 | 7.34 | -5 | 2 | 4.00 | 8.0 | 42 | ▇▆▁▁▁ |
| mob_residential | Almería | 0 | 1 | 6.01 | 6.58 | -4 | 2 | 5.00 | 7.0 | 41 | ▇▅▁▁▁ |
| mob_residential | Asturias | 0 | 1 | 5.34 | 7.44 | -8 | 1 | 3.00 | 8.0 | 40 | ▆▇▁▁▁ |
| mob_residential | Ávila | 0 | 1 | 5.77 | 7.24 | -5 | 1 | 4.00 | 8.0 | 40 | ▇▅▁▁▁ |
| mob_residential | Badajoz | 0 | 1 | 4.63 | 6.44 | -7 | 1 | 3.00 | 6.0 | 37 | ▆▇▁▁▁ |
| mob_residential | Baleares | 0 | 1 | 5.53 | 7.81 | -6 | 0 | 4.00 | 8.0 | 40 | ▇▆▁▁▁ |
| mob_residential | Barcelona | 0 | 1 | 9.00 | 8.45 | -7 | 4 | 7.00 | 11.0 | 47 | ▃▇▁▁▁ |
| mob_residential | Biscay | 0 | 1 | 6.32 | 8.25 | -10 | 2 | 4.00 | 9.0 | 45 | ▃▇▁▁▁ |
| mob_residential | Burgos | 0 | 1 | 4.13 | 8.00 | -11 | -1 | 2.00 | 7.0 | 43 | ▃▇▁▁▁ |
| mob_residential | Cáceres | 0 | 1 | 4.27 | 6.46 | -5 | 0 | 2.00 | 6.0 | 36 | ▇▃▁▁▁ |
| mob_residential | Cádiz | 0 | 1 | 5.40 | 7.10 | -5 | 1 | 3.00 | 7.0 | 38 | ▇▆▁▁▁ |
| mob_residential | Cantabria | 0 | 1 | 5.66 | 7.54 | -5 | 1 | 4.00 | 7.0 | 42 | ▇▅▁▁▁ |
| mob_residential | Castellón | 0 | 1 | 6.20 | 7.66 | -6 | 2 | 4.00 | 8.0 | 45 | ▇▅▁▁▁ |
| mob_residential | Ciudad Real | 0 | 1 | 4.91 | 7.22 | -7 | 1 | 3.00 | 6.0 | 42 | ▇▇▁▁▁ |
| mob_residential | Córdoba | 0 | 1 | 5.34 | 6.97 | -6 | 1 | 4.00 | 7.0 | 41 | ▇▇▁▁▁ |
| mob_residential | Cuenca | 0 | 1 | 4.82 | 7.24 | -6 | 0 | 3.00 | 6.0 | 42 | ▇▅▁▁▁ |
| mob_residential | Gipuzkoa | 0 | 1 | 6.57 | 7.91 | -6 | 2 | 5.00 | 9.0 | 44 | ▇▆▁▁▁ |
| mob_residential | Girona | 0 | 1 | 6.71 | 7.54 | -5 | 2 | 5.00 | 9.0 | 42 | ▇▆▂▁▁ |
| mob_residential | Granada | 0 | 1 | 5.96 | 7.32 | -6 | 1 | 4.00 | 8.0 | 40 | ▇▇▂▁▁ |
| mob_residential | Guadalajara | 0 | 1 | 6.80 | 7.83 | -8 | 2 | 5.00 | 8.0 | 46 | ▅▇▁▁▁ |
| mob_residential | Huelva | 0 | 1 | 4.48 | 6.03 | -6 | 1 | 3.00 | 6.0 | 33 | ▆▇▂▁▁ |
| mob_residential | Huesca | 0 | 1 | 4.94 | 6.96 | -7 | 1 | 3.00 | 7.0 | 40 | ▇▇▁▁▁ |
| mob_residential | Jaén | 0 | 1 | 5.63 | 6.75 | -5 | 2 | 4.00 | 7.0 | 40 | ▇▅▁▁▁ |
| mob_residential | Las Palmas | 0 | 1 | 9.09 | 5.72 | 0 | 5 | 8.00 | 10.0 | 40 | ▇▆▁▁▁ |
| mob_residential | León | 0 | 1 | 4.37 | 7.44 | -9 | 0 | 2.00 | 7.0 | 40 | ▅▇▁▁▁ |
| mob_residential | Lleida | 0 | 1 | 5.69 | 7.15 | -7 | 1 | 4.00 | 8.0 | 41 | ▇▇▁▁▁ |
| mob_residential | Lugo | 0 | 1 | 4.74 | 7.47 | -9 | 0 | 3.00 | 7.0 | 44 | ▆▇▁▁▁ |
| mob_residential | Madrid | 0 | 1 | 8.95 | 9.18 | -10 | 4 | 7.00 | 11.0 | 46 | ▂▇▂▁▁ |
| mob_residential | Málaga | 0 | 1 | 6.22 | 7.37 | -4 | 2 | 4.00 | 8.0 | 40 | ▇▆▁▁▁ |
| mob_residential | Murcia | 0 | 1 | 5.04 | 7.38 | -6 | 0 | 3.00 | 7.0 | 42 | ▇▆▁▁▁ |
| mob_residential | Navarra | 0 | 1 | 5.49 | 7.73 | -6 | 1 | 3.00 | 7.0 | 43 | ▇▆▁▁▁ |
| mob_residential | Palencia | 0 | 1 | 4.33 | 7.46 | -9 | 0 | 2.00 | 7.0 | 40 | ▅▇▁▁▁ |
| mob_residential | Pontevedra | 0 | 1 | 6.50 | 8.08 | -6 | 2 | 4.00 | 9.0 | 48 | ▇▅▁▁▁ |
| mob_residential | Province of Ourense | 0 | 1 | 5.28 | 7.75 | -9 | 1 | 3.00 | 8.0 | 44 | ▆▇▁▁▁ |
| mob_residential | Rioja | 0 | 1 | 4.74 | 7.67 | -10 | 0 | 2.00 | 7.0 | 42 | ▅▇▂▁▁ |
| mob_residential | Salamanca | 0 | 1 | 5.42 | 7.41 | -10 | 1 | 3.00 | 8.0 | 40 | ▃▇▁▁▁ |
| mob_residential | Santa Cruz de Tenerife | 0 | 1 | 9.11 | 5.96 | -1 | 6 | 8.00 | 10.0 | 41 | ▇▇▁▁▁ |
| mob_residential | Segovia | 0 | 1 | 5.58 | 7.58 | -6 | 1 | 3.00 | 8.0 | 42 | ▇▆▁▁▁ |
| mob_residential | Seville | 0 | 1 | 5.59 | 7.59 | -7 | 1 | 4.00 | 8.0 | 42 | ▆▇▁▁▁ |
| mob_residential | Soria | 0 | 1 | 4.62 | 7.63 | -8 | 0 | 2.00 | 7.0 | 38 | ▇▇▂▁▁ |
| mob_residential | Tarragona | 0 | 1 | 6.65 | 7.21 | -4 | 2 | 5.00 | 9.0 | 41 | ▇▅▁▁▁ |
| mob_residential | Teruel | 0 | 1 | 4.54 | 7.21 | -9 | 0 | 3.00 | 7.0 | 40 | ▅▇▁▁▁ |
| mob_residential | Toledo | 0 | 1 | 6.69 | 7.63 | -4 | 2 | 5.00 | 8.0 | 45 | ▇▅▁▁▁ |
| mob_residential | Valencia | 0 | 1 | 6.53 | 7.86 | -8 | 2 | 5.00 | 8.0 | 44 | ▅▇▁▁▁ |
| mob_residential | Valladolid | 0 | 1 | 5.54 | 8.03 | -10 | 1 | 3.00 | 8.0 | 43 | ▃▇▁▁▁ |
| mob_residential | Zamora | 0 | 1 | 3.86 | 7.04 | -7 | -1 | 2.00 | 6.0 | 38 | ▇▅▁▁▁ |
| mob_residential | Zaragoza | 0 | 1 | 5.41 | 7.84 | -12 | 1 | 4.00 | 8.0 | 43 | ▂▇▁▁▁ |
| mob_retail_recreation | A Coruña | 0 | 1 | -28.17 | 23.34 | -96 | -37 | -22.00 | -13.0 | 15 | ▁▁▃▇▂ |
| mob_retail_recreation | Álava | 0 | 1 | -30.00 | 21.83 | -96 | -37 | -25.00 | -15.0 | 26 | ▂▂▇▇▁ |
| mob_retail_recreation | Albacete | 0 | 1 | -22.63 | 24.17 | -97 | -28 | -16.00 | -7.0 | 19 | ▁▁▂▇▂ |
| mob_retail_recreation | Alicante | 0 | 1 | -19.75 | 27.20 | -96 | -29 | -14.00 | -2.0 | 39 | ▂▂▆▇▁ |
| mob_retail_recreation | Almería | 0 | 1 | -17.06 | 26.99 | -96 | -28 | -11.00 | 0.0 | 45 | ▁▂▆▇▁ |
| mob_retail_recreation | Asturias | 0 | 1 | -26.49 | 24.13 | -97 | -34 | -21.00 | -11.0 | 15 | ▁▁▃▇▃ |
| mob_retail_recreation | Ávila | 0 | 1 | -15.99 | 36.87 | -95 | -40 | -14.00 | 4.0 | 100 | ▃▇▇▂▁ |
| mob_retail_recreation | Badajoz | 0 | 1 | -27.61 | 22.27 | -96 | -33 | -23.00 | -13.0 | 33 | ▂▂▇▇▁ |
| mob_retail_recreation | Baleares | 0 | 1 | -17.84 | 27.82 | -95 | -28 | -15.00 | 2.0 | 39 | ▂▂▇▇▂ |
| mob_retail_recreation | Barcelona | 0 | 1 | -32.91 | 21.91 | -97 | -43 | -27.00 | -17.0 | 3 | ▁▁▃▇▅ |
| mob_retail_recreation | Biscay | 0 | 1 | -30.21 | 22.30 | -97 | -39 | -25.00 | -15.0 | 9 | ▁▁▃▇▃ |
| mob_retail_recreation | Burgos | 0 | 1 | -23.66 | 25.80 | -96 | -36 | -17.00 | -6.0 | 29 | ▁▂▃▇▁ |
| mob_retail_recreation | Cáceres | 0 | 1 | -21.43 | 26.02 | -96 | -29 | -17.00 | -6.0 | 46 | ▂▂▇▆▁ |
| mob_retail_recreation | Cádiz | 0 | 1 | -15.86 | 28.82 | -96 | -27 | -11.00 | 1.0 | 50 | ▂▂▇▇▂ |
| mob_retail_recreation | Cantabria | 0 | 1 | -16.74 | 30.12 | -96 | -30 | -15.00 | -1.0 | 63 | ▁▂▇▃▁ |
| mob_retail_recreation | Castellón | 0 | 1 | -17.96 | 28.15 | -96 | -27 | -12.00 | -1.0 | 49 | ▂▂▇▇▁ |
| mob_retail_recreation | Ciudad Real | 0 | 1 | -27.90 | 22.74 | -97 | -33 | -23.00 | -14.0 | 42 | ▁▁▇▃▁ |
| mob_retail_recreation | Córdoba | 0 | 1 | -26.62 | 21.36 | -96 | -33 | -22.00 | -13.0 | 23 | ▁▁▅▇▁ |
| mob_retail_recreation | Cuenca | 0 | 1 | -16.85 | 30.79 | -96 | -31 | -14.00 | 1.0 | 70 | ▂▂▇▃▁ |
| mob_retail_recreation | Gipuzkoa | 0 | 1 | -29.78 | 20.82 | -96 | -35 | -25.00 | -16.0 | 12 | ▁▁▃▇▂ |
| mob_retail_recreation | Girona | 0 | 1 | -12.74 | 34.29 | -95 | -34 | -8.00 | 8.0 | 82 | ▂▃▇▃▁ |
| mob_retail_recreation | Granada | 0 | 1 | -30.60 | 23.27 | -97 | -40 | -24.00 | -15.0 | 23 | ▂▂▆▇▁ |
| mob_retail_recreation | Guadalajara | 0 | 1 | -22.43 | 23.79 | -96 | -29 | -15.00 | -7.0 | 27 | ▁▁▃▇▁ |
| mob_retail_recreation | Huelva | 0 | 1 | -10.91 | 31.64 | -94 | -26 | -7.00 | 7.0 | 66 | ▂▂▇▅▁ |
| mob_retail_recreation | Huesca | 0 | 1 | -21.27 | 27.71 | -96 | -35 | -18.00 | -5.0 | 61 | ▁▂▇▂▁ |
| mob_retail_recreation | Jaén | 0 | 1 | -27.36 | 21.50 | -97 | -34 | -23.00 | -14.0 | 27 | ▁▁▆▇▁ |
| mob_retail_recreation | Las Palmas | 0 | 1 | -31.09 | 21.83 | -97 | -39 | -29.00 | -14.0 | 15 | ▂▁▇▇▂ |
| mob_retail_recreation | León | 0 | 1 | -23.45 | 26.64 | -96 | -35 | -16.00 | -7.0 | 34 | ▂▂▅▇▁ |
| mob_retail_recreation | Lleida | 0 | 1 | -27.55 | 23.10 | -95 | -40 | -22.00 | -12.0 | 18 | ▁▁▃▇▂ |
| mob_retail_recreation | Lugo | 0 | 1 | -21.54 | 26.90 | -95 | -33 | -15.00 | -4.0 | 44 | ▂▂▇▇▁ |
| mob_retail_recreation | Madrid | 0 | 1 | -32.62 | 21.35 | -96 | -38 | -28.00 | -19.0 | 4 | ▁▁▃▇▂ |
| mob_retail_recreation | Málaga | 0 | 1 | -21.14 | 26.07 | -97 | -31 | -16.00 | -4.0 | 30 | ▁▁▅▇▂ |
| mob_retail_recreation | Murcia | 0 | 1 | -27.37 | 21.76 | -96 | -34 | -22.00 | -13.0 | 7 | ▁▁▂▇▅ |
| mob_retail_recreation | Navarra | 0 | 1 | -23.26 | 22.90 | -95 | -30 | -18.00 | -9.0 | 23 | ▁▁▃▇▁ |
| mob_retail_recreation | Palencia | 0 | 1 | -19.57 | 28.81 | -97 | -34 | -13.00 | 0.0 | 45 | ▂▂▆▇▁ |
| mob_retail_recreation | Pontevedra | 0 | 1 | -25.54 | 23.57 | -95 | -36 | -19.00 | -11.0 | 17 | ▁▁▃▇▂ |
| mob_retail_recreation | Province of Ourense | 0 | 1 | -25.16 | 23.78 | -96 | -34 | -19.00 | -10.0 | 49 | ▁▂▇▃▁ |
| mob_retail_recreation | Rioja | 0 | 1 | -23.71 | 24.78 | -96 | -31 | -18.00 | -8.0 | 33 | ▂▁▅▇▁ |
| mob_retail_recreation | Salamanca | 0 | 1 | -29.79 | 24.84 | -97 | -41 | -24.00 | -13.0 | 24 | ▂▂▅▇▁ |
| mob_retail_recreation | Santa Cruz de Tenerife | 0 | 1 | -28.81 | 20.66 | -97 | -33 | -26.00 | -15.0 | 10 | ▁▁▂▇▂ |
| mob_retail_recreation | Segovia | 0 | 1 | -21.20 | 30.42 | -96 | -39 | -14.00 | -2.0 | 62 | ▂▃▇▃▁ |
| mob_retail_recreation | Seville | 0 | 1 | -26.91 | 22.30 | -97 | -35 | -23.00 | -11.0 | 23 | ▁▁▆▇▁ |
| mob_retail_recreation | Soria | 0 | 1 | -17.23 | 33.54 | -96 | -38 | -10.00 | 3.0 | 82 | ▂▃▇▂▁ |
| mob_retail_recreation | Tarragona | 0 | 1 | -15.19 | 31.19 | -95 | -31 | -11.00 | 4.0 | 68 | ▂▃▇▃▁ |
| mob_retail_recreation | Teruel | 0 | 1 | -16.24 | 31.17 | -96 | -32 | -13.00 | 0.0 | 94 | ▂▅▇▁▁ |
| mob_retail_recreation | Toledo | 0 | 1 | -25.87 | 22.78 | -96 | -30 | -19.00 | -12.0 | 17 | ▁▁▂▇▁ |
| mob_retail_recreation | Valencia | 0 | 1 | -26.73 | 23.00 | -96 | -33 | -20.00 | -11.0 | 10 | ▁▁▂▇▅ |
| mob_retail_recreation | Valladolid | 0 | 1 | -29.66 | 23.46 | -97 | -39 | -24.00 | -13.0 | 13 | ▁▁▃▇▂ |
| mob_retail_recreation | Zamora | 0 | 1 | -19.91 | 30.33 | -96 | -37 | -15.00 | -3.0 | 65 | ▂▃▇▃▁ |
| mob_retail_recreation | Zaragoza | 0 | 1 | -29.41 | 20.63 | -96 | -36 | -25.00 | -16.0 | 22 | ▁▁▆▇▁ |
| mob_transit_stations | A Coruña | 0 | 1 | -17.79 | 24.73 | -92 | -30 | -15.00 | 0.0 | 40 | ▁▂▇▇▁ |
| mob_transit_stations | Álava | 0 | 1 | -20.60 | 20.70 | -92 | -28 | -16.00 | -7.0 | 42 | ▁▂▇▇▁ |
| mob_transit_stations | Albacete | 0 | 1 | -18.32 | 21.73 | -92 | -26 | -15.00 | -4.0 | 21 | ▁▁▃▇▃ |
| mob_transit_stations | Alicante | 0 | 1 | -20.98 | 25.62 | -93 | -35 | -18.00 | -1.0 | 24 | ▂▂▇▇▅ |
| mob_transit_stations | Almería | 0 | 1 | -0.41 | 29.26 | -88 | -13 | 2.00 | 19.0 | 61 | ▂▂▇▇▂ |
| mob_transit_stations | Asturias | 0 | 1 | -17.30 | 20.87 | -85 | -26 | -14.00 | -4.0 | 26 | ▁▁▅▇▂ |
| mob_transit_stations | Ávila | 0 | 1 | -9.47 | 28.68 | -90 | -22 | -7.00 | 7.0 | 78 | ▁▂▇▂▁ |
| mob_transit_stations | Badajoz | 0 | 1 | -8.54 | 23.12 | -89 | -16 | -3.00 | 6.0 | 38 | ▁▁▂▇▁ |
| mob_transit_stations | Baleares | 0 | 1 | -2.61 | 44.99 | -92 | -33 | -8.00 | 17.0 | 120 | ▂▇▆▃▁ |
| mob_transit_stations | Barcelona | 0 | 1 | -27.65 | 18.95 | -91 | -35 | -25.00 | -15.0 | 10 | ▁▁▃▇▂ |
| mob_transit_stations | Biscay | 0 | 1 | -26.45 | 18.79 | -91 | -33 | -22.00 | -14.0 | 13 | ▁▁▃▇▁ |
| mob_transit_stations | Burgos | 0 | 1 | 2.38 | 42.13 | -93 | -22 | 5.00 | 24.0 | 135 | ▂▆▇▂▁ |
| mob_transit_stations | Cáceres | 0 | 1 | 9.82 | 44.07 | -94 | -13 | 10.00 | 38.0 | 165 | ▂▇▇▂▁ |
| mob_transit_stations | Cádiz | 0 | 1 | -21.46 | 26.13 | -93 | -35 | -18.00 | -3.0 | 118 | ▂▇▅▁▁ |
| mob_transit_stations | Cantabria | 0 | 1 | -10.91 | 27.11 | -91 | -24 | -7.00 | 6.0 | 49 | ▁▂▆▇▂ |
| mob_transit_stations | Castellón | 0 | 1 | -23.82 | 24.76 | -93 | -39 | -21.00 | -6.0 | 54 | ▂▃▇▃▁ |
| mob_transit_stations | Ciudad Real | 0 | 1 | -26.81 | 23.81 | -95 | -37 | -25.00 | -9.0 | 33 | ▂▂▇▇▁ |
| mob_transit_stations | Córdoba | 0 | 1 | -20.46 | 21.89 | -92 | -30 | -17.00 | -6.0 | 30 | ▁▁▆▇▁ |
| mob_transit_stations | Cuenca | 0 | 1 | -4.59 | 29.80 | -90 | -20 | -2.00 | 11.0 | 101 | ▁▃▇▂▁ |
| mob_transit_stations | Gipuzkoa | 0 | 1 | -16.62 | 19.96 | -89 | -22 | -11.00 | -4.0 | 41 | ▁▁▇▇▁ |
| mob_transit_stations | Girona | 0 | 1 | -11.15 | 29.55 | -90 | -23 | -9.00 | 5.0 | 80 | ▁▂▇▂▁ |
| mob_transit_stations | Granada | 0 | 1 | -14.85 | 26.04 | -91 | -27 | -10.00 | 4.0 | 41 | ▂▁▆▇▂ |
| mob_transit_stations | Guadalajara | 0 | 1 | -11.86 | 28.97 | -93 | -29 | -10.00 | 10.0 | 51 | ▂▂▇▇▂ |
| mob_transit_stations | Huelva | 0 | 1 | 20.34 | 38.52 | -85 | -1 | 22.00 | 48.0 | 107 | ▂▂▇▇▂ |
| mob_transit_stations | Huesca | 0 | 1 | -25.57 | 26.29 | -92 | -42 | -25.00 | -9.0 | 55 | ▂▅▇▂▁ |
| mob_transit_stations | Jaén | 0 | 1 | -21.62 | 20.60 | -94 | -27 | -18.00 | -9.0 | 48 | ▁▁▇▂▁ |
| mob_transit_stations | Las Palmas | 0 | 1 | -25.13 | 24.76 | -92 | -40 | -27.00 | -2.0 | 20 | ▁▂▇▃▅ |
| mob_transit_stations | León | 0 | 1 | -12.26 | 26.59 | -90 | -24 | -10.00 | 3.0 | 61 | ▁▂▇▃▁ |
| mob_transit_stations | Lleida | 0 | 1 | -4.42 | 26.82 | -89 | -15 | 1.00 | 14.0 | 50 | ▁▁▃▇▁ |
| mob_transit_stations | Lugo | 0 | 1 | -7.71 | 32.85 | -90 | -27 | -6.85 | 11.0 | 130 | ▂▇▇▁▁ |
| mob_transit_stations | Madrid | 0 | 1 | -33.40 | 19.63 | -93 | -42 | -32.00 | -19.0 | 10 | ▁▁▇▇▁ |
| mob_transit_stations | Málaga | 0 | 1 | -22.89 | 25.52 | -93 | -37 | -22.00 | -3.0 | 33 | ▂▂▇▆▂ |
| mob_transit_stations | Murcia | 0 | 1 | -21.17 | 19.80 | -89 | -29 | -19.00 | -7.0 | 26 | ▁▁▆▇▁ |
| mob_transit_stations | Navarra | 0 | 1 | -23.33 | 22.52 | -91 | -35 | -18.00 | -7.0 | 16 | ▁▁▅▇▅ |
| mob_transit_stations | Palencia | 0 | 1 | -22.80 | 23.15 | -93 | -34 | -19.00 | -8.0 | 53 | ▁▂▇▃▁ |
| mob_transit_stations | Pontevedra | 0 | 1 | -10.89 | 36.19 | -94 | -34 | -13.00 | 16.0 | 103 | ▂▇▇▃▁ |
| mob_transit_stations | Province of Ourense | 0 | 1 | -20.04 | 25.65 | -93 | -35 | -19.00 | -1.0 | 79 | ▁▆▇▂▁ |
| mob_transit_stations | Rioja | 0 | 1 | -21.79 | 24.65 | -93 | -34 | -16.15 | -4.0 | 40 | ▂▃▇▇▁ |
| mob_transit_stations | Salamanca | 0 | 1 | -14.96 | 26.94 | -94 | -25 | -9.00 | 3.0 | 52 | ▂▂▇▇▁ |
| mob_transit_stations | Santa Cruz de Tenerife | 0 | 1 | -23.83 | 22.16 | -91 | -34 | -25.00 | -5.0 | 27 | ▁▂▇▇▁ |
| mob_transit_stations | Segovia | 0 | 1 | -11.31 | 35.93 | -95 | -33 | -11.00 | 19.0 | 130 | ▃▇▇▁▁ |
| mob_transit_stations | Seville | 0 | 1 | -28.81 | 21.99 | -94 | -40 | -27.00 | -14.0 | 52 | ▁▃▇▂▁ |
| mob_transit_stations | Soria | 0 | 1 | -10.53 | 26.89 | -89 | -26 | -7.00 | 5.0 | 76 | ▁▃▇▂▁ |
| mob_transit_stations | Tarragona | 0 | 1 | -17.46 | 25.20 | -92 | -28 | -14.00 | -3.0 | 52 | ▁▂▇▅▁ |
| mob_transit_stations | Teruel | 0 | 1 | -11.41 | 35.64 | -86 | -40 | -4.15 | 13.0 | 177 | ▅▇▂▁▁ |
| mob_transit_stations | Toledo | 0 | 1 | -27.23 | 20.93 | -94 | -35 | -21.00 | -14.0 | 22 | ▁▁▃▇▁ |
| mob_transit_stations | Valencia | 0 | 1 | -24.41 | 22.42 | -93 | -35 | -21.00 | -9.0 | 53 | ▁▃▇▃▁ |
| mob_transit_stations | Valladolid | 0 | 1 | -19.97 | 24.79 | -93 | -33 | -17.00 | -2.0 | 27 | ▁▂▆▇▃ |
| mob_transit_stations | Zamora | 0 | 1 | 2.78 | 43.37 | -100 | -24 | 4.00 | 30.0 | 145 | ▂▇▇▂▁ |
| mob_transit_stations | Zaragoza | 0 | 1 | -27.45 | 19.35 | -91 | -36 | -24.00 | -15.0 | 10 | ▁▁▅▇▃ |
| mob_workplaces | A Coruña | 0 | 1 | -21.94 | 18.55 | -89 | -29 | -17.00 | -11.0 | 13 | ▁▁▃▇▂ |
| mob_workplaces | Álava | 0 | 1 | -22.64 | 20.28 | -90 | -29 | -15.00 | -9.0 | 11 | ▁▂▂▇▅ |
| mob_workplaces | Albacete | 0 | 1 | -19.12 | 19.09 | -88 | -27 | -12.00 | -7.0 | 12 | ▁▁▂▇▅ |
| mob_workplaces | Alicante | 0 | 1 | -20.08 | 19.36 | -89 | -27 | -14.00 | -9.0 | 25 | ▁▁▃▇▁ |
| mob_workplaces | Almería | 0 | 1 | -17.85 | 18.10 | -87 | -27 | -12.00 | -7.0 | 30 | ▁▁▅▇▁ |
| mob_workplaces | Asturias | 0 | 1 | -23.33 | 17.05 | -88 | -28 | -19.00 | -13.0 | 12 | ▁▁▂▇▁ |
| mob_workplaces | Ávila | 0 | 1 | -13.46 | 22.58 | -84 | -24 | -9.00 | -1.0 | 69 | ▁▃▇▁▁ |
| mob_workplaces | Badajoz | 0 | 1 | -20.37 | 16.99 | -85 | -28 | -14.00 | -9.0 | 9 | ▁▁▂▇▅ |
| mob_workplaces | Baleares | 0 | 1 | -16.41 | 22.67 | -88 | -24 | -15.00 | -6.0 | 70 | ▁▂▇▁▁ |
| mob_workplaces | Barcelona | 0 | 1 | -30.01 | 19.76 | -92 | -39 | -26.00 | -17.0 | 6 | ▁▂▃▇▃ |
| mob_workplaces | Biscay | 0 | 1 | -25.63 | 19.47 | -91 | -33 | -19.00 | -12.0 | 17 | ▁▂▃▇▁ |
| mob_workplaces | Burgos | 0 | 1 | -16.73 | 20.20 | -88 | -25 | -12.00 | -4.0 | 39 | ▁▂▆▇▁ |
| mob_workplaces | Cáceres | 0 | 1 | -14.95 | 19.35 | -85 | -25 | -8.00 | -1.0 | 22 | ▁▁▃▇▃ |
| mob_workplaces | Cádiz | 0 | 1 | -19.24 | 18.85 | -87 | -26 | -14.00 | -8.0 | 20 | ▁▁▃▇▂ |
| mob_workplaces | Cantabria | 0 | 1 | -19.24 | 18.69 | -87 | -25 | -14.00 | -9.0 | 32 | ▁▂▅▇▁ |
| mob_workplaces | Castellón | 0 | 1 | -16.21 | 20.90 | -89 | -24 | -9.00 | -4.0 | 42 | ▁▂▆▇▁ |
| mob_workplaces | Ciudad Real | 0 | 1 | -22.53 | 17.41 | -88 | -29 | -17.00 | -12.0 | 17 | ▁▁▃▇▁ |
| mob_workplaces | Córdoba | 0 | 1 | -22.43 | 17.67 | -88 | -29 | -16.00 | -12.0 | 6 | ▁▁▂▇▅ |
| mob_workplaces | Cuenca | 0 | 1 | -17.28 | 18.09 | -86 | -24 | -12.00 | -7.0 | 33 | ▁▁▅▇▁ |
| mob_workplaces | Gipuzkoa | 0 | 1 | -27.12 | 18.05 | -90 | -32 | -20.00 | -16.0 | 4 | ▁▁▂▇▂ |
| mob_workplaces | Girona | 0 | 1 | -16.25 | 20.65 | -88 | -24 | -12.00 | -5.0 | 52 | ▁▁▇▂▁ |
| mob_workplaces | Granada | 0 | 1 | -25.26 | 18.27 | -88 | -33 | -21.00 | -14.0 | 8 | ▁▁▃▇▃ |
| mob_workplaces | Guadalajara | 0 | 1 | -21.34 | 20.15 | -90 | -32 | -15.00 | -10.0 | 31 | ▁▂▅▇▁ |
| mob_workplaces | Huelva | 0 | 1 | -13.72 | 18.60 | -79 | -22 | -10.00 | -3.0 | 45 | ▁▁▇▅▁ |
| mob_workplaces | Huesca | 0 | 1 | -13.28 | 20.32 | -85 | -23 | -9.00 | 1.0 | 37 | ▁▁▅▇▁ |
| mob_workplaces | Jaén | 0 | 1 | -19.04 | 17.90 | -88 | -25 | -13.00 | -7.0 | 11 | ▁▁▂▇▅ |
| mob_workplaces | Las Palmas | 0 | 1 | -25.87 | 16.63 | -88 | -33 | -22.00 | -15.0 | 5 | ▁▁▂▇▃ |
| mob_workplaces | León | 0 | 1 | -17.66 | 18.92 | -86 | -25 | -13.00 | -5.0 | 26 | ▁▁▃▇▁ |
| mob_workplaces | Lleida | 0 | 1 | -22.03 | 16.96 | -87 | -30 | -17.00 | -11.0 | 5 | ▁▁▂▇▇ |
| mob_workplaces | Lugo | 0 | 1 | -15.89 | 17.41 | -84 | -23 | -10.00 | -4.0 | 19 | ▁▁▂▇▂ |
| mob_workplaces | Madrid | 0 | 1 | -30.44 | 22.60 | -92 | -45 | -27.00 | -15.0 | 20 | ▂▃▇▇▂ |
| mob_workplaces | Málaga | 0 | 1 | -21.63 | 19.72 | -89 | -29 | -18.00 | -10.0 | 29 | ▁▁▆▇▁ |
| mob_workplaces | Murcia | 0 | 1 | -20.34 | 17.68 | -88 | -26 | -16.00 | -10.0 | 13 | ▁▁▂▇▂ |
| mob_workplaces | Navarra | 0 | 1 | -21.07 | 19.43 | -90 | -30 | -14.00 | -8.0 | 15 | ▁▁▃▇▂ |
| mob_workplaces | Palencia | 0 | 1 | -18.42 | 18.35 | -85 | -26 | -12.00 | -6.0 | 21 | ▁▁▃▇▁ |
| mob_workplaces | Pontevedra | 0 | 1 | -22.84 | 17.54 | -89 | -28 | -18.00 | -13.0 | 12 | ▁▁▂▇▂ |
| mob_workplaces | Province of Ourense | 0 | 1 | -19.81 | 17.20 | -85 | -25 | -15.00 | -8.0 | 10 | ▁▁▂▇▅ |
| mob_workplaces | Rioja | 0 | 1 | -19.39 | 19.32 | -89 | -26 | -13.00 | -7.0 | 27 | ▁▁▃▇▁ |
| mob_workplaces | Salamanca | 0 | 1 | -19.55 | 19.86 | -87 | -28 | -14.00 | -6.0 | 16 | ▁▁▃▇▅ |
| mob_workplaces | Santa Cruz de Tenerife | 0 | 1 | -25.31 | 16.79 | -88 | -33 | -21.00 | -14.0 | 2 | ▁▂▂▇▆ |
| mob_workplaces | Segovia | 0 | 1 | -16.72 | 20.47 | -86 | -25 | -11.00 | -5.0 | 45 | ▁▂▇▆▁ |
| mob_workplaces | Seville | 0 | 1 | -23.28 | 19.04 | -90 | -32 | -17.00 | -10.0 | 9 | ▁▁▃▇▅ |
| mob_workplaces | Soria | 0 | 1 | -16.23 | 19.22 | -85 | -24 | -12.00 | -2.0 | 24 | ▁▁▃▇▂ |
| mob_workplaces | Tarragona | 0 | 1 | -19.20 | 19.96 | -88 | -26 | -15.00 | -9.0 | 45 | ▁▁▇▂▁ |
| mob_workplaces | Teruel | 0 | 1 | -18.21 | 18.51 | -87 | -25 | -15.00 | -6.0 | 30 | ▁▁▅▇▁ |
| mob_workplaces | Toledo | 0 | 1 | -23.11 | 17.88 | -89 | -30 | -16.00 | -13.0 | 9 | ▁▁▂▇▂ |
| mob_workplaces | Valencia | 0 | 1 | -23.42 | 19.84 | -90 | -32 | -17.00 | -11.0 | 17 | ▁▁▃▇▂ |
| mob_workplaces | Valladolid | 0 | 1 | -23.80 | 20.12 | -90 | -32 | -18.00 | -11.0 | 15 | ▁▁▃▇▂ |
| mob_workplaces | Zamora | 0 | 1 | -19.79 | 16.76 | -82 | -25 | -17.00 | -11.0 | 27 | ▁▂▆▇▁ |
| mob_workplaces | Zaragoza | 0 | 1 | -21.95 | 19.72 | -90 | -30 | -16.00 | -8.0 | 11 | ▁▁▃▇▆ |