London
lgp
24/5/2021
library(tidyverse)
library(sf)INFORMACIÓN GEOGRÁFICA DE LA CIUDAD DE LONDRES
Los datos de shapes de los distritos de Londres fueron tomadas de https://joshuaboyd1.carto.com/tables/london_boroughs_proper/public/map
Mientras que otros datos estadísticos de Londres fueron tomados del portal de datos abiertos de dicha ciudad https://data.london.gov.uk/
Definimos un dataframe con las geometrias de los distritos de Londres con sus nombres
london_area <- st_read("london_boroughs_proper.geojson", stringsAsFactors=TRUE)## Reading layer `london_boroughs_proper' from data source `C:\Users\LUIS.PEREZ\Documents\Modulo2\london_boroughs_proper.geojson' using driver `GeoJSON'
## Simple feature collection with 33 features and 4 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -0.508813 ymin: 51.28691 xmax: 0.335677 ymax: 51.69207
## Geodetic CRS: WGS 84head(london_area, 10)## Simple feature collection with 10 features and 4 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -0.41808 ymin: 51.28691 xmax: 0.225322 ymax: 51.69207
## Geodetic CRS: WGS 84
## name cartodb_id created_at updated_at
## 1 Barking and Dagenham 1 2015-07-01 06:57:45 2015-07-01 06:57:45
## 2 Barnet 2 2015-07-01 06:57:45 2015-07-01 06:57:45
## 3 Bexley 3 2015-07-01 06:57:45 2015-07-01 06:57:45
## 4 Brent 4 2015-07-01 06:57:45 2015-07-01 06:57:45
## 5 Bromley 5 2015-07-01 06:57:45 2015-07-01 06:57:45
## 6 Camden 6 2015-07-01 06:57:45 2015-07-01 06:57:45
## 7 City of London 7 2015-07-01 06:57:45 2015-07-01 06:57:45
## 8 Croydon 8 2015-07-01 06:57:45 2015-07-01 06:57:45
## 9 Ealing 9 2015-07-01 06:57:45 2015-07-01 06:57:45
## 10 Enfield 10 2015-07-01 06:57:45 2015-07-01 06:57:45
## geometry
## 1 MULTIPOLYGON (((0.148209 51...
## 2 MULTIPOLYGON (((-0.183361 5...
## 3 MULTIPOLYGON (((0.158044 51...
## 4 MULTIPOLYGON (((-0.212138 5...
## 5 MULTIPOLYGON (((0.076463 51...
## 6 MULTIPOLYGON (((-0.140804 5...
## 7 MULTIPOLYGON (((-0.083712 5...
## 8 MULTIPOLYGON (((-0.077495 5...
## 9 MULTIPOLYGON (((-0.334018 5...
## 10 MULTIPOLYGON (((-0.010576 5...str(london_area)## Classes 'sf' and 'data.frame': 33 obs. of 5 variables:
## $ name : Factor w/ 33 levels "Barking and Dagenham",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ cartodb_id: int 1 2 3 4 5 6 7 8 9 10 ...
## $ created_at: POSIXct, format: "2015-07-01 06:57:45" "2015-07-01 06:57:45" ...
## $ updated_at: POSIXct, format: "2015-07-01 06:57:45" "2015-07-01 06:57:45" ...
## $ geometry :sfc_MULTIPOLYGON of length 33; first list element: List of 1
## ..$ :List of 1
## .. ..$ : num [1:1205, 1:2] 0.148 0.148 0.147 0.144 0.144 ...
## ..- attr(*, "class")= chr [1:3] "XY" "MULTIPOLYGON" "sfg"
## - attr(*, "sf_column")= chr "geometry"
## - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA
## ..- attr(*, "names")= chr [1:4] "name" "cartodb_id" "created_at" "updated_at"summary(london_area)## name cartodb_id created_at
## Barking and Dagenham: 1 Min. : 1 Min. :2015-07-01 06:57:45
## Barnet : 1 1st Qu.: 9 1st Qu.:2015-07-01 06:57:45
## Bexley : 1 Median :17 Median :2015-07-01 06:57:45
## Brent : 1 Mean :17 Mean :2015-07-01 06:57:45
## Bromley : 1 3rd Qu.:25 3rd Qu.:2015-07-01 06:57:45
## Camden : 1 Max. :33 Max. :2015-07-01 06:57:45
## (Other) :27
## updated_at geometry
## Min. :2015-07-01 06:57:45 MULTIPOLYGON :33
## 1st Qu.:2015-07-01 06:57:45 epsg:4326 : 0
## Median :2015-07-01 06:57:45 +proj=long...: 0
## Mean :2015-07-01 06:57:45
## 3rd Qu.:2015-07-01 06:57:45
## Max. :2015-07-01 06:57:45
## Primer esquema
ggplot(london_area)+
geom_sf()
Le asociamos etiquetas para identificar espacialmente cada distrito
ggplot(london_area)+
geom_sf()+
labs(title="Distritos de Londres",
x="longitud",
y="latitud")+
geom_sf_label(aes(label=name), size=1.8)## Warning in st_point_on_surface.sfc(sf::st_zm(x)): st_point_on_surface may not
## give correct results for longitude/latitude data
Como información representativa, en particular en terminos poblacionales, de los distritos de Londres tomamos un dataset del portal de Datos Abiertos de la ciudad
london_prof <- read.csv("london-borough-profiles.csv", stringsAsFactors = TRUE)dim(london_prof)## [1] 38 84head(london_prof)## Code Area_name Inner._Outer_London
## 1 E09000001 City of London Inner London
## 2 E09000002 Barking and Dagenham Outer London
## 3 E09000003 Barnet Outer London
## 4 E09000004 Bexley Outer London
## 5 E09000005 Brent Outer London
## 6 E09000006 Bromley Outer London
## GLA_Population_Estimate_2017 GLA_Household_Estimate_2017
## 1 8800 5326
## 2 209000 78188
## 3 389600 151423
## 4 244300 97736
## 5 332100 121048
## 6 327900 140602
## Inland_Area_.Hectares. Population_density_.per_hectare._2017
## 1 290 30.3
## 2 3,611 57.9
## 3 8,675 44.9
## 4 6,058 40.3
## 5 4,323 76.8
## 6 15,013 21.8
## Average_Age._2017 Proportion_of_population_aged_0.15._2015
## 1 43.2 11.4
## 2 32.9 27.2
## 3 37.3 21.1
## 4 39.0 20.6
## 5 35.6 20.9
## 6 40.2 19.9
## Proportion_of_population_of_working.age._2015
## 1 73.1
## 2 63.1
## 3 64.9
## 4 62.9
## 5 67.8
## 6 62.6
## Proportion_of_population_aged_65_and_over._2015 Net_internal_migration_.2015.
## 1 15.5 -7
## 2 9.7 -1176
## 3 14.0 -3379
## 4 16.6 413
## 5 11.3 -7739
## 6 17.5 1342
## Net_international_migration_.2015. Net_natural_change_.2015.
## 1 665 30
## 2 2509 2356
## 3 5407 2757
## 4 760 1095
## 5 7640 3372
## 6 796 1445
## X._of_resident_population_born_abroad_.2015.
## 1 .
## 2 37.8
## 3 35.2
## 4 16.1
## 5 53.9
## 6 18.3
## Largest_migrant_population_by_country_of_birth_.2011.
## 1 United States
## 2 Nigeria
## 3 India
## 4 Nigeria
## 5 India
## 6 India
## X._of_largest_migrant_population_.2011.
## 1 2.8
## 2 4.7
## 3 3.1
## 4 2.6
## 5 9.2
## 6 1.1
## Second_largest_migrant_population_by_country_of_birth_.2011.
## 1 France
## 2 India
## 3 Poland
## 4 India
## 5 Poland
## 6 Ireland
## X._of_second_largest_migrant_population_.2011.
## 1 2
## 2 2.3
## 3 2.4
## 4 1.5
## 5 3.4
## 6 1.1
## Third_largest_migrant_population_by_country_of_birth_.2011.
## 1 Australia
## 2 Pakistan
## 3 Iran
## 4 Ireland
## 5 Ireland
## 6 Nigeria
## X._of_third_largest_migrant_population_.2011.
## 1 1.9
## 2 2.3
## 3 2
## 4 0.9
## 5 2.9
## 6 0.7
## X._of_population_from_BAME_groups_.2016.
## 1 27.5
## 2 49.5
## 3 38.7
## 4 21.4
## 5 64.9
## 6 18.9
## X._people_aged_3._whose_main_language_is_not_English_.2011_Census.
## 1 17.1
## 2 18.7
## 3 23.4
## 4 6
## 5 37.2
## 6 5.8
## Overseas_nationals_entering_the_UK_.NINo.._.2015.16.
## 1 975
## 2 7,538
## 3 13,094
## 4 2,198
## 5 22,162
## 6 2,924
## New_migrant_.NINo._rates._.2015.16.
## 1 152.2
## 2 59.1
## 3 53.1
## 4 14.4
## 5 100.9
## 6 14.4
## Largest_migrant_population_arrived_during_2015.16
## 1 India
## 2 Romania
## 3 Romania
## 4 Romania
## 5 Romania
## 6 Romania
## Second_largest_migrant_population_arrived_during_2015.16
## 1 France
## 2 Bulgaria
## 3 Poland
## 4 Poland
## 5 Italy
## 6 Italy
## Third_largest_migrant_population_arrived_during_2015.16
## 1 United States
## 2 Lithuania
## 3 Italy
## 4 Nigeria
## 5 Portugal
## 6 Spain
## Employment_rate_..._.2015. Male_employment_rate_.2015.
## 1 64.6 .
## 2 65.8 75.6
## 3 68.5 74.5
## 4 75.1 82.1
## 5 69.5 76
## 6 75.3 80.4
## Female_employment_rate_.2015. Unemployment_rate_.2015.
## 1 . .
## 2 56.5 11
## 3 62.9 8.5
## 4 68.5 7.6
## 5 62.6 7.5
## 6 70.4 5.3
## Youth_Unemployment_.claimant._rate_18.24_.Dec.15.
## 1 1.6
## 2 4.5
## 3 1.9
## 4 2.9
## 5 3.1
## 6 2.5
## Proportion_of_16.18_year_olds_who_are_NEET_..._.2014.
## 1 .
## 2 5.7
## 3 2.5
## 4 3.4
## 5 2.6
## 6 4.3
## Proportion_of_the_working.age_population_who_claim_out.of.work_benefits_..._.May.2016.
## 1 3.4
## 2 10.5
## 3 6.2
## 4 6.8
## 5 8.3
## 6 6
## X._working.age_with_a_disability_.2015.
## 1 .
## 2 17.2
## 3 14.9
## 4 15.9
## 5 17.7
## 6 15.9
## Proportion_of_working_age_people_with_no_qualifications_..._2015
## 1 .
## 2 11.3
## 3 5.2
## 4 10.8
## 5 6.2
## 6 4.3
## Proportion_of_working_age_with_degree_or_equivalent_and_above_..._2015
## 1 .
## 2 32.2
## 3 49
## 4 33.5
## 5 45.1
## 6 46.7
## Gross_Annual_Pay._.2016. Gross_Annual_Pay_._Male_.2016.
## 1 . .
## 2 27886 30104
## 3 33443 36475
## 4 34350 37881
## 5 29812 30129
## 6 37682 42026
## Gross_Annual_Pay_._Female_.2016.
## 1 .
## 2 24602
## 3 31235
## 4 28924
## 5 29600
## 6 32491
## Modelled_Household_median_income_estimates_2012.13
## 1 £63,620
## 2 £29,420
## 3 £40,530
## 4 £36,990
## 5 £32,140
## 6 £43,060
## X._adults_that_volunteered_in_past_12_months_.2010.11_to_2012.13.
## 1 .
## 2 20.5
## 3 33.2
## 4 22.1
## 5 17.3
## 6 29
## Number_of_jobs_by_workplace_.2014.
## 1 500400
## 2 58900
## 3 167300
## 4 80700
## 5 133600
## 6 127800
## X._of_employment_that_is_in_public_sector_.2014. Jobs_Density._2015
## 1 3.4 84.3
## 2 21.1 0.5
## 3 18.7 0.7
## 4 15.9 0.6
## 5 17.6 0.6
## 6 13.9 0.6
## Number_of_active_businesses._2015
## 1 26130
## 2 6560
## 3 26190
## 4 9075
## 5 15745
## 6 15695
## Two.year_business_survival_rates_.started_in_2013.
## 1 64.3
## 2 73.0
## 3 73.8
## 4 73.5
## 5 74.4
## 6 78.6
## Crime_rates_per_thousand_population_2014.15
## 1 .
## 2 83.4
## 3 62.7
## 4 51.8
## 5 78.8
## 6 64.1
## Fires_per_thousand_population_.2014.
## 1 12.3
## 2 3
## 3 1.6
## 4 2.3
## 5 1.8
## 6 2.3
## Ambulance_incidents_per_hundred_population_.2014. Median_House_Price._2015
## 1 . 799999
## 2 13.7 243500
## 3 11.1 445000
## 4 11.8 275000
## 5 12.1 407250
## 6 11.2 374975
## Average_Band_D_Council_Tax_charge_...._2015.16
## 1 931.2
## 2 1354.03
## 3 1397.07
## 4 1472.43
## 5 1377.24
## 6 1347.27
## New_Homes_.net._2015.16_.provisional. Homes_Owned_outright._.2014._.
## 1 80 .
## 2 730 16.4
## 3 1460 32.4
## 4 -130 38.1
## 5 1050 22.2
## 6 700 37.8
## Being_bought_with_mortgage_or_loan._.2014._.
## 1 .
## 2 27.4
## 3 25.2
## 4 35.3
## 5 22.6
## 6 34.9
## Rented_from_Local_Authority_or_Housing_Association._.2014._.
## 1 .
## 2 35.9
## 3 11.1
## 4 15.2
## 5 20.4
## 6 13.2
## Rented_from_Private_landlord._.2014._. X._of_area_that_is_Greenspace._2005
## 1 . 4.8
## 2 20.3 33.6
## 3 31.1 41.3
## 4 11.4 31.7
## 5 34.8 21.9
## 6 14.1 57.8
## Total_carbon_emissions_.2014. Household_Waste_Recycling_Rate._2014.15
## 1 1036 34.4
## 2 644 23.4
## 3 1415 38
## 4 975 54
## 5 1175 35.2
## 6 1180 48
## Number_of_cars._.2011_Census. Number_of_cars_per_household._.2011_Census.
## 1 1692 0.4
## 2 56966 0.8
## 3 144717 1.1
## 4 108507 1.2
## 5 87802 0.8
## 6 153908 1.2
## X._of_adults_who_cycle_at_least_once_per_month._2014.15
## 1 16.9
## 2 8.8
## 3 7.4
## 4 10.6
## 5 7.9
## 6 13
## Average_Public_Transport_Accessibility_score._2014
## 1 7.9
## 2 3
## 3 3
## 4 2.6
## 5 3.7
## 6 2.8
## Achievement_of_5_or_more_A.._C_grades_at_GCSE_or_equivalent_including_English_and_Maths._2013.14
## 1 78.6
## 2 58
## 3 67.3
## 4 60.3
## 5 60.1
## 6 68
## Rates_of_Children_Looked_After_.2016.
## 1 101
## 2 69
## 3 35
## 4 46
## 5 45
## 6 40
## X._of_pupils_whose_first_language_is_not_English_.2015.
## 1 .
## 2 41.7
## 3 46
## 4 32.6
## 5 37.6
## 6 38.9
## X._children_living_in_out.of.work_households_.2015.
## 1 7.9
## 2 18.7
## 3 9.3
## 4 12.6
## 5 13.7
## 6 10.2
## Male_life_expectancy._.2012.14. Female_life_expectancy._.2012.14.
## 1 . .
## 2 77.6 82.1
## 3 82.1 85.1
## 4 80.4 84.4
## 5 80.1 85.1
## 6 81.4 84.9
## Teenage_conception_rate_.2014. Life_satisfaction_score_2011.14_.out_of_10.
## 1 . 6.6
## 2 32.4 7.1
## 3 12.8 7.5
## 4 19.5 7.4
## 5 18.5 7.3
## 6 16.7 7.5
## Worthwhileness_score_2011.14_.out_of_10. Happiness_score_2011.14_.out_of_10.
## 1 7.1 6.0
## 2 7.6 7.1
## 3 7.8 7.4
## 4 7.7 7.2
## 5 7.4 7.2
## 6 7.9 7.4
## Anxiety_score_2011.14_.out_of_10. Childhood_Obesity_Prevalance_..._2015.16
## 1 5.6 n/a
## 2 3.1 28.5
## 3 2.8 20.7
## 4 3.3 22.7
## 5 2.9 24.3
## 6 3.3 16
## People_aged_17._with_diabetes_...
## 1 2.6
## 2 7.3
## 3 6
## 4 6.9
## 5 7.9
## 6 5.2
## Mortality_rate_from_causes_considered_preventable_2012.14
## 1 129
## 2 228
## 3 134
## 4 164
## 5 169
## 6 148
## Political_control_in_council
## 1 .
## 2 Lab
## 3 Cons
## 4 Cons
## 5 Lab
## 6 Cons
## Proportion_of_seats_won_by_Conservatives_in_2014_election
## 1 .
## 2 0
## 3 50.8
## 4 71.4
## 5 9.5
## 6 85
## Proportion_of_seats_won_by_Labour_in_2014_election
## 1 .
## 2 100
## 3 .
## 4 23.8
## 5 88.9
## 6 11.7
## Proportion_of_seats_won_by_Lib_Dems_in_2014_election
## 1 .
## 2 0
## 3 1.6
## 4 0
## 5 1.6
## 6 0
## Turnout_at_2014_local_elections
## 1 .
## 2 36.5
## 3 40.5
## 4 39.6
## 5 36.3
## 6 40.8summary(london_prof)## Code Area_name Inner._Outer_London
## E09000001: 1 Barking and Dagenham: 1 : 5
## E09000002: 1 Barnet : 1 Inner London:14
## E09000003: 1 Bexley : 1 Outer London:19
## E09000004: 1 Brent : 1
## E09000005: 1 Bromley : 1
## E09000006: 1 Camden : 1
## (Other) :32 (Other) :32
## GLA_Population_Estimate_2017 GLA_Household_Estimate_2017
## Min. : 8800 . : 2
## 1st Qu.: 242200 104098 : 1
## Median : 290550 105038 : 1
## Mean : 3897766 105887 : 1
## 3rd Qu.: 332775 105981 : 1
## Max. :65999100 107654 : 1
## (Other):31
## Inland_Area_.Hectares. Population_density_.per_hectare._2017 Average_Age._2017
## . : 1 . : 2 Min. :31.40
## 1,212 : 1 108.9 : 1 1st Qu.:35.00
## 1,486 : 1 110.7 : 1 Median :36.25
## 1,640 : 1 111.3 : 1 Mean :36.53
## 1,905 : 1 112.7 : 1 3rd Qu.:38.15
## 1,978 : 1 113 : 1 Max. :43.20
## (Other):32 (Other):31
## Proportion_of_population_aged_0.15._2015
## Min. :11.40
## 1st Qu.:18.00
## Median :20.55
## Mean :20.07
## 3rd Qu.:21.25
## Max. :38.50
##
## Proportion_of_population_of_working.age._2015
## Min. :54.70
## 1st Qu.:64.50
## Median :67.65
## Mean :67.87
## 3rd Qu.:72.00
## Max. :75.30
##
## Proportion_of_population_aged_65_and_over._2015 Net_internal_migration_.2015.
## Min. : 6.00 -1176 : 1
## 1st Qu.: 9.40 -1192 : 1
## Median :12.00 -1480 : 1
## Mean :12.06 -1536 : 1
## 3rd Qu.:14.45 -1572 : 1
## Max. :18.40 -1616 : 1
## (Other):32
## Net_international_migration_.2015. Net_natural_change_.2015.
## . : 1 . : 1
## 10532 : 1 1047 : 1
## 10763 : 1 1095 : 1
## 1077 : 1 1207 : 1
## 11182 : 1 1269 : 1
## 1296 : 1 1391 : 1
## (Other):32 (Other):32
## X._of_resident_population_born_abroad_.2015.
## 36.6 : 2
## . : 1
## 10.9 : 1
## 13.3 : 1
## 14.6 : 1
## 16.1 : 1
## (Other):31
## Largest_migrant_population_by_country_of_birth_.2011.
## India :13
## Nigeria : 4
## United States: 4
## Ireland : 3
## Poland : 3
## Bangladesh : 2
## (Other) : 9
## X._of_largest_migrant_population_.2011.
## 2.8 : 3
## 3.6 : 3
## 1.1 : 2
## 1.8 : 2
## 2.2 : 2
## 3.2 : 2
## (Other):24
## Second_largest_migrant_population_by_country_of_birth_.2011.
## Poland : 8
## India : 7
## France : 3
## Bangladesh: 2
## Ireland : 2
## Jamaica : 2
## (Other) :14
## X._of_second_largest_migrant_population_.2011.
## 1.8 : 4
## 2.7 : 3
## 1.1 : 2
## 1.5 : 2
## 1.9 : 2
## 2 : 2
## (Other):23
## Third_largest_migrant_population_by_country_of_birth_.2011.
## Ireland :10
## Pakistan : 5
## Poland : 3
## Australia: 2
## Jamaica : 2
## Nigeria : 2
## (Other) :14
## X._of_third_largest_migrant_population_.2011.
## 1.6 : 4
## 1.7 : 4
## 0.9 : 3
## 1.4 : 3
## 1.9 : 3
## 2.3 : 3
## (Other):18
## X._of_population_from_BAME_groups_.2016.
## . : 2
## 15.7 : 2
## 45.7 : 2
## 49.9 : 2
## 18.9 : 1
## 21.4 : 1
## (Other):28
## X._people_aged_3._whose_main_language_is_not_English_.2011_Census.
## . : 1
## 10 : 1
## 10.4 : 1
## 14.5 : 1
## 16.4 : 1
## 16.5 : 1
## (Other):32
## Overseas_nationals_entering_the_UK_.NINo.._.2015.16.
## 10,384 : 1
## 10,427 : 1
## 10,534 : 1
## 11,259 : 1
## 11,336 : 1
## 12,157 : 1
## (Other):32
## New_migrant_.NINo._rates._.2015.16.
## Min. : 14.40
## 1st Qu.: 36.25
## Median : 53.30
## Mean : 53.46
## 3rd Qu.: 65.35
## Max. :152.20
##
## Largest_migrant_population_arrived_during_2015.16
## Bulgaria: 1
## India : 1
## Italy :10
## Poland : 2
## Romania :22
## Spain : 2
##
## Second_largest_migrant_population_arrived_during_2015.16
## France :8
## Poland :8
## Italy :6
## Bulgaria:5
## India :4
## Romania :4
## (Other) :3
## Third_largest_migrant_population_arrived_during_2015.16
## Spain :10
## Italy : 8
## Poland : 8
## Bulgaria : 4
## Australia: 1
## France : 1
## (Other) : 6
## Employment_rate_..._.2015. Male_employment_rate_.2015.
## Min. :64.60 79.1 : 2
## 1st Qu.:69.72 80.3 : 2
## Median :73.15 80.4 : 2
## Mean :72.78 80.9 : 2
## 3rd Qu.:75.25 82.1 : 2
## Max. :79.60 . : 1
## (Other):27
## Female_employment_rate_.2015. Unemployment_rate_.2015.
## 68.5 : 2 5.3 : 3
## 68.6 : 2 5.7 : 3
## . : 1 5.9 : 3
## 56.1 : 1 3.8 : 2
## 56.5 : 1 4.5 : 2
## 57.6 : 1 4.6 : 2
## (Other):30 (Other):23
## Youth_Unemployment_.claimant._rate_18.24_.Dec.15.
## 4.1 : 4
## 2.4 : 2
## 2.5 : 2
## 2.9 : 2
## 3.1 : 2
## 3.2 : 2
## (Other):24
## Proportion_of_16.18_year_olds_who_are_NEET_..._.2014.
## 3.4 : 4
## 4.3 : 4
## 3 : 3
## 3.3 : 3
## . : 2
## 2.2 : 2
## (Other):20
## Proportion_of_the_working.age_population_who_claim_out.of.work_benefits_..._.May.2016.
## 10.5 : 2
## 6 : 2
## 7 : 2
## 8.5 : 2
## 8.8 : 2
## . : 1
## (Other):27
## X._working.age_with_a_disability_.2015.
## 15.9 : 2
## 16.1 : 2
## 17.5 : 2
## 17.9 : 2
## . : 1
## 10.8 : 1
## (Other):28
## Proportion_of_working_age_people_with_no_qualifications_..._2015
## 4.3 : 3
## 6.2 : 3
## 10.8 : 2
## 4.5 : 2
## 5.2 : 2
## 7.3 : 2
## (Other):24
## Proportion_of_working_age_with_degree_or_equivalent_and_above_..._2015
## 43.4 : 2
## 44.7 : 2
## 49.2 : 2
## . : 1
## 26 : 1
## 32.2 : 1
## (Other):29
## Gross_Annual_Pay._.2016. Gross_Annual_Pay_._Male_.2016.
## . : 4 . :12
## 27886 : 1 30104 : 1
## 27942 : 1 30129 : 1
## 28213 : 1 30141 : 1
## 28503 : 1 30567 : 1
## 29812 : 1 30943 : 1
## (Other):29 (Other):21
## Gross_Annual_Pay_._Female_.2016.
## . : 6
## 24006 : 1
## 24602 : 1
## 24833 : 1
## 24965 : 1
## 27226 : 1
## (Other):27
## Modelled_Household_median_income_estimates_2012.13
## . : 1
## £28,780: 1
## £29,420: 1
## £30,600: 1
## £32,140: 1
## £33,080: 1
## (Other):32
## X._adults_that_volunteered_in_past_12_months_.2010.11_to_2012.13.
## . : 4
## 31.1 : 2
## 16.9 : 1
## 17.3 : 1
## 17.4 : 1
## 19.2 : 1
## (Other):28
## Number_of_jobs_by_workplace_.2014.
## . : 1
## 111100 : 1
## 127800 : 1
## 128800 : 1
## 132800 : 1
## 133600 : 1
## (Other):32
## X._of_employment_that_is_in_public_sector_.2014. Jobs_Density._2015
## Min. : 3.40 Min. : 0.400
## 1st Qu.:14.43 1st Qu.: 0.600
## Median :16.95 Median : 0.700
## Mean :17.17 Mean : 3.113
## 3rd Qu.:20.55 3rd Qu.: 1.000
## Max. :27.30 Max. :84.300
##
## Number_of_active_businesses._2015
## Min. : 6560
## 1st Qu.: 12221
## Median : 15348
## Mean : 174843
## 3rd Qu.: 21258
## Max. :2672025
##
## Two.year_business_survival_rates_.started_in_2013.
## Min. :63.80
## 1st Qu.:73.00
## Median :74.40
## Mean :73.78
## 3rd Qu.:75.67
## Max. :78.80
##
## Crime_rates_per_thousand_population_2014.15
## . : 2
## 69.4 : 2
## 77 : 2
## 100.6 : 1
## 104.6 : 1
## 106.4 : 1
## (Other):29
## Fires_per_thousand_population_.2014.
## 1.8 : 4
## 2.2 : 4
## 2.5 : 4
## 2 : 3
## 2.1 : 3
## 2.3 : 3
## (Other):17
## Ambulance_incidents_per_hundred_population_.2014. Median_House_Price._2015
## . : 3 320000 : 2
## 11.3 : 3 350000 : 2
## 11.8 : 3 415000 : 2
## 12.2 : 3 . : 1
## 11.1 : 2 1200000: 1
## 12.1 : 2 209995 : 1
## (Other):22 (Other):29
## Average_Band_D_Council_Tax_charge_...._2015.16
## . : 5
## 1003.81: 1
## 1058.58: 1
## 1196.85: 1
## 1206.38: 1
## 1240.54: 1
## (Other):28
## New_Homes_.net._2015.16_.provisional. Homes_Owned_outright._.2014._.
## . : 5 22.2 : 2
## 240 : 2 . : 1
## 510 : 2 10.1 : 1
## 910 : 2 10.9 : 1
## 970 : 2 11.1 : 1
## -130 : 1 14.6 : 1
## (Other):24 (Other):31
## Being_bought_with_mortgage_or_loan._.2014._.
## 15.1 : 2
## 19.8 : 2
## 31.8 : 2
## 34.9 : 2
## . : 1
## 11.6 : 1
## (Other):28
## Rented_from_Local_Authority_or_Housing_Association._.2014._.
## 16.7 : 2
## 17.2 : 2
## . : 1
## 10.7 : 1
## 11.1 : 1
## 11.3 : 1
## (Other):30
## Rented_from_Private_landlord._.2014._. X._of_area_that_is_Greenspace._2005
## 23.9 : 2 34.6 : 2
## 33.1 : 2 . : 1
## . : 1 12.4 : 1
## 11.4 : 1 15.1 : 1
## 13.8 : 1 15.2 : 1
## 14.1 : 1 17.3 : 1
## (Other):30 (Other):31
## Total_carbon_emissions_.2014. Household_Waste_Recycling_Rate._2014.15
## . : 2 . : 3
## 1014 : 1 20.7 : 2
## 1032 : 1 25.3 : 2
## 1036 : 1 17.1 : 1
## 1038 : 1 17.2 : 1
## 1091 : 1 19.1 : 1
## (Other):31 (Other):28
## Number_of_cars._.2011_Census. Number_of_cars_per_household._.2011_Census.
## Min. : 1692 Min. :0.4000
## 1st Qu.: 60602 1st Qu.:0.5250
## Median : 86360 Median :0.8000
## Mean : 1684820 Mean :0.8263
## 3rd Qu.: 119148 3rd Qu.:1.1000
## Max. :30333100 Max. :1.2000
##
## X._of_adults_who_cycle_at_least_once_per_month._2014.15
## . : 3
## 14.7 : 2
## 16 : 2
## 16.9 : 2
## 20.1 : 2
## 7.9 : 2
## (Other):25
## Average_Public_Transport_Accessibility_score._2014
## 3 : 6
## 2.9 : 3
## 4.9 : 3
## . : 2
## 3.4 : 2
## 4.3 : 2
## (Other):20
## Achievement_of_5_or_more_A.._C_grades_at_GCSE_or_equivalent_including_English_and_Maths._2013.14
## . : 3
## 59.9 : 2
## 68.7 : 2
## 55.7 : 1
## 56.3 : 1
## 56.8 : 1
## (Other):28
## Rates_of_Children_Looked_After_.2016.
## 35 : 2
## 41 : 2
## 42 : 2
## 43 : 2
## 45 : 2
## 46 : 2
## (Other):26
## X._of_pupils_whose_first_language_is_not_English_.2015.
## . : 2
## 38.9 : 2
## 57.6 : 2
## 15.7 : 1
## 25.2 : 1
## 29.3 : 1
## (Other):29
## X._children_living_in_out.of.work_households_.2015.
## Min. : 0.80
## 1st Qu.:10.55
## Median :13.85
## Mean :13.80
## 3rd Qu.:17.05
## Max. :23.40
##
## Male_life_expectancy._.2012.14. Female_life_expectancy._.2012.14.
## . : 4 . : 4
## 79 : 3 83.9 : 4
## 80.4 : 3 84.2 : 3
## 78.5 : 2 82.5 : 2
## 78.9 : 2 83.3 : 2
## 80.1 : 2 83.4 : 2
## (Other):22 (Other):21
## Teenage_conception_rate_.2014. Life_satisfaction_score_2011.14_.out_of_10.
## . : 2 Min. :6.600
## 18.5 : 2 1st Qu.:7.200
## 22.8 : 2 Median :7.300
## 11 : 1 Mean :7.289
## 12.6 : 1 3rd Qu.:7.400
## 12.8 : 1 Max. :7.600
## (Other):29
## Worthwhileness_score_2011.14_.out_of_10. Happiness_score_2011.14_.out_of_10.
## Min. :7.100 Min. :6.000
## 1st Qu.:7.500 1st Qu.:7.200
## Median :7.600 Median :7.200
## Mean :7.574 Mean :7.216
## 3rd Qu.:7.700 3rd Qu.:7.300
## Max. :7.900 Max. :7.600
##
## Anxiety_score_2011.14_.out_of_10. Childhood_Obesity_Prevalance_..._2015.16
## Min. :2.600 - : 3
## 1st Qu.:3.125 21.3 : 2
## Median :3.300 23.8 : 2
## Mean :3.337 27.6 : 2
## 3rd Qu.:3.400 12.6 : 1
## Max. :5.600 16 : 1
## (Other):27
## People_aged_17._with_diabetes_...
## 5.9 : 3
## 6.5 : 3
## 4.2 : 2
## 4.4 : 2
## 5 : 2
## 6 : 2
## (Other):24
## Mortality_rate_from_causes_considered_preventable_2012.14
## . : 3
## 164 : 3
## 134 : 2
## 162 : 2
## 169 : 2
## 183 : 2
## (Other):24
## Political_control_in_council
## . : 6
## Cons : 9
## Lab :20
## Lib Dem : 1
## No Overall Control : 1
## Tower Hamlets First: 1
##
## Proportion_of_seats_won_by_Conservatives_in_2014_election
## 0 : 5
## . : 3
## 11.1 : 1
## 15.7 : 1
## 16.7 : 1
## 17.4 : 1
## (Other):26
## Proportion_of_seats_won_by_Labour_in_2014_election
## . : 4
## 0 : 2
## 100 : 2
## 1.9 : 1
## 11.7 : 1
## 23.8 : 1
## (Other):27
## Proportion_of_seats_won_by_Lib_Dems_in_2014_election
## 0 :18
## . : 3
## 1.6 : 3
## 1.7 : 1
## 1.9 : 1
## 15.8 : 1
## (Other):11
## Turnout_at_2014_local_elections
## . : 3
## 37.6 : 2
## 39.6 : 2
## 40.5 : 2
## 43.1 : 2
## 29.8 : 1
## (Other):26necesitamos hacer algunas modificaciones al data set London_prof para poder combinarlo con london_area
por un lado en London_prof hay 5 registros (la diferencia de filas entre ambos datasets) que, por lo que observamos al ver el contenido del archivo, son totalizadores interno y dos datos externos (los correspondientes a Inglaterra y al Reino Unido en general)
tampoco vamos a centrar nuestro análisis en todas las columnas (84) de london_prof, por lo cual seleccionaremos solo algunas para reducir el tamaño del set
por último necesitamos que las columnas que contienen los nombres de los distritos (bouroghs) tengan el mismo nombre para poder hacer el joint_left
london_prof_sel <- select(london_prof, Area_name:X._of_third_largest_migrant_population_.2011.)london_prof_sel <- filter(london_prof_sel, !(Area_name %in% c("Inner London", "Outer London", "London", "England", "United Kingdom")))london_prof_sel <- rename(london_prof_sel, name=Area_name)head(london_prof_sel)## name Inner._Outer_London GLA_Population_Estimate_2017
## 1 City of London Inner London 8800
## 2 Barking and Dagenham Outer London 209000
## 3 Barnet Outer London 389600
## 4 Bexley Outer London 244300
## 5 Brent Outer London 332100
## 6 Bromley Outer London 327900
## GLA_Household_Estimate_2017 Inland_Area_.Hectares.
## 1 5326 290
## 2 78188 3,611
## 3 151423 8,675
## 4 97736 6,058
## 5 121048 4,323
## 6 140602 15,013
## Population_density_.per_hectare._2017 Average_Age._2017
## 1 30.3 43.2
## 2 57.9 32.9
## 3 44.9 37.3
## 4 40.3 39.0
## 5 76.8 35.6
## 6 21.8 40.2
## Proportion_of_population_aged_0.15._2015
## 1 11.4
## 2 27.2
## 3 21.1
## 4 20.6
## 5 20.9
## 6 19.9
## Proportion_of_population_of_working.age._2015
## 1 73.1
## 2 63.1
## 3 64.9
## 4 62.9
## 5 67.8
## 6 62.6
## Proportion_of_population_aged_65_and_over._2015 Net_internal_migration_.2015.
## 1 15.5 -7
## 2 9.7 -1176
## 3 14.0 -3379
## 4 16.6 413
## 5 11.3 -7739
## 6 17.5 1342
## Net_international_migration_.2015. Net_natural_change_.2015.
## 1 665 30
## 2 2509 2356
## 3 5407 2757
## 4 760 1095
## 5 7640 3372
## 6 796 1445
## X._of_resident_population_born_abroad_.2015.
## 1 .
## 2 37.8
## 3 35.2
## 4 16.1
## 5 53.9
## 6 18.3
## Largest_migrant_population_by_country_of_birth_.2011.
## 1 United States
## 2 Nigeria
## 3 India
## 4 Nigeria
## 5 India
## 6 India
## X._of_largest_migrant_population_.2011.
## 1 2.8
## 2 4.7
## 3 3.1
## 4 2.6
## 5 9.2
## 6 1.1
## Second_largest_migrant_population_by_country_of_birth_.2011.
## 1 France
## 2 India
## 3 Poland
## 4 India
## 5 Poland
## 6 Ireland
## X._of_second_largest_migrant_population_.2011.
## 1 2
## 2 2.3
## 3 2.4
## 4 1.5
## 5 3.4
## 6 1.1
## Third_largest_migrant_population_by_country_of_birth_.2011.
## 1 Australia
## 2 Pakistan
## 3 Iran
## 4 Ireland
## 5 Ireland
## 6 Nigeria
## X._of_third_largest_migrant_population_.2011.
## 1 1.9
## 2 2.3
## 3 2
## 4 0.9
## 5 2.9
## 6 0.7Estamos ahora en condición de combinarlos
london_area_full <- left_join(london_area, london_prof_sel, by="name")head(london_area_full)## Simple feature collection with 6 features and 23 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -0.333999 ymin: 51.2895 xmax: 0.225322 ymax: 51.67036
## Geodetic CRS: WGS 84
## name cartodb_id created_at updated_at
## 1 Barking and Dagenham 1 2015-07-01 06:57:45 2015-07-01 06:57:45
## 2 Barnet 2 2015-07-01 06:57:45 2015-07-01 06:57:45
## 3 Bexley 3 2015-07-01 06:57:45 2015-07-01 06:57:45
## 4 Brent 4 2015-07-01 06:57:45 2015-07-01 06:57:45
## 5 Bromley 5 2015-07-01 06:57:45 2015-07-01 06:57:45
## 6 Camden 6 2015-07-01 06:57:45 2015-07-01 06:57:45
## Inner._Outer_London GLA_Population_Estimate_2017 GLA_Household_Estimate_2017
## 1 Outer London 209000 78188
## 2 Outer London 389600 151423
## 3 Outer London 244300 97736
## 4 Outer London 332100 121048
## 5 Outer London 327900 140602
## 6 Inner London 242500 107654
## Inland_Area_.Hectares. Population_density_.per_hectare._2017
## 1 3,611 57.9
## 2 8,675 44.9
## 3 6,058 40.3
## 4 4,323 76.8
## 5 15,013 21.8
## 6 2,179 111.3
## Average_Age._2017 Proportion_of_population_aged_0.15._2015
## 1 32.9 27.2
## 2 37.3 21.1
## 3 39.0 20.6
## 4 35.6 20.9
## 5 40.2 19.9
## 6 36.4 17.3
## Proportion_of_population_of_working.age._2015
## 1 63.1
## 2 64.9
## 3 62.9
## 4 67.8
## 5 62.6
## 6 71.0
## Proportion_of_population_aged_65_and_over._2015 Net_internal_migration_.2015.
## 1 9.7 -1176
## 2 14.0 -3379
## 3 16.6 413
## 4 11.3 -7739
## 5 17.5 1342
## 6 11.7 -2917
## Net_international_migration_.2015. Net_natural_change_.2015.
## 1 2509 2356
## 2 5407 2757
## 3 760 1095
## 4 7640 3372
## 5 796 1445
## 6 7504 1618
## X._of_resident_population_born_abroad_.2015.
## 1 37.8
## 2 35.2
## 3 16.1
## 4 53.9
## 5 18.3
## 6 41.4
## Largest_migrant_population_by_country_of_birth_.2011.
## 1 Nigeria
## 2 India
## 3 Nigeria
## 4 India
## 5 India
## 6 United States
## X._of_largest_migrant_population_.2011.
## 1 4.7
## 2 3.1
## 3 2.6
## 4 9.2
## 5 1.1
## 6 2.8
## Second_largest_migrant_population_by_country_of_birth_.2011.
## 1 India
## 2 Poland
## 3 India
## 4 Poland
## 5 Ireland
## 6 Bangladesh
## X._of_second_largest_migrant_population_.2011.
## 1 2.3
## 2 2.4
## 3 1.5
## 4 3.4
## 5 1.1
## 6 2.7
## Third_largest_migrant_population_by_country_of_birth_.2011.
## 1 Pakistan
## 2 Iran
## 3 Ireland
## 4 Ireland
## 5 Nigeria
## 6 Ireland
## X._of_third_largest_migrant_population_.2011. geometry
## 1 2.3 MULTIPOLYGON (((0.148209 51...
## 2 2 MULTIPOLYGON (((-0.183361 5...
## 3 0.9 MULTIPOLYGON (((0.158044 51...
## 4 2.9 MULTIPOLYGON (((-0.212138 5...
## 5 0.7 MULTIPOLYGON (((0.076463 51...
## 6 2.4 MULTIPOLYGON (((-0.140804 5...Distribución de población
Representaremos el mapa de lOndres según la población de cada distrito
ggplot(london_area_full)+
geom_sf(aes(fill=GLA_Population_Estimate_2017))+
labs(title="Mapa de Población Londres",
subtitle="por distrito, segun datos 2017",
x="longitud",
y="latitud")+
scale_fill_distiller(palette = "Spectral")
El dataset divide a la cudad en un sector interno y otro externo Podemos ver como resulta en el “Londres interno” En este caso agregando las etiquetas de los nombres de los distritos
ggplot(london_area_full %>% filter(Inner._Outer_London=="Inner London"))+
geom_sf(aes(fill=GLA_Population_Estimate_2017))+
labs(title="Mapa de Población Londres",
subtitle="Inner London",
x="longitud",
y="latitud")+
scale_fill_distiller(palette = "Spectral")+
geom_sf_label(aes(label=name), size=1.8)## Warning in st_point_on_surface.sfc(sf::st_zm(x)): st_point_on_surface may not
## give correct results for longitude/latitude data
Eliminando del análisis la City de Londres (el sector financiero) el distrito con menor población es Kesington and Chelsea, seguramente la zona más residencial de londres, predominantemente de casas bajas y donde residen la mayoría de las embajadas.
Distribución espacial de inmigrantes
Como parte de la información de población de los distritos, la columna “Largest_migrant_population_by_country_of_birth_.2011.” indica de que pais son originarios la primera mayoría de inmigrantes Podemos representarlo en el mapa de la siguiente manera
ggplot(london_area_full)+
geom_sf(aes(fill=Largest_migrant_population_by_country_of_birth_.2011.))+
labs(title="Mapa de Población Londres", subtitle="por distrito, segun datos 2017")
Como se puede observar aparecen claras agrupaciones por zonas, mientras en el noroeste y en el sur este hay mayoría de inmigrantes indúes, Candem y Westmister hay mayoría de inmigrantes de USA, al sur dos distritos tienen mayoría de inmigrantes de Sri Lanka y Enfield, al norte, inmigrantes procedentes de Turquia.