PCA SOLE
Variables
merged2 <- merged %>%
remove_rownames %>%
column_to_rownames(var="Nom_Barri") %>%
select("n.tot","pc.esp","pc.ext","pc.ue27-esp","pc.20.34","2019-2014","var20192014",
"hotel2019",
"alq.mq","alq.num","alq.pmq",
"tot_ann","pc.ent","pc.priv","pc.shared","pc.hotel","pm_ent","pm_priv","pm_sha","pm_hot",
"RFD.2017",
"tot.comp","perc.nou.comp","perc.prot.comp","perc.usat.comp",
"tot.m2","nou.m2","prot.m2","usat.m2",
"tot.eur","nou.eur","usat.eur",
"tot.eurm2","nou.eurm2","usat.eurm2",
"rest1614")Standardizar los datos
df <- scale(merged2)Calcular eigenvalues and eigenvectors
pca_result <- prcomp(merged2, scale = TRUE)
pca_result$center## n.tot pc.esp pc.ext pc.ue27-esp pc.20.34
## 22607.643836 80.781048 13.404986 7.114347 18.988279
## 2019-2014 var20192014 hotel2019 alq.mq alq.num
## 658.342466 5.214562 276.054795 69.992967 167.369863
## alq.pmq tot_ann pc.ent pc.priv pc.shared
## 12.531159 279.835616 33.437569 60.914692 1.734542
## pc.hotel pm_ent pm_priv pm_sha pm_hot
## 1.173470 160.829973 44.526768 46.970471 172.496888
## RFD.2017 tot.comp perc.nou.comp perc.prot.comp perc.usat.comp
## 93.671233 185.191781 7.687534 2.268758 91.924106
## tot.m2 nou.m2 prot.m2 usat.m2 tot.eur
## 77.679909 59.242808 15.476027 77.344635 309.594521
## nou.eur usat.eur tot.eurm2 nou.eurm2 usat.eurm2
## 260.815068 302.687671 3722.853425 2650.116438 3675.641096
## rest1614
## 1.191781pca_result$scale## n.tot pc.esp pc.ext pc.ue27-esp pc.20.34
## 14753.886904 9.009606 6.720753 7.320092 3.873115
## 2019-2014 var20192014 hotel2019 alq.mq alq.num
## 1490.085971 10.477120 490.230782 14.165945 159.168980
## alq.pmq tot_ann pc.ent pc.priv pc.shared
## 4.260785 443.819033 18.180666 20.110450 6.114537
## pc.hotel pm_ent pm_priv pm_sha pm_hot
## 1.943317 201.699239 16.003633 143.964167 403.002786
## RFD.2017 tot.comp perc.nou.comp perc.prot.comp perc.usat.comp
## 42.709775 148.403509 10.382977 17.543273 10.563166
## tot.m2 nou.m2 prot.m2 usat.m2 tot.eur
## 18.930482 47.275532 32.108977 18.206886 183.338837
## nou.eur usat.eur tot.eurm2 nou.eurm2 usat.eurm2
## 440.142831 171.131367 1266.180075 2861.379533 1234.737827
## rest1614
## 26.158522#pesos asignados a cada componente
pca_result$rotation[,1:5]## PC1 PC2 PC3 PC4 PC5
## n.tot -0.16516544 -0.165839329 -0.072038562 0.334558689 -0.167297172
## pc.esp 0.07599470 0.331308108 -0.054782766 0.251075796 -0.035081851
## pc.ext 0.03105891 -0.314671685 0.082044518 -0.196260332 -0.003665424
## pc.ue27-esp -0.16425197 -0.248949015 0.031787245 -0.282641635 0.084738880
## pc.20.34 -0.08583139 -0.340682082 0.037270593 -0.214251697 0.160317616
## 2019-2014 -0.03502102 0.153801556 -0.117377009 0.352255049 -0.043349468
## var20192014 0.03301277 0.185838980 -0.041502116 0.126939300 0.300534766
## hotel2019 -0.18887244 -0.208009575 -0.104796987 0.158670246 0.100060310
## alq.mq -0.22754241 0.166339818 0.008173313 -0.095235862 0.034205491
## alq.num -0.20779800 -0.185054733 -0.106556103 0.252617998 -0.022163929
## alq.pmq -0.20294583 -0.026599968 -0.034111306 -0.012805585 -0.302196639
## tot_ann -0.17952423 -0.293003501 -0.084978732 0.045021902 0.105984946
## pc.ent -0.19442100 -0.013809087 -0.183842820 -0.049777955 0.207942635
## pc.priv 0.11069835 -0.008341634 0.123138739 0.008440571 -0.398101238
## pc.shared 0.10549583 -0.035033834 -0.063445508 0.059203593 -0.057561324
## pc.hotel -0.15673663 -0.137583846 -0.175465940 0.245346091 0.073329289
## pm_ent -0.04660363 0.070758710 -0.091098809 0.070218576 0.367143934
## pm_priv -0.18754587 -0.055917581 -0.126860693 -0.032514504 -0.175377880
## pm_sha -0.10344544 -0.018258893 -0.184599738 0.013387924 0.010092399
## pm_hot -0.13989583 -0.105123766 -0.193294600 0.101725303 0.128768854
## RFD.2017 -0.25739984 0.175795005 -0.012654108 -0.061983099 -0.006888339
## tot.comp -0.11948666 -0.180544094 0.080464085 0.291724778 -0.151011643
## perc.nou.comp -0.03396862 0.016511560 0.426409194 0.100255740 0.230261474
## perc.prot.comp 0.05498072 0.022842961 -0.057228399 0.041368954 0.408157724
## perc.usat.comp 0.02623529 -0.017647494 -0.419297757 -0.115240015 -0.285310167
## tot.m2 -0.23057978 0.222871621 0.023736532 -0.094810579 -0.045982239
## nou.m2 -0.16952372 -0.023361870 0.344677073 0.161646487 -0.065015572
## prot.m2 -0.05729853 -0.097723317 0.136191229 0.296339001 0.035089560
## usat.m2 -0.21419723 0.246623663 -0.005422952 -0.090155826 0.009813247
## tot.eur -0.26271621 0.176743018 0.022473664 -0.110050900 -0.028557483
## nou.eur -0.17582945 0.041184026 0.319908645 0.017128329 -0.065263513
## usat.eur -0.26183963 0.185294292 -0.019531302 -0.109297374 -0.010190294
## tot.eurm2 -0.27722413 0.082152887 -0.027718557 -0.118810700 -0.010487385
## nou.eurm2 -0.18891270 -0.030710565 0.366458830 0.062040897 -0.039434919
## usat.eurm2 -0.27154347 0.081465550 -0.056930554 -0.117350018 0.001825782
## rest1614 0.02586620 0.170334210 -0.098818123 0.190711619 0.020547767#results
pca_result$x[,1:5]## PC1 PC2 PC3
## el Raval -2.21781988 -7.5853853 0.10748785
## el Barri Gòtic -4.55381738 -7.6699178 3.12867967
## la Barceloneta -0.65477622 -4.3035726 -0.03159807
## Sant Pere, Santa Caterina i la Ribera -3.41367711 -5.3290436 0.62605617
## el Fort Pienc -4.45136679 -0.6305147 3.74527767
## la Sagrada FamÃlia -1.50455362 -2.4112208 -2.95771166
## la Dreta de l'Eixample -8.15830760 -2.4781772 -1.84542961
## l'Antiga Esquerra de l'Eixample -5.32705473 -2.1867419 -0.99663130
## la Nova Esquerra de l'Eixample -2.47737844 -2.1388038 -0.48641626
## Sant Antoni -2.82627843 -2.4568364 -2.66986105
## el Poble Sec -1.80045866 -3.6358061 -0.74701136
## la Marina del Prat Vermell 4.93743101 1.1477810 -1.60290881
## la Marina de Port 2.20098729 0.1910154 -0.79039412
## la Font de la Guatlla 0.52658321 -0.3374349 -1.03073285
## Hostafrancs -0.68054547 -0.3450139 0.66479782
## la Bordeta 2.29056537 0.1711813 -1.22334883
## Sants - Badal 1.31515128 -0.2573923 -1.01509308
## Sants -0.89417574 -0.8953334 -1.39329415
## les Corts -3.25740109 -0.2500281 0.10058182
## la Maternitat i Sant Ramon -0.25181834 1.1051357 -1.88915801
## Pedralbes -8.23713976 5.8705809 4.30956346
## Vallvidrera, el Tibidabo i les Planes -1.87505308 3.6968273 -1.82921464
## Sarrià -4.48321127 3.8873905 0.58646224
## les Tres Torres -5.16578899 5.3410948 -3.04261386
## Sant Gervasi - la Bonanova -4.58560748 4.0339119 1.00615965
## Sant Gervasi - Galvany -6.37111841 1.9026177 0.90184451
## el Putxet i el Farró -3.20490351 1.6771321 0.56011173
## Vallcarca i els Penitents -0.45271288 1.3738700 1.24541291
## el Coll 1.91430375 0.4209502 1.81286386
## la Salut -0.53179698 1.1201427 0.71728609
## la Vila de Grà cia -5.51133746 -3.3123719 -2.54174924
## el Camp d'en Grassot i Grà cia Nova -1.94699724 -0.4117966 -1.73331629
## el Baix Guinardó 0.56396120 -0.1151044 -1.85176487
## Can Baró 1.90690534 0.3917359 -1.41935262
## el Guinardó 0.40039022 -0.2493064 0.03512734
## la Font d'en Fargues 1.40497089 2.5560642 -0.48211289
## el Carmel 1.26617170 -1.0593382 2.25580290
## la Teixonera 2.31699472 0.4054950 2.72518547
## Sant GenÃs dels Agudells 1.92069393 0.8411061 1.60580764
## Montbau 2.70928019 0.5045632 2.91183187
## la Vall d'Hebron 1.88671727 1.4065643 2.34013339
## la Clota 2.79819589 2.3395017 4.07553145
## Horta 1.31387691 0.3821931 1.93627822
## Vilapicina i la Torre Llobeta 2.65372409 0.3594988 -0.88298030
## Porta 2.59825653 0.1010059 -0.45865650
## el Turó de la Peira 2.75895722 -1.1815280 -0.46561571
## Can Peguera 8.28817088 -1.0813320 -1.06025360
## la Guineueta 2.10737069 1.1485762 0.59509497
## Canyelles 3.53105131 1.5292577 -0.82216751
## les Roquetes 3.30341126 -1.1026646 -0.81268583
## Verdun 3.06996929 -0.9245743 0.88417519
## la Prosperitat 3.80210913 -0.4350234 -0.94386465
## la Trinitat Nova 4.62607326 -1.1847987 -0.24069889
## Torre Baró 4.23582770 0.8564354 -0.83539834
## Ciutat Meridiana 4.83366773 -2.0286426 0.09674048
## Vallbona 4.60278256 1.3454405 -0.57980929
## la Trinitat Vella 3.00950384 -1.1855088 -0.41899855
## Baró de Viver 0.16627403 2.5317964 -1.88245301
## el Bon Pastor 2.86327754 0.1737218 0.54864977
## Sant Andreu 0.20443536 0.2035818 0.65864860
## la Sagrera 1.53706386 0.2957190 -1.29498841
## el Congrés i els Indians 1.43344182 0.4245311 -0.81915009
## Navas 0.01044098 1.0797189 0.42179284
## el Camp de l'Arpa del Clot -1.47389422 -1.1900235 1.03075362
## el Clot -0.70841712 -0.1030109 0.70781531
## el Parc i la Llacuna del Poblenou 0.62773793 0.1120644 -1.31043391
## la Vila OlÃmpica del Poblenou -2.43384160 3.0837628 -2.61369960
## el Poblenou -2.21190306 0.4220057 0.28570587
## Diagonal Mar i el Front MarÃtim del Poblenou -3.11967329 3.4004125 -3.68459889
## el Besòs i el Maresme 0.05908273 -1.8071444 3.53800604
## Provençals del Poblenou -0.64730176 1.7707613 1.69360904
## Sant Martà de Provençals 0.98818999 0.7686598 1.96920355
## la Verneda i la Pau 2.44612769 -0.0904135 0.87768768
## PC4 PC5
## el Raval -0.91683045 0.003098849
## el Barri Gòtic -6.91432145 1.194943029
## la Barceloneta -3.22337930 0.651548911
## Sant Pere, Santa Caterina i la Ribera -1.58602386 0.766795838
## el Fort Pienc 1.24680975 -0.558077084
## la Sagrada FamÃlia 0.33210317 0.335828278
## la Dreta de l'Eixample 3.84440945 1.673358045
## l'Antiga Esquerra de l'Eixample 1.15845848 0.925894752
## la Nova Esquerra de l'Eixample 1.93885361 -0.474265343
## Sant Antoni 1.92459402 1.127065038
## el Poble Sec -0.44040460 -0.047860804
## la Marina del Prat Vermell 0.71509993 7.983034462
## la Marina de Port 0.38892031 -1.729473267
## la Font de la Guatlla -0.84866366 -0.133449992
## Hostafrancs -0.37700371 0.829156316
## la Bordeta -0.24981546 -0.826014431
## Sants - Badal -0.03353059 -0.579062583
## Sants 1.79858286 -0.458490621
## les Corts 3.04382268 -0.755684860
## la Maternitat i Sant Ramon -0.68361462 -1.021201428
## Pedralbes -2.61870709 -1.631413731
## Vallvidrera, el Tibidabo i les Planes -2.48293332 -0.574746665
## Sarrià -0.86467290 -1.605311260
## les Tres Torres -2.34291146 -0.274360019
## Sant Gervasi - la Bonanova -0.14921898 0.761487986
## Sant Gervasi - Galvany 0.94145069 0.102599552
## el Putxet i el Farró 0.22305315 0.635918066
## Vallcarca i els Penitents -0.43784807 -0.015112481
## el Coll 0.04388191 0.566130145
## la Salut -0.63205442 -0.978741993
## la Vila de Grà cia 1.39182375 0.815252458
## el Camp d'en Grassot i Grà cia Nova 0.64299864 -0.776919234
## el Baix Guinardó -0.40821607 -0.933183940
## Can Baró -1.25574447 0.201771023
## el Guinardó 1.00121970 -1.257915273
## la Font d'en Fargues -0.34730885 0.405111585
## el Carmel 1.71359311 0.500075141
## la Teixonera 0.26710688 0.520843522
## Sant GenÃs dels Agudells -0.37397620 0.138259074
## Montbau 0.78960835 0.407619081
## la Vall d'Hebron 0.29223681 1.096853985
## la Clota 0.50742802 5.582202880
## Horta 1.45191585 -0.863207082
## Vilapicina i la Torre Llobeta -0.26918382 -1.451014640
## Porta 0.76137100 -0.954521414
## el Turó de la Peira 0.50006370 -1.138094600
## Can Peguera 1.03685588 -0.114391257
## la Guineueta -0.04227403 -1.287608479
## Canyelles -0.64955288 -0.913733061
## les Roquetes -0.83437983 -0.743572856
## Verdun -0.37521142 -1.064907215
## la Prosperitat 0.21212401 -1.325718908
## la Trinitat Nova -1.14659149 -1.240003226
## Torre Baró -0.69587892 1.195711886
## Ciutat Meridiana -1.36448472 -1.367130804
## Vallbona -0.69139983 1.865415851
## la Trinitat Vella -1.50922441 -0.595754430
## Baró de Viver -2.45045224 2.969396514
## el Bon Pastor 1.38583189 -0.621346783
## Sant Andreu 3.39963841 -1.293323760
## la Sagrera 0.10117023 -1.185715660
## el Congrés i els Indians -0.43950063 -1.222697851
## Navas -0.29426049 -1.366141714
## el Camp de l'Arpa del Clot 1.77622961 -0.072459812
## el Clot 1.06450468 -1.479004971
## el Parc i la Llacuna del Poblenou -0.32051611 0.358175045
## la Vila OlÃmpica del Poblenou -1.98062502 0.462997573
## el Poblenou 1.58792560 0.909620697
## Diagonal Mar i el Front MarÃtim del Poblenou 0.03531732 1.499472791
## el Besòs i el Maresme 1.75523340 0.845119073
## Provençals del Poblenou 0.04891843 -0.104573852
## Sant Martà de Provençals 0.28354260 -0.678359074
## la Verneda i la Pau 0.64401749 -1.616190985Var Exp
VE <- pca_result$sdev^2
PVE <- VE / sum(VE)
round(PVE, 2)## [1] 0.29 0.16 0.08 0.07 0.06 0.05 0.04 0.04 0.03 0.03 0.02 0.02 0.02 0.01 0.01
## [16] 0.01 0.01 0.01 0.01 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## [31] 0.00 0.00 0.00 0.00 0.00 0.00vis eigen
fviz_eig(pca_result)
Plot
biplot(pca_result, scale = 0)
graph pca
fviz_pca_ind(pca_result,
col.ind = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE
)
graph var
fviz_pca_var(pca_result,
col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE
)
graph biplot
fviz_pca_biplot(pca_result, repel = TRUE,
col.var = "#2E9FDF", # Variables color
col.ind = "#696969" # Individuals color
)