taller_econometria
rosa caraballo, daniela perez, carol martinez
2025-09-26
Uilisamos nuestra base de datos tipo excel
library(dplyr)##
## Adjuntando el paquete: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(ggplot2) # <- agrega esta
library(GGally)
library(Hmisc)##
## Adjuntando el paquete: 'Hmisc'## The following objects are masked from 'package:dplyr':
##
## src, summarize## The following objects are masked from 'package:base':
##
## format.pval, unitslibrary(corrplot)## corrplot 0.95 loadedlibrary(readxl)
# Cargar archivo Excel
base_taller <- read_excel("C:/Users/carab/Downloads/Rosi_files/dp2015-13_Dataset.xls")
# Ver tabla en pestaña nueva
View(base_taller)head(base_taller)## # A tibble: 6 × 184
## City City_Eng City_Short NAds Price_Median Price_Mean Area_Median Area_Mean
## <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Amste… Amsterd… AMS 9520 3420. 3426. 71 75.3
## 2 Athina Athens ATH 10782 2064. 2109. 76 77.2
## 3 Barce… Barcelo… BCN 5479 3140 3268. 77 80.8
## 4 Beogr… Belgrade BEG 12797 1417. 1466. 58 60.2
## 5 Berlin Berlin BER 16772 2150. 2314. 75 82.3
## 6 Bruxe… Brussels BRU 7879 2357. 2428. 95 98.4
## # ℹ 176 more variables: Room_Median <dbl>, Room_Mean <dbl>, Euro_area <dbl>,
## # EU <dbl>, Population <dbl>, City_Area <dbl>, Density <dbl>, GDP_PC <dbl>,
## # GDP_PC_PPS <dbl>, GDP_PC2008 <dbl>, GDP_PC2009 <dbl>, GDP_PC2010 <dbl>,
## # Gini <dbl>, HOR <dbl>, Kearny_GCI2010 <dbl>, LRIR <dbl>,
## # Inflation2010 <dbl>, Inflation2011 <dbl>, URate <dbl>, MIR2009 <dbl>,
## # MIR2010 <dbl>, Mortgage_PC2010 <dbl>, Tppl1989_1993 <dbl>,
## # Tppl1994_1998 <dbl>, Tppl1999_2002 <dbl>, Tppl2003_2006 <dbl>, …tail(base_taller)## # A tibble: 6 × 184
## City City_Eng City_Short NAds Price_Median Price_Mean Area_Median Area_Mean
## <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Tall… Tallinn TAL 8876 1062. 1059. 52.6 54.1
## 2 Tori… Turin TUR 8525 2225 2321. 75 80.5
## 3 Vale… Valencia VAL 14537 1741. 1849. 93 96.5
## 4 Viln… Vilnius VIL 2794 1251. 1289. 58 59.1
## 5 Wars… Warsaw WAW 155154 1934. 1976. 54 56.7
## 6 Wien Vienna VIE 10370 3571. 3657. 87 93.0
## # ℹ 176 more variables: Room_Median <dbl>, Room_Mean <dbl>, Euro_area <dbl>,
## # EU <dbl>, Population <dbl>, City_Area <dbl>, Density <dbl>, GDP_PC <dbl>,
## # GDP_PC_PPS <dbl>, GDP_PC2008 <dbl>, GDP_PC2009 <dbl>, GDP_PC2010 <dbl>,
## # Gini <dbl>, HOR <dbl>, Kearny_GCI2010 <dbl>, LRIR <dbl>,
## # Inflation2010 <dbl>, Inflation2011 <dbl>, URate <dbl>, MIR2009 <dbl>,
## # MIR2010 <dbl>, Mortgage_PC2010 <dbl>, Tppl1989_1993 <dbl>,
## # Tppl1994_1998 <dbl>, Tppl1999_2002 <dbl>, Tppl2003_2006 <dbl>, …summary(base_taller)## City City_Eng City_Short NAds
## Length:50 Length:50 Length:50 Min. : 576
## Class :character Class :character Class :character 1st Qu.: 4932
## Mode :character Mode :character Mode :character Median : 9694
## Mean : 17924
## 3rd Qu.: 15981
## Max. :155154
##
## Price_Median Price_Mean Area_Median Area_Mean
## Min. : 503.1 Min. : 534.7 Min. : 47.00 Min. : 51.12
## 1st Qu.:1305.3 1st Qu.:1322.1 1st Qu.: 55.03 1st Qu.: 59.10
## Median :2107.2 Median :2200.7 Median : 65.50 Median : 68.07
## Mean :2436.7 Mean :2535.0 Mean : 68.56 Mean : 72.14
## 3rd Qu.:3092.2 3rd Qu.:3176.5 3rd Qu.: 78.50 3rd Qu.: 82.63
## Max. :8590.9 Max. :8865.7 Max. :100.00 Max. :109.49
##
## Room_Median Room_Mean Euro_area EU Population
## Min. :2.00 Min. :1.805 Min. :0.0 Min. :0.0 Min. : 401389
## 1st Qu.:2.00 1st Qu.:2.172 1st Qu.:0.0 1st Qu.:0.0 1st Qu.: 799132
## Median :2.00 Median :2.476 Median :0.5 Median :1.0 Median : 1148799
## Mean :2.47 Mean :2.515 Mean :0.5 Mean :0.7 Mean : 1872288
## 3rd Qu.:3.00 3rd Qu.:2.832 3rd Qu.:1.0 3rd Qu.:1.0 3rd Qu.: 1707910
## Max. :3.00 Max. :3.394 Max. :1.0 Max. :1.0 Max. :12915158
##
## City_Area Density GDP_PC GDP_PC_PPS
## Min. : 84.8 Min. : 1315 Min. : 2535 Min. : 4696
## 1st Qu.: 169.9 1st Qu.: 2571 1st Qu.:11862 1st Qu.:15047
## Median : 375.2 Median : 3297 Median :29550 Median :30400
## Mean : 523.4 Mean : 4552 Mean :31026 Mean :31335
## 3rd Qu.: 500.0 3rd Qu.: 5551 3rd Qu.:42750 3rd Qu.:42750
## Max. :5512.0 Max. :20618 Max. :86464 Max. :76200
##
## GDP_PC2008 GDP_PC2009 GDP_PC2010 Gini
## Min. : 2535 Min. : 1872 Min. : 2301 Min. :23.60
## 1st Qu.:10537 1st Qu.: 9384 1st Qu.:10685 1st Qu.:28.35
## Median :25848 Median :24680 Median :25899 Median :31.85
## Mean :31226 Mean :28888 Mean :30422 Mean :32.89
## 3rd Qu.:47699 3rd Qu.:43128 3rd Qu.:48444 3rd Qu.:36.40
## Max. :88300 Max. :84421 Max. :85861 Max. :52.10
##
## HOR Kearny_GCI2010 LRIR Inflation2010
## Min. :12.80 Min. :0.0000 Min. : 0.690 Min. :-1.600
## 1st Qu.:30.02 1st Qu.:0.0000 1st Qu.: 3.770 1st Qu.: 1.450
## Median :66.15 Median :0.0000 Median : 4.515 Median : 2.000
## Mean :58.74 Mean :0.9976 Mean : 6.525 Mean : 3.885
## 3rd Qu.:83.25 3rd Qu.:2.3050 3rd Qu.:10.706 3rd Qu.: 8.400
## Max. :97.42 Max. :5.8600 Max. :15.970 Max. :10.500
##
## Inflation2011 URate MIR2009 MIR2010
## Min. : 1.200 Min. : 0.300 Min. : 1.260 Min. : 0.920
## 1st Qu.: 2.500 1st Qu.: 5.802 1st Qu.: 3.277 1st Qu.: 2.993
## Median : 3.100 Median : 7.990 Median : 4.360 Median : 3.815
## Mean : 4.816 Mean : 9.446 Mean : 7.457 Mean : 7.026
## 3rd Qu.: 5.275 3rd Qu.:11.908 3rd Qu.: 9.352 3rd Qu.: 8.615
## Max. :53.200 Max. :23.124 Max. :26.000 Max. :26.200
## NA's :6 NA's :2 NA's :2
## Mortgage_PC2010 Tppl1989_1993 Tppl1994_1998 Tppl1999_2002
## Min. : 0.190 Min. : 464773 Min. : 421249 Min. : 399685
## 1st Qu.: 0.395 1st Qu.: 702444 1st Qu.: 704303 1st Qu.: 722104
## Median : 6.475 Median :1067365 Median : 964346 Median : 993134
## Mean :10.195 Mean :1450095 Mean :1393183 Mean :1570878
## 3rd Qu.:14.090 3rd Qu.:1655272 3rd Qu.:1611954 3rd Qu.:1698320
## Max. :45.160 Max. :6829300 Max. :6901300 Max. :8803468
## NA's :2 NA's :17 NA's :19 NA's :14
## Tppl2003_2006 Tppl2007_2009 GDP_PC_PPS1989_1993 GDP_PC_PPS1994_1998
## Min. : 392306 Min. : 401389 Mode:logical Min. : 6900
## 1st Qu.: 689874 1st Qu.: 704162 NA's:50 1st Qu.:13675
## Median :1000174 Median :1021956 Median :20700
## Mean :1363199 Mean :1467902 Mean :23215
## 3rd Qu.:1622183 3rd Qu.:1695450 3rd Qu.:29500
## Max. :7413100 Max. :7668300 Max. :54300
## NA's :14 NA's :20 NA's :16
## GDP_PC_PPS1999_2002 GDP_PC_PPS2003_2006 GDP_PC_PPS2007_2009 CITIES
## Min. :10600 Min. :13900 Min. :16000 Length:50
## 1st Qu.:21175 1st Qu.:22700 1st Qu.:26550 Class :character
## Median :27800 Median :31100 Median :34300 Mode :character
## Mean :30556 Mean :33851 Mean :39020
## 3rd Qu.:37575 3rd Qu.:43300 3rd Qu.:48450
## Max. :65800 Max. :70100 Max. :76200
## NA's :16 NA's :15 NA's :15
## DemoDepend1989_1993 DemoDepend1994_1998 DemoDepend1999_2002
## Min. :48.10 Min. :49.40 Min. :48.40
## 1st Qu.:53.83 1st Qu.:53.40 1st Qu.:54.40
## Median :61.30 Median :61.00 Median :57.00
## Mean :60.58 Mean :59.36 Mean :57.36
## 3rd Qu.:66.72 3rd Qu.:63.80 3rd Qu.:59.30
## Max. :72.40 Max. :68.10 Max. :71.50
## NA's :22 NA's :25 NA's :19
## DemoDepend2003_2006 DemoDepend2007_2009 DemoODepend1989_1993
## Min. :48.20 Min. :45.10 Min. :11.60
## 1st Qu.:52.30 1st Qu.:51.85 1st Qu.:21.00
## Median :55.50 Median :55.40 Median :24.30
## Mean :57.08 Mean :56.45 Mean :24.02
## 3rd Qu.:59.90 3rd Qu.:59.80 3rd Qu.:26.30
## Max. :73.10 Max. :73.90 Max. :35.20
## NA's :17 NA's :23 NA's :17
## DemoODepend1994_1998 DemoODepend1999_2002 DemoODepend2003_2006
## Min. :19.90 Min. :17.80 Min. : 8.00
## 1st Qu.:22.10 1st Qu.:23.05 1st Qu.:22.30
## Median :24.90 Median :25.30 Median :25.60
## Mean :24.97 Mean :25.87 Mean :25.63
## 3rd Qu.:26.50 3rd Qu.:27.60 3rd Qu.:27.90
## Max. :33.80 Max. :39.70 Max. :41.20
## NA's :21 NA's :14 NA's :13
## DemoODepend2007_2009 Thh1989_1993 Thh1994_1998 Thh1999_2002
## Min. :16.50 Min. : 181700 Min. : 172189 Min. : 173215
## 1st Qu.:23.60 1st Qu.: 321757 1st Qu.: 300098 1st Qu.: 301566
## Median :27.25 Median : 468546 Median : 501000 Median : 459053
## Mean :27.29 Mean : 640428 Mean : 677489 Mean : 650780
## 3rd Qu.:29.25 3rd Qu.: 745727 3rd Qu.: 784475 3rd Qu.: 757578
## Max. :42.10 Max. :2841000 Max. :3002000 Max. :3015997
## NA's :20 NA's :20 NA's :27 NA's :13
## Thh2003_2006 Thh2007_2009 Ndwe1989_1993 Ndwe1994_1998
## Min. : 169913 Min. : 179823 Min. : 245810 Min. : 172218
## 1st Qu.: 315000 1st Qu.: 311600 1st Qu.: 336712 1st Qu.: 318326
## Median : 445413 Median : 441678 Median : 640641 Median : 483800
## Mean : 740042 Mean : 709285 Mean : 675929 Mean : 656970
## 3rd Qu.: 861892 3rd Qu.: 778750 3rd Qu.: 826938 3rd Qu.: 756840
## Max. :3112000 Max. :3243000 Max. :1734320 Max. :1792443
## NA's :23 NA's :27 NA's :35 NA's :43
## Ndwe1999_2002 Ndwe2003_2006 Ndwe2007_2009 Napart1989_1993
## Min. : 172753 Min. : 175200 Min. : 180500 Min. : 216902
## 1st Qu.: 318722 1st Qu.: 309745 1st Qu.: 300026 1st Qu.: 293286
## Median : 459753 Median : 473332 Median : 398317 Median : 493569
## Mean : 714348 Mean : 761303 Mean : 575072 Mean : 583210
## 3rd Qu.: 779094 3rd Qu.: 827429 3rd Qu.: 743266 3rd Qu.: 783494
## Max. :3401080 Max. :3414094 Max. :1890837 Max. :1128801
## NA's :13 NA's :19 NA's :29 NA's :46
## Napart1994_1998 Napart1999_2002 Napart2003_2006 Napart2007_2009
## Mode:logical Min. : 50230 Min. : 52280 Min. : 165200
## NA's:50 1st Qu.: 278208 1st Qu.: 287361 1st Qu.: 270472
## Median : 364509 Median : 371303 Median : 310492
## Mean : 533246 Mean : 542447 Mean : 579920
## 3rd Qu.: 651279 3rd Qu.: 660014 3rd Qu.: 663682
## Max. :1692262 Max. :1694180 Max. :1721929
## NA's :16 NA's :27 NA's :38
## Nhouse1989_1993 Nhouse1994_1998 Nhouse1999_2002 Nhouse2003_2006
## Min. : 10383 Mode:logical Min. : 5354 Min. : 10162
## 1st Qu.: 19111 NA's:50 1st Qu.: 21275 1st Qu.: 27275
## Median : 28908 Median : 43705 Median : 45387
## Mean : 50611 Mean : 103348 Mean : 74495
## 3rd Qu.: 40959 3rd Qu.: 92317 3rd Qu.: 98770
## Max. :153693 Max. :1553888 Max. :307987
## NA's :45 NA's :16 NA's :27
## Nhouse2007_2009 Aphouse1989_1993 Aphouse1994_1998 Aphouse1999_2002
## Min. : 1779 Min. : 477.3 Min. : 585.6 Min. : 160.0
## 1st Qu.: 35839 1st Qu.:1116.4 1st Qu.: 976.0 1st Qu.: 951.3
## Median : 70374 Median :1800.0 Median :1629.8 Median :1759.0
## Mean : 203085 Mean :1830.0 Mean :1797.1 Mean :1727.5
## 3rd Qu.: 144459 3rd Qu.:2350.0 3rd Qu.:2550.0 3rd Qu.:2476.8
## Max. :1570149 Max. :3700.0 Max. :3500.0 Max. :3784.0
## NA's :38 NA's :39 NA's :38 NA's :31
## Aphouse2003_2006 Aphouse2007_2009 ApapartMincome1989_1993
## Min. : 408.6 Min. : 238.7 Min. :0.1080
## 1st Qu.:1097.0 1st Qu.:1466.5 1st Qu.:0.1108
## Median :2200.0 Median :2800.0 Median :0.1190
## Mean :2187.3 Mean :2714.4 Mean :0.1270
## 3rd Qu.:2838.5 3rd Qu.:3833.0 3rd Qu.:0.1452
## Max. :4530.0 Max. :5399.9 Max. :0.1540
## NA's :27 NA's :31 NA's :44
## ApapartMincome1994_1998 ApapartMincome1999_2002 ApapartMincome2003_2006
## Min. :0.1070 Min. :0.0440 Min. :0.0800
## 1st Qu.:0.1138 1st Qu.:0.0775 1st Qu.:0.0915
## Median :0.1255 Median :0.0955 Median :0.1145
## Mean :0.1230 Mean :0.1095 Mean :0.1335
## 3rd Qu.:0.1305 3rd Qu.:0.1080 3rd Qu.:0.1610
## Max. :0.1380 Max. :0.3050 Max. :0.2660
## NA's :44 NA's :38 NA's :34
## ApapartMincome2007_2009 Arent-housing1989_1993 Arent-housing1994_1998
## Min. :0.0650 Mode:logical Mode:logical
## 1st Qu.:0.0950 NA's:50 NA's:50
## Median :0.1100
## Mean :0.1334
## 3rd Qu.:0.1340
## Max. :0.2870
## NA's :37
## Arent-housing1999_2002 Arent-housing2003_2006 Arent-housing2007_2009
## Min. : 3.00 Min. : 5.00 Min. : 8.00
## 1st Qu.:12.25 1st Qu.: 13.00 1st Qu.: 18.00
## Median :70.50 Median : 78.00 Median : 88.00
## Mean :55.00 Mean : 58.59 Mean : 76.06
## 3rd Qu.:80.50 3rd Qu.: 85.00 3rd Qu.: 99.00
## Max. :99.00 Max. :105.00 Max. :167.00
## NA's :34 NA's :33 NA's :33
## Alarea1989_1993 Alarea1994_1998 Alarea1999_2002 Alarea2003_2006
## Min. :14.91 Min. :16.70 Min. :13.20 Min. :14.80
## 1st Qu.:19.28 1st Qu.:21.06 1st Qu.:24.27 1st Qu.:32.71
## Median :32.75 Median :33.35 Median :34.90 Median :38.20
## Mean :28.58 Mean :30.16 Mean :31.65 Mean :34.29
## 3rd Qu.:35.12 3rd Qu.:38.12 3rd Qu.:38.00 3rd Qu.:40.35
## Max. :37.10 Max. :39.30 Max. :47.70 Max. :45.86
## NA's :32 NA's :38 NA's :19 NA's :30
## Alarea2007_2009 Phh-owndwe1989_1993 Phh-owndwe1994_1998 Phh-owndwe1999_2002
## Min. :15.85 Min. : 9.30 Min. :10.10 Min. :11.40
## 1st Qu.:27.03 1st Qu.:21.20 1st Qu.:16.45 1st Qu.:22.20
## Median :38.76 Median :39.90 Median :20.10 Median :50.00
## Mean :33.50 Mean :42.26 Mean :36.05 Mean :47.05
## 3rd Qu.:39.75 3rd Qu.:57.20 3rd Qu.:54.90 3rd Qu.:64.20
## Max. :46.44 Max. :86.50 Max. :78.10 Max. :88.80
## NA's :35 NA's :23 NA's :39 NA's :13
## Phh-owndwe2003_2006 Phh-owndwe2007_2009 Urate1989_1993 Urate1994_1998
## Min. :11.50 Min. :12.80 Min. : 1.300 Min. : 2.00
## 1st Qu.:19.27 1st Qu.:19.93 1st Qu.: 4.025 1st Qu.: 8.60
## Median :23.50 Median :21.25 Median : 7.150 Median : 9.30
## Mean :36.59 Mean :36.03 Mean :10.575 Mean :12.24
## 3rd Qu.:50.80 3rd Qu.:41.15 3rd Qu.:14.250 3rd Qu.:16.60
## Max. :84.70 Max. :85.20 Max. :42.700 Max. :27.80
## NA's :32 NA's :38 NA's :26 NA's :29
## Urate1999_2002 Urate2003_2006 Urate2007_2009 Ncom-head1989_1993
## Min. : 2.600 Min. : 3.300 Min. : 1.100 Mode:logical
## 1st Qu.: 5.250 1st Qu.: 6.700 1st Qu.: 5.225 NA's:50
## Median : 8.000 Median : 8.900 Median : 6.550
## Mean : 9.842 Mean : 9.134 Mean : 6.906
## 3rd Qu.:12.475 3rd Qu.:11.300 3rd Qu.: 8.550
## Max. :31.800 Max. :19.100 Max. :15.300
## NA's :14 NA's :15 NA's :32
## Ncom-head1994_1998 Ncom-head1999_2002 Ncom-head2003_2006 Ncom-head2007_2009
## Mode:logical Min. : 8.00 Min. : 2.00 Min. : 9.00
## NA's:50 1st Qu.: 23.25 1st Qu.: 12.50 1st Qu.: 21.75
## Median : 46.00 Median : 21.00 Median : 38.00
## Mean :171.55 Mean : 42.74 Mean : 64.42
## 3rd Qu.:117.00 3rd Qu.: 37.50 3rd Qu.: 68.75
## Max. :985.00 Max. :331.00 Max. :210.00
## NA's :28 NA's :27 NA's :38
## Mhhincome1989_1993 Mhhincome1994_1998 Mhhincome1999_2002 Mhhincome2003_2006
## Min. :11913 Min. : 1091 Min. : 1641 Min. : 2877
## 1st Qu.:14350 1st Qu.: 8118 1st Qu.:12148 1st Qu.:12475
## Median :14988 Median :15500 Median :17476 Median :17400
## Mean :14511 Mean :11525 Mean :15866 Mean :15766
## 3rd Qu.:15225 3rd Qu.:16000 3rd Qu.:21700 3rd Qu.:20600
## Max. :15700 Max. :17400 Max. :26490 Max. :26544
## NA's :42 NA's :35 NA's :25 NA's :33
## Mhhincome2007_2009 Ahhincome1989_1993 Ahhincome1994_1998 Ahhincome1999_2002
## Min. : 3437 Mode:logical Mode:logical Min. : 2873
## 1st Qu.:13587 NA's:50 NA's:50 1st Qu.:21302
## Median :21650 Median :24900
## Mean :18643 Mean :22507
## 3rd Qu.:23275 3rd Qu.:26022
## Max. :32210 Max. :38516
## NA's :36 NA's :35
## Ahhincome2003_2006 Ahhincome2007_2009 RQ1-Q4earn1989_1993 RQ1-Q4earn1994_1998
## Min. : 3592 Min. : 4278 Mode:logical Mode:logical
## 1st Qu.:21926 1st Qu.:23952 NA's:50 NA's:50
## Median :25150 Median :28200
## Mean :22890 Mean :24842
## 3rd Qu.:27525 3rd Qu.:30437
## Max. :40250 Max. :35917
## NA's :32 NA's :31
## RQ1-Q4earn1999_2002 RQ1-Q4earn2003_2006 RQ1-Q4earn2007_2009
## Min. :0.20 Min. :0.3000 Min. :0.3000
## 1st Qu.:0.30 1st Qu.:0.3000 1st Qu.:0.3000
## Median :0.40 Median :0.3000 Median :0.3000
## Mean :0.35 Mean :0.3429 Mean :0.3286
## 3rd Qu.:0.40 3rd Qu.:0.4000 3rd Qu.:0.3750
## Max. :0.50 Max. :0.4000 Max. :0.4000
## NA's :32 NA's :36 NA's :36
## HhincomeQ21989_1993 HhincomeQ21994_1998 HhincomeQ21999_2002
## Mode:logical Mode:logical Min. : 1374
## NA's:50 NA's:50 1st Qu.:11138
## Median :16500
## Mean :14535
## 3rd Qu.:18350
## Max. :28444
## NA's :32
## HhincomeQ22003_2006 HhincomeQ22007_2009 HhincomeQ31989_1993
## Min. : 2498 Min. : 2838 Mode:logical
## 1st Qu.:12900 1st Qu.:11096 NA's:50
## Median :16900 Median :18350
## Mean :14058 Mean :15866
## 3rd Qu.:17900 3rd Qu.:19975
## Max. :23502 Max. :27899
## NA's :37 NA's :36
## HhincomeQ31994_1998 HhincomeQ31999_2002 HhincomeQ32003_2006
## Mode:logical Min. : 2009 Min. : 3338
## NA's:50 1st Qu.:15869 1st Qu.:19509
## Median :22907 Median :23400
## Mean :20194 Mean :19306
## 3rd Qu.:25450 3rd Qu.:24500
## Max. :43628 Max. :30372
## NA's :32 NA's :37
## HhincomeQ32007_2009 Tlandarea1989_1993 Tlandarea1994_1998 Tlandarea1999_2002
## Min. : 3989 Min. : 39.0 Min. : 83.8 Min. : 38.9
## 1st Qu.:15830 1st Qu.: 139.5 1st Qu.: 144.1 1st Qu.: 158.3
## Median :25450 Median : 267.1 Median : 287.2 Median : 248.4
## Mean :21855 Mean : 363.2 Mean : 364.2 Mean : 382.6
## 3rd Qu.:27325 3rd Qu.: 487.8 3rd Qu.: 495.0 3rd Qu.: 494.0
## Max. :36527 Max. :1498.7 Max. :1285.3 Max. :1572.0
## NA's :36 NA's :26 NA's :23 NA's :17
## Tlandarea2003_2006 Tlandarea2007_2009 Larea-leisure1989_1993
## Min. : 38.9 Min. : 84.7 Min. :1.50
## 1st Qu.: 141.3 1st Qu.: 148.2 1st Qu.:3.05
## Median : 217.0 Median : 248.3 Median :4.60
## Mean : 327.9 Mean : 359.3 Mean :4.60
## 3rd Qu.: 426.2 3rd Qu.: 496.0 3rd Qu.:6.15
## Max. :1285.3 Max. :1307.7 Max. :7.70
## NA's :21 NA's :25 NA's :48
## Larea-leisure1994_1998 Larea-leisure1999_2002 Larea-leisure2003_2006
## Min. :2.000 Min. : 0.00 Min. : 2.40
## 1st Qu.:2.600 1st Qu.: 4.35 1st Qu.:10.40
## Median :3.200 Median : 9.45 Median :22.00
## Mean :3.667 Mean :15.34 Mean :21.76
## 3rd Qu.:4.500 3rd Qu.:24.60 3rd Qu.:34.20
## Max. :5.800 Max. :38.90 Max. :42.80
## NA's :47 NA's :32 NA's :33
## Larea-leisure2007_2009 Parea-housing1989_1993 Parea-housing1994_1998
## Min. : 5.80 Min. :34 Min. :16.50
## 1st Qu.:18.70 1st Qu.:34 1st Qu.:29.25
## Median :26.70 Median :34 Median :37.10
## Mean :25.09 Mean :34 Mean :38.79
## 3rd Qu.:31.18 3rd Qu.:34 3rd Qu.:44.05
## Max. :42.00 Max. :34 Max. :71.30
## NA's :38 NA's :49 NA's :43
## Parea-housing1999_2002 Parea-housing2003_2006 Parea-housing2007_2009
## Min. : 4.30 Min. :10.70 Min. :13.10
## 1st Qu.:14.75 1st Qu.:14.25 1st Qu.:15.12
## Median :20.20 Median :19.60 Median :18.00
## Mean :23.02 Mean :24.40 Mean :19.12
## 3rd Qu.:24.45 3rd Qu.:27.98 3rd Qu.:22.70
## Max. :72.00 Max. :72.10 Max. :28.60
## NA's :31 NA's :34 NA's :38
## Ppldens1989_1993 Ppldens1994_1998 Ppldens1999_2002 Ppldens2003_2006
## Min. : 1852 Min. : 2014 Min. : 1384 Min. : 1243
## 1st Qu.: 2674 1st Qu.: 2627 1st Qu.: 2510 1st Qu.: 2608
## Median : 3775 Median : 3816 Median : 3768 Median : 4030
## Mean : 5357 Mean : 4622 Mean : 5271 Mean : 5103
## 3rd Qu.: 6031 3rd Qu.: 5617 3rd Qu.: 5633 3rd Qu.: 6196
## Max. :19797 Max. :15240 Max. :20287 Max. :20467
## NA's :26 NA's :26 NA's :18 NA's :21
## Ppldens2007_2009 Netresidens-housingarea1989_1993
## Min. : 1313 Min. :48871
## 1st Qu.: 2486 1st Qu.:48871
## Median : 3306 Median :48871
## Mean : 4477 Mean :48871
## 3rd Qu.: 5778 3rd Qu.:48871
## Max. :16454 Max. :48871
## NA's :25 NA's :49
## Netresidens-housingarea1994_1998 Netresidens-housingarea1999_2002
## Min. : 7075 Min. : 6422
## 1st Qu.: 7362 1st Qu.: 13804
## Median :11080 Median : 18127
## Mean :18732 Mean : 42694
## 3rd Qu.:22451 3rd Qu.: 25980
## Max. :45694 Max. :465043
## NA's :46 NA's :31
## Netresidens-housingarea2003_2006 Netresidens-housingarea2007_2009
## Min. : 8265 Min. : 8537
## 1st Qu.:12476 1st Qu.:13269
## Median :16750 Median :16869
## Mean :17101 Mean :16338
## 3rd Qu.:20177 3rd Qu.:18911
## Max. :28404 Max. :22743
## NA's :33 NA's :38
## APApartment1989_1993 APApartment1994_1998 APApartment1999_2002
## Min. :1600 Min. : 848 Min. : 217.7
## 1st Qu.:1725 1st Qu.:1700 1st Qu.:1072.7
## Median :1800 Median :2000 Median :1342.5
## Mean :1883 Mean :1821 Mean :1425.4
## 3rd Qu.:1950 3rd Qu.:2150 3rd Qu.:1879.2
## Max. :2400 Max. :2200 Max. :2666.8
## NA's :44 NA's :43 NA's :34
## APApartment2003_2006 APApartment2007_2009 Temp_Jul1989_1993 Temp_Jul1994_1998
## Min. : 341 Min. : 962 Min. :17.40 Min. :14.80
## 1st Qu.:1352 1st Qu.:1660 1st Qu.:18.20 1st Qu.:20.85
## Median :2007 Median :2150 Median :19.00 Median :26.00
## Mean :2017 Mean :2468 Mean :20.77 Mean :25.33
## 3rd Qu.:2681 3rd Qu.:3232 3rd Qu.:22.45 3rd Qu.:29.55
## Max. :4486 Max. :5269 Max. :25.90 Max. :36.00
## NA's :23 NA's :29 NA's :47 NA's :39
## Temp_Jul1999_2002 Temp_Jul2003_2006 Temp_Jul2007_2009 Temp_Jan1989_1993
## Min. :18.50 Min. :16.00 Min. :16.70 Min. :-1.800
## 1st Qu.:20.00 1st Qu.:19.00 1st Qu.:18.50 1st Qu.: 0.300
## Median :21.00 Median :20.45 Median :20.30 Median : 2.400
## Mean :22.40 Mean :21.44 Mean :22.06 Mean : 3.333
## 3rd Qu.:25.12 3rd Qu.:24.52 3rd Qu.:25.12 3rd Qu.: 5.900
## Max. :31.50 Max. :29.20 Max. :32.00 Max. : 9.400
## NA's :20 NA's :16 NA's :22 NA's :47
## Temp_Jan1994_1998 Temp_Jan1999_2002 Temp_Jan2003_2006 Temp_Jan2007_2009
## Min. :-8.500 Min. :-7.200 Min. :-7.700 Min. :-3.000
## 1st Qu.: 1.800 1st Qu.:-0.625 1st Qu.:-1.475 1st Qu.: 0.375
## Median : 4.500 Median : 1.700 Median : 1.600 Median : 1.950
## Mean : 4.122 Mean : 2.480 Mean : 2.006 Mean : 2.754
## 3rd Qu.: 7.600 3rd Qu.: 6.150 3rd Qu.: 5.525 3rd Qu.: 3.650
## Max. :13.400 Max. :13.200 Max. :11.900 Max. :11.700
## NA's :41 NA's :20 NA's :16 NA's :22
## Latitude_deg Latitude_min Latitude_sec Longitude_deg
## Min. :37.00 Min. : 0.00 Min. : 0.00 Min. :-9.00
## 1st Qu.:44.25 1st Qu.:17.50 1st Qu.: 0.00 1st Qu.: 6.00
## Median :50.00 Median :28.00 Median : 0.00 Median :14.00
## Mean :48.72 Mean :29.98 Mean :14.07 Mean :17.44
## 3rd Qu.:53.00 3rd Qu.:45.75 3rd Qu.:32.75 3rd Qu.:26.75
## Max. :59.00 Max. :56.00 Max. :59.76 Max. :60.00
##
## Longitude_min Longitude_sec Lat Lon
## Min. :-59.00 Min. :-57.000 Min. :37.38 Min. :-9.185
## 1st Qu.: 6.00 1st Qu.: 0.000 1st Qu.:44.88 1st Qu.: 6.829
## Median : 21.00 Median : 0.000 Median :50.04 Median :14.336
## Mean : 20.18 Mean : 8.731 Mean :49.22 Mean :17.779
## 3rd Qu.: 39.25 3rd Qu.: 22.250 3rd Qu.:53.50 3rd Qu.:27.143
## Max. : 59.00 Max. : 59.000 Max. :59.93 Max. :60.583
##
## Liveability2010 Mercer_Qual_Liv2011 Mercer_Per_Safe2011 ECM2010
## Min. :61.00 Min. : 1.0 Min. : 5.00 Min. :0.0200
## 1st Qu.:80.00 1st Qu.:16.0 1st Qu.: 11.00 1st Qu.:0.0550
## Median :90.00 Median :30.0 Median : 20.50 Median :0.1000
## Mean :86.23 Mean :33.2 Mean : 34.94 Mean :0.1663
## 3rd Qu.:93.00 3rd Qu.:42.0 3rd Qu.: 40.50 3rd Qu.:0.2300
## Max. :98.00 Max. :84.0 Max. :199.00 Max. :0.8500
## NA's :19 NA's :25 NA's :34 NA's :23
## ECM_Cost2010
## Min. :0.0200
## 1st Qu.:0.1600
## Median :0.2700
## Mean :0.4637
## 3rd Qu.:0.6350
## Max. :1.4200
## NA's :23library(dplyr)Revision de valores faltantes
faltantes <- data.frame(
Variable = names(base_taller),
NAs = colSums(is.na(base_taller))
)
faltantes## Variable NAs
## City City 0
## City_Eng City_Eng 0
## City_Short City_Short 0
## NAds NAds 0
## Price_Median Price_Median 0
## Price_Mean Price_Mean 0
## Area_Median Area_Median 0
## Area_Mean Area_Mean 0
## Room_Median Room_Median 0
## Room_Mean Room_Mean 0
## Euro_area Euro_area 0
## EU EU 0
## Population Population 0
## City_Area City_Area 0
## Density Density 0
## GDP_PC GDP_PC 0
## GDP_PC_PPS GDP_PC_PPS 0
## GDP_PC2008 GDP_PC2008 0
## GDP_PC2009 GDP_PC2009 0
## GDP_PC2010 GDP_PC2010 0
## Gini Gini 0
## HOR HOR 0
## Kearny_GCI2010 Kearny_GCI2010 0
## LRIR LRIR 0
## Inflation2010 Inflation2010 0
## Inflation2011 Inflation2011 6
## URate URate 0
## MIR2009 MIR2009 2
## MIR2010 MIR2010 2
## Mortgage_PC2010 Mortgage_PC2010 2
## Tppl1989_1993 Tppl1989_1993 17
## Tppl1994_1998 Tppl1994_1998 19
## Tppl1999_2002 Tppl1999_2002 14
## Tppl2003_2006 Tppl2003_2006 14
## Tppl2007_2009 Tppl2007_2009 20
## GDP_PC_PPS1989_1993 GDP_PC_PPS1989_1993 50
## GDP_PC_PPS1994_1998 GDP_PC_PPS1994_1998 16
## GDP_PC_PPS1999_2002 GDP_PC_PPS1999_2002 16
## GDP_PC_PPS2003_2006 GDP_PC_PPS2003_2006 15
## GDP_PC_PPS2007_2009 GDP_PC_PPS2007_2009 15
## CITIES CITIES 13
## DemoDepend1989_1993 DemoDepend1989_1993 22
## DemoDepend1994_1998 DemoDepend1994_1998 25
## DemoDepend1999_2002 DemoDepend1999_2002 19
## DemoDepend2003_2006 DemoDepend2003_2006 17
## DemoDepend2007_2009 DemoDepend2007_2009 23
## DemoODepend1989_1993 DemoODepend1989_1993 17
## DemoODepend1994_1998 DemoODepend1994_1998 21
## DemoODepend1999_2002 DemoODepend1999_2002 14
## DemoODepend2003_2006 DemoODepend2003_2006 13
## DemoODepend2007_2009 DemoODepend2007_2009 20
## Thh1989_1993 Thh1989_1993 20
## Thh1994_1998 Thh1994_1998 27
## Thh1999_2002 Thh1999_2002 13
## Thh2003_2006 Thh2003_2006 23
## Thh2007_2009 Thh2007_2009 27
## Ndwe1989_1993 Ndwe1989_1993 35
## Ndwe1994_1998 Ndwe1994_1998 43
## Ndwe1999_2002 Ndwe1999_2002 13
## Ndwe2003_2006 Ndwe2003_2006 19
## Ndwe2007_2009 Ndwe2007_2009 29
## Napart1989_1993 Napart1989_1993 46
## Napart1994_1998 Napart1994_1998 50
## Napart1999_2002 Napart1999_2002 16
## Napart2003_2006 Napart2003_2006 27
## Napart2007_2009 Napart2007_2009 38
## Nhouse1989_1993 Nhouse1989_1993 45
## Nhouse1994_1998 Nhouse1994_1998 50
## Nhouse1999_2002 Nhouse1999_2002 16
## Nhouse2003_2006 Nhouse2003_2006 27
## Nhouse2007_2009 Nhouse2007_2009 38
## Aphouse1989_1993 Aphouse1989_1993 39
## Aphouse1994_1998 Aphouse1994_1998 38
## Aphouse1999_2002 Aphouse1999_2002 31
## Aphouse2003_2006 Aphouse2003_2006 27
## Aphouse2007_2009 Aphouse2007_2009 31
## ApapartMincome1989_1993 ApapartMincome1989_1993 44
## ApapartMincome1994_1998 ApapartMincome1994_1998 44
## ApapartMincome1999_2002 ApapartMincome1999_2002 38
## ApapartMincome2003_2006 ApapartMincome2003_2006 34
## ApapartMincome2007_2009 ApapartMincome2007_2009 37
## Arent-housing1989_1993 Arent-housing1989_1993 50
## Arent-housing1994_1998 Arent-housing1994_1998 50
## Arent-housing1999_2002 Arent-housing1999_2002 34
## Arent-housing2003_2006 Arent-housing2003_2006 33
## Arent-housing2007_2009 Arent-housing2007_2009 33
## Alarea1989_1993 Alarea1989_1993 32
## Alarea1994_1998 Alarea1994_1998 38
## Alarea1999_2002 Alarea1999_2002 19
## Alarea2003_2006 Alarea2003_2006 30
## Alarea2007_2009 Alarea2007_2009 35
## Phh-owndwe1989_1993 Phh-owndwe1989_1993 23
## Phh-owndwe1994_1998 Phh-owndwe1994_1998 39
## Phh-owndwe1999_2002 Phh-owndwe1999_2002 13
## Phh-owndwe2003_2006 Phh-owndwe2003_2006 32
## Phh-owndwe2007_2009 Phh-owndwe2007_2009 38
## Urate1989_1993 Urate1989_1993 26
## Urate1994_1998 Urate1994_1998 29
## Urate1999_2002 Urate1999_2002 14
## Urate2003_2006 Urate2003_2006 15
## Urate2007_2009 Urate2007_2009 32
## Ncom-head1989_1993 Ncom-head1989_1993 50
## Ncom-head1994_1998 Ncom-head1994_1998 50
## Ncom-head1999_2002 Ncom-head1999_2002 28
## Ncom-head2003_2006 Ncom-head2003_2006 27
## Ncom-head2007_2009 Ncom-head2007_2009 38
## Mhhincome1989_1993 Mhhincome1989_1993 42
## Mhhincome1994_1998 Mhhincome1994_1998 35
## Mhhincome1999_2002 Mhhincome1999_2002 25
## Mhhincome2003_2006 Mhhincome2003_2006 33
## Mhhincome2007_2009 Mhhincome2007_2009 36
## Ahhincome1989_1993 Ahhincome1989_1993 50
## Ahhincome1994_1998 Ahhincome1994_1998 50
## Ahhincome1999_2002 Ahhincome1999_2002 35
## Ahhincome2003_2006 Ahhincome2003_2006 32
## Ahhincome2007_2009 Ahhincome2007_2009 31
## RQ1-Q4earn1989_1993 RQ1-Q4earn1989_1993 50
## RQ1-Q4earn1994_1998 RQ1-Q4earn1994_1998 50
## RQ1-Q4earn1999_2002 RQ1-Q4earn1999_2002 32
## RQ1-Q4earn2003_2006 RQ1-Q4earn2003_2006 36
## RQ1-Q4earn2007_2009 RQ1-Q4earn2007_2009 36
## HhincomeQ21989_1993 HhincomeQ21989_1993 50
## HhincomeQ21994_1998 HhincomeQ21994_1998 50
## HhincomeQ21999_2002 HhincomeQ21999_2002 32
## HhincomeQ22003_2006 HhincomeQ22003_2006 37
## HhincomeQ22007_2009 HhincomeQ22007_2009 36
## HhincomeQ31989_1993 HhincomeQ31989_1993 50
## HhincomeQ31994_1998 HhincomeQ31994_1998 50
## HhincomeQ31999_2002 HhincomeQ31999_2002 32
## HhincomeQ32003_2006 HhincomeQ32003_2006 37
## HhincomeQ32007_2009 HhincomeQ32007_2009 36
## Tlandarea1989_1993 Tlandarea1989_1993 26
## Tlandarea1994_1998 Tlandarea1994_1998 23
## Tlandarea1999_2002 Tlandarea1999_2002 17
## Tlandarea2003_2006 Tlandarea2003_2006 21
## Tlandarea2007_2009 Tlandarea2007_2009 25
## Larea-leisure1989_1993 Larea-leisure1989_1993 48
## Larea-leisure1994_1998 Larea-leisure1994_1998 47
## Larea-leisure1999_2002 Larea-leisure1999_2002 32
## Larea-leisure2003_2006 Larea-leisure2003_2006 33
## Larea-leisure2007_2009 Larea-leisure2007_2009 38
## Parea-housing1989_1993 Parea-housing1989_1993 49
## Parea-housing1994_1998 Parea-housing1994_1998 43
## Parea-housing1999_2002 Parea-housing1999_2002 31
## Parea-housing2003_2006 Parea-housing2003_2006 34
## Parea-housing2007_2009 Parea-housing2007_2009 38
## Ppldens1989_1993 Ppldens1989_1993 26
## Ppldens1994_1998 Ppldens1994_1998 26
## Ppldens1999_2002 Ppldens1999_2002 18
## Ppldens2003_2006 Ppldens2003_2006 21
## Ppldens2007_2009 Ppldens2007_2009 25
## Netresidens-housingarea1989_1993 Netresidens-housingarea1989_1993 49
## Netresidens-housingarea1994_1998 Netresidens-housingarea1994_1998 46
## Netresidens-housingarea1999_2002 Netresidens-housingarea1999_2002 31
## Netresidens-housingarea2003_2006 Netresidens-housingarea2003_2006 33
## Netresidens-housingarea2007_2009 Netresidens-housingarea2007_2009 38
## APApartment1989_1993 APApartment1989_1993 44
## APApartment1994_1998 APApartment1994_1998 43
## APApartment1999_2002 APApartment1999_2002 34
## APApartment2003_2006 APApartment2003_2006 23
## APApartment2007_2009 APApartment2007_2009 29
## Temp_Jul1989_1993 Temp_Jul1989_1993 47
## Temp_Jul1994_1998 Temp_Jul1994_1998 39
## Temp_Jul1999_2002 Temp_Jul1999_2002 20
## Temp_Jul2003_2006 Temp_Jul2003_2006 16
## Temp_Jul2007_2009 Temp_Jul2007_2009 22
## Temp_Jan1989_1993 Temp_Jan1989_1993 47
## Temp_Jan1994_1998 Temp_Jan1994_1998 41
## Temp_Jan1999_2002 Temp_Jan1999_2002 20
## Temp_Jan2003_2006 Temp_Jan2003_2006 16
## Temp_Jan2007_2009 Temp_Jan2007_2009 22
## Latitude_deg Latitude_deg 0
## Latitude_min Latitude_min 0
## Latitude_sec Latitude_sec 0
## Longitude_deg Longitude_deg 0
## Longitude_min Longitude_min 0
## Longitude_sec Longitude_sec 0
## Lat Lat 0
## Lon Lon 0
## Liveability2010 Liveability2010 19
## Mercer_Qual_Liv2011 Mercer_Qual_Liv2011 25
## Mercer_Per_Safe2011 Mercer_Per_Safe2011 34
## ECM2010 ECM2010 23
## ECM_Cost2010 ECM_Cost2010 23Matriz de correlacion entre variables explicativas y dependientes
# Filtrar solo las variables numéricas de interés
vars <- c("Price_Median", "Area_Median", "Room_Median", "GDP_PC", "URate", "MIR2010")
datos_cor <- base_taller[, vars]
library(Hmisc)
cor_test <- rcorr(as.matrix(datos_cor))library(Hmisc)
library(corrplot)
vars <- c("Price_Median", "Area_Median", "Room_Median", "GDP_PC", "URate", "MIR2010")
datos_cor <- base_taller[, vars]
datos_cor <- data.frame(lapply(datos_cor, as.numeric))
datos_cor <- na.omit(datos_cor)
# Calcular correlaciones y p-valores
cor_test <- rcorr(as.matrix(datos_cor))
matrizcor <- round(cor_test$r, 3)
pval <- cor_test$P
# Asegurar que las dimensiones y nombres coincidan
stopifnot(identical(dim(matrizcor), dim(pval)))
rownames(pval) <- rownames(matrizcor)
colnames(pval) <- colnames(matrizcor)
# Reemplazar NA en pval si los hay
pval[is.na(pval)] <- 1
# Graficar
corrplot(
matrizcor,
method = "color",
type = "upper",
tl.col = "black",
tl.srt = 45,
addCoef.col = "black",
number.cex = 0.7,
p.mat = pval, # Matriz de p-valores
sig.level = 0.05, # Nivel de significancia
insig = "blank", # Oculta correlaciones no significativas
title = "Mapa de calor de correlaciones significativas",
mar = c(0, 0, 2, 0) # Márgenes del gráfico
)
# Seleccionar las variables vars <- c(“Price_Median”, “Area_Median”,
“Room_Median”, “GDP_PC”, “URate”, “MIR2010”)
Matriz de dispersión con otro color
pairs(base_taller[vars], main = “Matriz de dispersión”, pch = 19, col = “blue”) # cambia el color aquí (ej: “red”, “purple”, “orange”)
grafios de dispercion:`
## Matriz de dispersión con pares de variables
# Seleccionar las variables
vars <- c("Price_Median", "Area_Median", "Room_Median", "GDP_PC", "URate", "MIR2010")
# Matriz de dispersión con otro color
pairs(base_taller[vars],
main = "Matriz de dispersión",
pch = 19, col = "blue") # puedes cambiar: "red", "purple", "orange", etc.
Graficos de dispersion individuales
## Dispersión de Price_Median vs Area_Median
ggplot(base_taller, aes(x = Area_Median, y = Price_Median)) +
geom_point(color = "steelblue", alpha = 0.6) +
geom_smooth(method = "lm", se = FALSE, color = "red") +
labs(title = "Dispersión de Price_Median vs Area_Median",
x = "Area_Median", y = "Price_Median") +
theme_minimal()## `geom_smooth()` using formula = 'y ~ x'
## Gráfico 2 – Price_Median vs Room_Media
## Dispersión de Price_Median vs Room_Median
ggplot(base_taller, aes(x = Room_Median, y = Price_Median)) +
geom_point(color = "steelblue", alpha = 0.6) +
geom_smooth(method = "lm", se = FALSE, color = "red") +
labs(title = "Dispersión de Price_Median vs Room_Median",
x = "Room_Median", y = "Price_Median") +
theme_minimal()## `geom_smooth()` using formula = 'y ~ x'
## Gráfico 3
## Dispersión de Price_Median vs GDP_PC
ggplot(base_taller, aes(x = GDP_PC, y = Price_Median)) +
geom_point(color = "steelblue", alpha = 0.6) +
geom_smooth(method = "lm", se = FALSE, color = "red") +
labs(title = "Dispersión de Price_Median vs GDP_PC",
x = "GDP_PC", y = "Price_Median") +
theme_minimal()## `geom_smooth()` using formula = 'y ~ x'
## Gráfico 4
## Dispersión de Price_Median vs URate
ggplot(base_taller, aes(x = URate, y = Price_Median)) +
geom_point(color = "steelblue", alpha = 0.6) +
geom_smooth(method = "lm", se = FALSE, color = "red") +
labs(title = "Dispersión de Price_Median vs URate",
x = "URate", y = "Price_Median") +
theme_minimal()## `geom_smooth()` using formula = 'y ~ x'
## Gráfico 5
## Dispersión de Price_Median vs MIR2010
ggplot(base_taller, aes(x = MIR2010, y = Price_Median)) +
geom_point(color = "steelblue", alpha = 0.6) +
geom_smooth(method = "lm", se = FALSE, color = "red") +
labs(title = "Dispersión de Price_Median vs MIR2010",
x = "MIR2010", y = "Price_Median") +
theme_minimal()## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 2 rows containing non-finite outside the scale range
## (`stat_smooth()`).## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_point()`).