Proba funcioens de librería dplyr
library(dplyr)
library(readr)datos.temperaturas <- read.csv("https://raw.githubusercontent.com/rpizarrog/CIIT.-Diplomado-en-Ciencia-de-los-Datos-e-IoT/main/M%C3%B3dulo%20I/datos/datos.temperaturas.csv", encoding = "UTF8", stringsAsFactors = TRUE)
datos.precipitaciones <- read.csv("https://raw.githubusercontent.com/rpizarrog/CIIT.-Diplomado-en-Ciencia-de-los-Datos-e-IoT/main/M%C3%B3dulo%20I/datos/datos.precipitaciones.csv", encoding = "UTF-8", stringsAsFactors = TRUE)Datos de temperatura
summary(datos.temperaturas)## X abreviatura entidad ene
## Min. : 1.00 AGS : 12 Aguascalientes : 9 Min. : 9.10
## 1st Qu.: 96.75 BC : 12 Baja California : 9 1st Qu.:13.70
## Median :192.50 BCS : 12 Baja California Sur : 9 Median :16.48
## Mean :192.50 CAMP : 12 Campeche : 9 Mean :17.09
## 3rd Qu.:288.25 CDMX : 12 Chiapas : 9 3rd Qu.:21.00
## Max. :384.00 CHIH : 12 Chihuahua : 9 Max. :25.90
## (Other):312 (Other) :330
## feb mar abr may
## Min. :10.10 Min. :13.40 Min. :14.80 Min. :16.80
## 1st Qu.:15.43 1st Qu.:18.04 1st Qu.:20.20 1st Qu.:22.03
## Median :18.10 Median :20.70 Median :22.85 Median :24.95
## Mean :18.70 Mean :20.95 Mean :23.01 Mean :24.65
## 3rd Qu.:22.60 3rd Qu.:24.02 3rd Qu.:25.80 3rd Qu.:27.20
## Max. :26.70 Max. :28.00 Max. :31.10 Max. :31.30
##
## jun jul ago sep
## Min. :15.70 Min. :15.30 Min. :15.00 Min. :14.10
## 1st Qu.:22.07 1st Qu.:21.07 1st Qu.:20.80 1st Qu.:20.50
## Median :25.71 Median :25.40 Median :25.20 Median :24.70
## Mean :24.97 Mean :24.63 Mean :24.68 Mean :23.89
## 3rd Qu.:28.24 3rd Qu.:28.40 3rd Qu.:28.48 3rd Qu.:27.70
## Max. :30.60 Max. :31.90 Max. :32.50 Max. :30.40
##
## oct nov dic anual agnio
## Min. :12.80 Min. :11.80 Min. : 9.30 Min. :14.00 Min. :2010
## 1st Qu.:18.71 1st Qu.:16.29 1st Qu.:13.97 1st Qu.:18.90 1st Qu.:2013
## Median :22.45 Median :19.34 Median :17.00 Median :22.30 Median :2016
## Mean :22.15 Mean :19.69 Mean :17.46 Mean :21.84 Mean :2016
## 3rd Qu.:25.60 3rd Qu.:23.62 3rd Qu.:21.20 3rd Qu.:25.02 3rd Qu.:2018
## Max. :29.50 Max. :28.00 Max. :26.60 Max. :28.10 Max. :2021
## NA's :32 NA's :32 NA's :32 NA's :192str(datos.temperaturas)## 'data.frame': 384 obs. of 17 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ abreviatura: Factor w/ 32 levels "AGS","BC","BCS",..: 1 2 3 4 8 9 7 6 5 10 ...
## $ entidad : Factor w/ 64 levels "Aguascalientes ",..: 2 4 6 8 15 17 10 12 18 20 ...
## $ ene : num 11.4 13.9 17.7 21.6 11.5 23.5 21 9.1 13.1 10 ...
## $ feb : num 12.2 13.8 18.2 23.1 12.4 23.1 23.3 10.1 14.6 10.6 ...
## $ mar : num 15.3 14.8 19 24.1 17.1 23.8 24 13.4 18.2 13.6 ...
## $ abr : num 18.3 15.9 20.8 28.6 22.3 25.1 26.7 18.1 18.8 17.7 ...
## $ may : num 21.4 18.8 23.1 29.9 26.4 26.1 26.7 21.6 20.8 21.4 ...
## $ jun : num 22.4 23.4 25.4 29.6 28.5 27.6 26.4 25.7 20.5 23.6 ...
## $ jul : num 19.9 27.2 27.5 28.4 26.2 26.8 25.3 23.9 18.1 21.6 ...
## $ ago : num 20.6 28.3 29.5 28.3 28 27 24.9 24.3 18.4 22.1 ...
## $ sep : num 20.8 26.1 28.3 28.1 22.2 24.3 25.1 26.6 17.9 20.8 ...
## $ oct : num 17.5 22.1 25.4 25.9 22 27.2 23.9 18.8 16.6 17.5 ...
## $ nov : num 15 16.7 20.5 25 17.4 24.8 22.9 13.4 14.9 13.5 ...
## $ dic : num 12.7 15.4 18.1 21.4 13.9 22.9 21.4 12 12.8 11.4 ...
## $ anual : num 17.3 19.7 22.8 26.2 20.7 25.2 24.3 18.1 17.1 17 ...
## $ agnio : int 2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 ...head(datos.temperaturas, 20)## X abreviatura entidad ene feb mar abr may jun jul ago
## 1 1 AGS AGUASCALIENTES 11.4 12.2 15.3 18.3 21.4 22.4 19.9 20.6
## 2 2 BC BAJA CALIFORNIA 13.9 13.8 14.8 15.9 18.8 23.4 27.2 28.3
## 3 3 BCS BAJA CALIFORNIA SUR 17.7 18.2 19.0 20.8 23.1 25.4 27.5 29.5
## 4 4 CAMP CAMPECHE 21.6 23.1 24.1 28.6 29.9 29.6 28.4 28.3
## 5 5 COAH COAHUILA 11.5 12.4 17.1 22.3 26.4 28.5 26.2 28.0
## 6 6 COL COLIMA 23.5 23.1 23.8 25.1 26.1 27.6 26.8 27.0
## 7 7 CHIS CHIAPAS 21.0 23.3 24.0 26.7 26.7 26.4 25.3 24.9
## 8 8 CHIH CHIHUAHUA 9.1 10.1 13.4 18.1 21.6 25.7 23.9 24.3
## 9 9 CDMX DISTRITO FEDERAL 13.1 14.6 18.2 18.8 20.8 20.5 18.1 18.4
## 10 10 DGO DURANGO 10.0 10.6 13.6 17.7 21.4 23.6 21.6 22.1
## 11 11 GTO GUANAJUATO 13.2 14.1 17.6 20.0 22.5 23.1 20.6 21.0
## 12 12 GRO GUERRERO 22.5 23.3 24.7 26.3 27.7 27.0 25.4 25.2
## 13 13 HGO HIDALGO 12.7 13.7 16.7 19.4 20.8 21.5 18.8 19.3
## 14 14 JAL JALISCO 15.5 16.4 19.0 21.0 24.0 24.5 22.5 22.8
## 15 15 MEX ESTADO DE MÉXICO 9.4 11.2 14.2 15.9 17.8 17.6 15.7 15.5
## 16 16 MICH MICHOACÁN 14.4 14.5 17.7 19.9 22.3 22.3 20.3 20.2
## 17 17 MOR MORELOS 17.3 19.0 22.5 23.4 26.4 24.9 22.2 22.2
## 18 18 NAY NAYARIT 21.0 21.2 22.9 25.0 26.8 28.8 27.2 28.0
## 19 19 NL NUEVO LEÓN 12.5 13.3 17.6 22.4 26.4 28.6 26.6 28.2
## 20 20 OAX OAXACA 20.0 21.5 23.2 25.9 27.4 26.0 24.6 24.5
## sep oct nov dic anual agnio
## 1 20.8 17.5 15.0 12.7 17.3 2010
## 2 26.1 22.1 16.7 15.4 19.7 2010
## 3 28.3 25.4 20.5 18.1 22.8 2010
## 4 28.1 25.9 25.0 21.4 26.2 2010
## 5 22.2 22.0 17.4 13.9 20.7 2010
## 6 24.3 27.2 24.8 22.9 25.2 2010
## 7 25.1 23.9 22.9 21.4 24.3 2010
## 8 26.6 18.8 13.4 12.0 18.1 2010
## 9 17.9 16.6 14.9 12.8 17.1 2010
## 10 20.8 17.5 13.5 11.4 17.0 2010
## 11 24.9 17.9 15.8 13.7 18.7 2010
## 12 20.5 25.6 23.9 21.8 24.5 2010
## 13 19.1 16.3 14.7 12.7 17.2 2010
## 14 22.6 20.6 18.0 17.3 20.4 2010
## 15 15.0 13.4 11.8 11.0 14.0 2010
## 16 20.0 18.1 16.1 14.0 18.3 2010
## 17 21.9 21.7 19.7 17.5 21.6 2010
## 18 27.5 27.1 23.6 21.4 25.0 2010
## 19 25.9 22.4 18.3 14.8 21.4 2010
## 20 23.8 23.4 22.7 20.2 23.6 2010tail(datos.temperaturas)## X abreviatura entidad ene feb mar abr may jun jul ago sep
## 379 379 TAB Tabasco 24.2 25.0 27.3 29.5 29.4 28.8 29.2 28.9 28.6
## 380 380 TAMPS Tamaulipas 18.4 18.3 23.0 26.3 28.2 28.7 28.6 29.7 28.5
## 381 381 TLAX Tlaxcala 12.6 13.0 16.2 16.8 16.9 16.0 15.8 15.9 15.8
## 382 382 VER Veracruz 19.0 19.9 22.5 24.9 25.8 25.1 24.9 24.7 24.7
## 383 383 YUC Yucatán 23.3 24.7 26.6 29.1 29.5 28.6 28.9 28.6 28.4
## 384 384 ZAC Zacatecas 13.0 15.5 18.2 19.9 21.6 21.2 20.0 20.2 19.5
## oct nov dic anual agnio
## 379 NA NA NA NA 2021
## 380 NA NA NA NA 2021
## 381 NA NA NA NA 2021
## 382 NA NA NA NA 2021
## 383 NA NA NA NA 2021
## 384 NA NA NA NA 2021Proyectar variables de un conjunto de datos o seleccionar ciertas columnas del conjunto de datos
select(.data = datos.temperaturas, abreviatura, agnio, ene, feb, mar, abr, may, jun)## abreviatura agnio ene feb mar abr may jun
## 1 AGS 2010 11.40000 12.20000 15.30000 18.30000 21.40000 22.40000
## 2 BC 2010 13.90000 13.80000 14.80000 15.90000 18.80000 23.40000
## 3 BCS 2010 17.70000 18.20000 19.00000 20.80000 23.10000 25.40000
## 4 CAMP 2010 21.60000 23.10000 24.10000 28.60000 29.90000 29.60000
## 5 COAH 2010 11.50000 12.40000 17.10000 22.30000 26.40000 28.50000
## 6 COL 2010 23.50000 23.10000 23.80000 25.10000 26.10000 27.60000
## 7 CHIS 2010 21.00000 23.30000 24.00000 26.70000 26.70000 26.40000
## 8 CHIH 2010 9.10000 10.10000 13.40000 18.10000 21.60000 25.70000
## 9 CDMX 2010 13.10000 14.60000 18.20000 18.80000 20.80000 20.50000
## 10 DGO 2010 10.00000 10.60000 13.60000 17.70000 21.40000 23.60000
## 11 GTO 2010 13.20000 14.10000 17.60000 20.00000 22.50000 23.10000
## 12 GRO 2010 22.50000 23.30000 24.70000 26.30000 27.70000 27.00000
## 13 HGO 2010 12.70000 13.70000 16.70000 19.40000 20.80000 21.50000
## 14 JAL 2010 15.50000 16.40000 19.00000 21.00000 24.00000 24.50000
## 15 MEX 2010 9.40000 11.20000 14.20000 15.90000 17.80000 17.60000
## 16 MICH 2010 14.40000 14.50000 17.70000 19.90000 22.30000 22.30000
## 17 MOR 2010 17.30000 19.00000 22.50000 23.40000 26.40000 24.90000
## 18 NAY 2010 21.00000 21.20000 22.90000 25.00000 26.80000 28.80000
## 19 NL 2010 12.50000 13.30000 17.60000 22.40000 26.40000 28.60000
## 20 OAX 2010 20.00000 21.50000 23.20000 25.90000 27.40000 26.00000
## 21 PUE 2010 12.10000 14.30000 16.90000 19.10000 21.10000 20.70000
## 22 QRO 2010 13.20000 13.90000 17.50000 20.30000 22.70000 23.00000
## 23 QROO 2010 22.50000 23.50000 23.40000 27.50000 28.60000 29.60000
## 24 SLP 2010 14.80000 15.80000 19.10000 23.40000 26.20000 27.00000
## 25 SIN 2010 19.60000 19.60000 21.30000 23.60000 26.30000 29.40000
## 26 SON 2010 13.70000 14.40000 16.80000 20.00000 23.40000 28.70000
## 27 TAB 2010 21.00000 22.90000 23.80000 28.50000 29.60000 30.00000
## 28 TAMPS 2010 15.50000 15.60000 19.50000 24.20000 27.70000 29.40000
## 29 TLAX 2010 10.60000 11.80000 14.20000 16.10000 17.70000 17.40000
## 30 VER 2010 16.60000 17.90000 20.10000 23.70000 26.10000 26.30000
## 31 YUC 2010 21.60000 22.30000 22.90000 27.50000 28.90000 29.40000
## 32 ZAC 2010 10.70000 11.10000 14.10000 17.40000 21.00000 21.90000
## 33 AGS 2011 12.80000 15.20000 17.90000 20.50000 22.40000 22.00000
## 34 BC 2011 14.10000 11.10000 16.30000 18.10000 19.60000 23.70000
## 35 BCS 2011 16.50000 16.40000 19.70000 21.10000 22.80000 25.00000
## 36 CAMP 2011 23.40000 25.00000 27.00000 29.50000 30.70000 28.20000
## 37 COAH 2011 13.00000 15.80000 21.80000 25.90000 27.50000 28.20000
## 38 COL 2011 22.70000 23.80000 23.90000 25.00000 27.60000 27.00000
## 39 CHIS 2011 22.20000 23.10000 24.40000 26.10000 27.70000 25.40000
## 40 CHIH 2011 10.50000 12.00000 17.80000 20.80000 23.00000 26.70000
## 41 CDMX 2011 14.60000 16.70000 17.20000 20.10000 21.40000 18.90000
## 42 DGO 2011 11.50000 13.30000 17.90000 20.30000 22.30000 24.40000
## 43 GTO 2011 14.70000 16.80000 18.70000 21.80000 23.80000 21.80000
## 44 GRO 2011 22.80000 24.50000 25.10000 26.70000 28.30000 26.20000
## 45 HGO 2011 14.90000 16.50000 17.70000 20.90000 22.20000 19.00000
## 46 JAL 2011 16.40000 18.40000 20.50000 22.60000 24.60000 23.90000
## 47 MEX 2011 11.60000 13.40000 14.40000 16.60000 18.30000 15.70000
## 48 MICH 2011 15.20000 17.20000 19.00000 24.80000 23.50000 21.60000
## 49 MOR 2011 18.40000 20.40000 22.60000 24.80000 24.80000 22.70000
## 50 NAY 2011 20.10000 20.90000 23.00000 24.20000 27.10000 28.10000
## 51 NL 2011 14.00000 17.00000 22.30000 24.70000 28.10000 27.90000
## 52 OAX 2011 21.50000 23.10000 24.70000 27.00000 28.40000 25.90000
## 53 PUE 2011 14.80000 16.10000 17.60000 20.10000 20.70000 18.90000
## 54 QRO 2011 15.20000 16.50000 17.60000 21.20000 22.80000 19.60000
## 55 QROO 2011 24.00000 24.80000 26.10000 28.30000 29.30000 27.50000
## 56 SLP 2011 17.50000 18.20000 23.80000 27.20000 28.40000 26.40000
## 57 SIN 2011 18.30000 18.50000 22.50000 23.80000 26.40000 29.20000
## 58 SON 2011 13.90000 14.00000 19.50000 21.80000 23.90000 28.90000
## 59 TAB 2011 22.60000 23.60000 25.80000 28.50000 29.60000 27.30000
## 60 TAMPS 2011 17.00000 18.20000 23.80000 27.40000 28.60000 28.60000
## 61 TLAX 2011 11.50000 13.70000 14.30000 17.00000 17.80000 16.10000
## 62 VER 2011 19.50000 20.10000 23.00000 26.70000 27.30000 25.50000
## 63 YUC 2011 22.40000 24.10000 26.00000 28.80000 29.70000 27.70000
## 64 ZAC 2011 11.90000 14.20000 17.50000 19.90000 21.80000 21.70000
## 65 AGS 2012 12.90000 14.00000 17.70000 18.50000 21.50000 21.60000
## 66 BC 2012 15.60000 13.40000 14.10000 17.60000 22.00000 23.90000
## 67 BCS 2012 17.60000 17.20000 18.70000 21.10000 24.00000 26.30000
## 68 CAMP 2012 23.90000 25.20000 26.90000 28.20000 29.50000 27.70000
## 69 COAH 2012 14.60000 15.50000 20.70000 24.30000 26.50000 26.50000
## 70 COL 2012 23.70000 23.80000 24.20000 20.40000 26.70000 26.60000
## 71 CHIS 2012 23.20000 23.60000 24.40000 23.50000 26.20000 25.30000
## 72 CHIH 2012 11.20000 12.30000 15.30000 25.10000 23.30000 26.50000
## 73 CDMX 2012 13.90000 15.10000 17.50000 17.90000 19.00000 18.80000
## 74 DGO 2012 12.10000 13.10000 16.40000 19.90000 22.10000 23.60000
## 75 GTO 2012 14.60000 15.90000 18.30000 22.50000 22.40000 22.00000
## 76 GRO 2012 23.70000 24.00000 25.70000 25.50000 27.40000 26.00000
## 77 HGO 2012 13.70000 14.80000 17.10000 18.80000 20.30000 20.40000
## 78 JAL 2012 16.70000 17.70000 19.90000 20.90000 24.00000 23.30000
## 79 MEX 2012 10.80000 12.40000 14.30000 14.80000 16.80000 16.30000
## 80 MICH 2012 15.90000 16.70000 19.70000 20.50000 23.40000 22.10000
## 81 MOR 2012 18.70000 20.30000 22.10000 23.10000 24.20000 22.90000
## 82 NAY 2012 21.10000 21.50000 23.00000 23.90000 27.50000 28.00000
## 83 NL 2012 15.80000 16.20000 20.90000 24.40000 26.30000 27.70000
## 84 OAX 2012 21.60000 23.30000 24.50000 25.20000 26.80000 25.50000
## 85 PUE 2012 15.10000 16.20000 17.90000 18.70000 20.00000 19.30000
## 86 QRO 2012 15.00000 16.70000 19.40000 20.70000 23.00000 21.30000
## 87 QROO 2012 24.10000 24.30000 26.30000 27.20000 28.40000 28.10000
## 88 SLP 2012 17.50000 19.00000 22.10000 23.60000 26.50000 26.70000
## 89 SIN 2012 19.40000 19.50000 20.80000 24.20000 27.80000 29.80000
## 90 SON 2012 15.20000 14.80000 17.10000 21.70000 26.00000 29.70000
## 91 TAB 2012 21.40000 24.00000 26.20000 24.00000 28.50000 27.50000
## 92 TAMPS 2012 18.30000 18.70000 22.90000 25.80000 27.90000 29.10000
## 93 TLAX 2012 11.40000 13.10000 14.70000 14.80000 17.00000 16.70000
## 94 VER 2012 18.80000 20.10000 22.60000 24.20000 25.60000 25.30000
## 95 YUC 2012 22.80000 24.30000 26.00000 26.80000 28.40000 27.60000
## 96 ZAC 2012 12.20000 13.30000 16.80000 18.20000 21.00000 21.10000
## 97 AGS 2013 12.81667 14.97222 17.93064 19.57576 21.54882 21.80202
## 98 BC 2013 14.40303 13.49512 15.20354 18.32811 20.49916 23.98249
## 99 BCS 2013 17.87525 18.10657 19.63434 21.72205 23.51768 26.20152
## 100 CAMP 2013 23.24259 25.25640 26.76027 29.21599 30.05556 28.96263
## 101 COAH 2013 13.03603 15.62963 20.05017 23.47424 26.76599 28.22475
## 102 COL 2013 24.48535 24.55505 25.04091 24.97071 27.05101 27.95185
## 103 CHIS 2013 22.71852 24.09495 25.03384 26.45118 27.08047 25.93131
## 104 CHIH 2013 10.42811 12.42290 16.01633 19.99226 22.96330 26.38468
## 105 CDMX 2013 14.46987 16.58737 18.52609 19.59529 20.46549 19.50370
## 106 DGO 2013 11.63114 13.84327 17.09697 19.55404 22.03013 23.94933
## 107 GTO 2013 14.62441 16.62138 19.39428 21.47475 22.78131 21.95118
## 108 GRO 2013 23.28923 24.22391 25.58805 26.46633 27.41599 26.31650
## 109 HGO 2013 14.43485 16.40354 18.50741 20.58535 21.66279 20.70724
## 110 JAL 2013 16.81953 18.61498 20.77963 22.09024 24.15825 24.24697
## 111 MEX 2013 11.24276 13.22492 15.28737 16.44731 17.49276 16.71835
## 112 MICH 2013 16.33098 17.83047 20.27576 22.22475 23.18872 22.36431
## 113 MOR 2013 18.68569 20.79916 23.53939 24.58148 25.01481 23.57508
## 114 NAY 2013 21.41566 22.42172 23.62710 24.89411 27.17172 28.78114
## 115 NL 2013 14.14007 16.53333 20.72323 23.49848 26.53401 27.71347
## 116 OAX 2013 20.99899 22.79158 24.25758 25.86414 26.81263 25.20791
## 117 PUE 2013 14.50152 16.49293 18.49680 20.17643 20.91835 20.09798
## 118 QRO 2013 15.07407 17.23956 19.76448 21.99040 23.41667 21.97256
## 119 QROO 2013 23.88535 25.30842 26.03569 28.22273 29.10034 29.02424
## 120 SLP 2013 17.23148 19.38552 22.69680 25.58906 27.44192 27.15791
## 121 SIN 2013 19.64916 20.23569 22.14343 24.24630 27.01128 29.97508
## 122 SON 2013 14.64276 15.07020 18.04024 21.45926 24.43603 29.41128
## 123 TAB 2013 22.80825 24.69192 26.30101 28.47727 29.72896 28.78872
## 124 TAMPS 2013 17.20909 18.89529 22.86549 25.85724 28.28468 29.16650
## 125 TLAX 2013 11.59697 13.56886 15.47862 16.73434 17.56734 16.84562
## 126 VER 2013 18.40438 20.11599 22.33232 24.79428 26.19933 25.64512
## 127 YUC 2013 22.53064 24.50202 25.77862 28.51380 29.24680 28.63535
## 128 ZAC 2013 12.25471 14.34040 17.35051 19.09562 21.36364 21.76498
## 129 AGS 2014 12.80833 15.06944 17.95370 19.68333 21.55370 21.82222
## 130 BC 2014 14.28333 13.50463 15.31389 18.40093 20.34907 23.99074
## 131 BCS 2014 17.90278 18.19722 19.72778 21.78426 23.46944 26.19167
## 132 CAMP 2014 23.17685 25.26204 26.74630 29.31759 30.11111 29.08889
## 133 COAH 2014 12.87963 15.64259 19.98519 23.39167 26.79259 28.39722
## 134 COL 2014 24.56389 24.63056 25.12500 25.42778 27.08611 28.08704
## 135 CHIS 2014 22.67037 24.14444 25.09722 26.74630 27.16852 25.99444
## 136 CHIH 2014 10.35093 12.43519 16.08796 19.48148 22.92963 26.37315
## 137 CDMX 2014 14.52685 16.73611 18.62870 19.76481 20.61204 19.57407
## 138 DGO 2014 11.58426 13.91759 17.16667 19.51944 22.02315 23.98426
## 139 GTO 2014 14.62685 16.69352 19.50370 21.37222 22.81944 21.94630
## 140 GRO 2014 23.24815 24.24630 25.57685 26.56296 27.41759 26.34815
## 141 HGO 2014 14.50833 16.56389 18.64815 20.76389 21.79907 20.73796
## 142 JAL 2014 16.83148 18.70648 20.86759 22.20926 24.17407 24.34167
## 143 MEX 2014 11.28704 13.30741 15.38611 16.61204 17.56204 16.76019
## 144 MICH 2014 16.37407 17.94352 20.33333 22.39722 23.16759 22.39074
## 145 MOR 2014 18.68426 20.84907 23.68333 24.72963 25.09630 23.64259
## 146 NAY 2014 21.44722 22.51389 23.68981 24.99352 27.13889 28.85926
## 147 NL 2014 13.97407 16.56667 20.70556 23.40833 26.55741 27.71481
## 148 OAX 2014 20.93889 22.74074 24.23333 25.93056 26.81389 25.17870
## 149 PUE 2014 14.44167 16.52222 18.55648 20.32407 21.01019 20.17778
## 150 QRO 2014 15.08148 17.29352 19.80093 22.11944 23.45833 22.03981
## 151 QROO 2014 23.86389 25.40926 26.00926 28.32500 29.17037 29.11667
## 152 SLP 2014 17.20463 19.42407 22.75648 25.78796 27.53611 27.20370
## 153 SIN 2014 19.67407 20.30926 22.27778 24.25093 26.93241 29.99259
## 154 SON 2014 14.58704 15.09722 18.13426 21.43519 24.27963 29.38241
## 155 TAB 2014 22.94907 24.76111 26.31111 28.92500 29.85185 28.91759
## 156 TAMPS 2014 17.10000 18.91481 22.86204 25.86296 28.32315 29.17315
## 157 TLAX 2014 11.61667 13.61574 15.55648 16.92778 17.62407 16.86019
## 158 VER 2014 18.36481 20.11759 22.30556 24.85370 26.25926 25.67963
## 159 YUC 2014 22.50370 24.52222 25.75648 28.68519 29.33148 28.73889
## 160 ZAC 2014 12.26019 14.44444 17.40556 19.18519 21.40000 21.83148
## 161 AGS 2015 12.47500 14.42500 17.31667 19.55000 21.71667 22.00000
## 162 BC 2015 14.15000 13.00833 15.42500 17.74167 19.80833 23.78333
## 163 BCS 2015 17.52500 17.77500 19.55000 21.39167 23.22500 25.72500
## 164 CAMP 2015 22.85833 24.69167 26.18333 29.19167 30.20000 29.00000
## 165 COAH 2015 12.58333 14.91667 19.73333 23.72500 26.86667 28.37500
## 166 COL 2015 23.87500 24.07500 24.52500 25.25000 26.97500 27.71667
## 167 CHIS 2015 22.16667 23.70000 24.67500 26.58333 27.18333 25.95000
## 168 CHIH 2015 10.09167 11.78333 15.85833 19.46667 22.63333 26.29167
## 169 CDMX 2015 14.20833 16.22500 18.19167 19.61667 20.84167 19.63333
## 170 DGO 2015 11.19167 12.99167 16.50000 19.27500 21.94167 23.99167
## 171 GTO 2015 14.30833 16.10833 18.86667 21.15000 22.97500 22.18333
## 172 GRO 2015 22.96667 24.08333 25.25833 26.53333 27.69167 26.46667
## 173 HGO 2015 14.17500 15.87500 17.96667 20.47500 21.65833 20.50833
## 174 JAL 2015 16.41667 18.09167 20.34167 22.01667 24.23333 24.27500
## 175 MEX 2015 10.91667 12.83333 14.87500 16.44167 17.79167 16.70833
## 176 MICH 2015 15.63333 16.95833 19.40000 22.37500 23.04167 22.18333
## 177 MOR 2015 18.29167 20.30833 23.15000 24.43333 25.33333 23.71667
## 178 NAY 2015 21.02500 21.82500 23.34167 24.80833 27.05000 28.66667
## 179 NL 2015 13.63333 15.90000 20.35000 23.47500 26.88333 27.96667
## 180 OAX 2015 20.85000 22.53333 24.10000 26.17500 27.32500 25.54167
## 181 PUE 2015 13.97500 15.90000 17.94167 19.98333 20.95833 20.00000
## 182 QRO 2015 14.66667 16.30833 18.74167 21.47500 23.12500 21.69167
## 183 QROO 2015 23.57500 24.81667 25.41667 28.12500 29.06667 28.85000
## 184 SLP 2015 16.70833 18.28333 22.14167 25.55833 27.42500 26.96667
## 185 SIN 2015 19.33333 19.71667 22.10000 23.99167 26.65833 29.66667
## 186 SON 2015 14.21667 14.67500 18.14167 21.18333 23.98333 29.10833
## 187 TAB 2015 22.40833 24.05000 25.60000 28.72500 29.73333 28.79167
## 188 TAMPS 2015 16.70000 17.96667 22.29167 25.83333 28.24167 29.09167
## 189 TLAX 2015 11.35000 13.20833 14.94167 16.75000 17.68333 16.80833
## 190 VER 2015 18.21667 19.59167 21.95000 25.01667 26.46667 25.78333
## 191 YUC 2015 22.26667 23.90000 25.14167 28.43333 29.31667 28.65000
## 192 ZAC 2015 11.80833 13.60000 16.65000 18.93333 21.40000 21.81667
## 193 AGS 2016 12.85000 15.15000 18.03333 19.70000 21.53333 21.80000
## 194 BC 2016 14.30000 13.56667 15.30000 18.48333 20.41667 24.01667
## 195 BCS 2016 17.95000 18.25000 19.75000 21.83333 23.50000 26.25000
## 196 CAMP 2016 23.21667 25.33333 26.81667 29.33333 30.10000 29.10000
## 197 COAH 2016 12.91667 15.73333 20.01667 23.35000 26.78333 28.40000
## 198 COL 2016 24.65000 24.70000 25.20000 25.45000 27.10000 28.13333
## 199 CHIS 2016 22.73333 24.20000 25.15000 26.76667 27.16667 26.00000
## 200 CHIH 2016 10.38333 12.51667 16.11667 19.48333 22.96667 26.38333
## 201 CDMX 2016 14.56667 16.80000 18.68333 19.78333 20.58333 19.56667
## 202 DGO 2016 11.63333 14.03333 17.25000 19.55000 22.03333 23.98333
## 203 GTO 2016 14.66667 16.76667 19.58333 21.40000 22.80000 21.91667
## 204 GRO 2016 23.28333 24.26667 25.61667 26.56667 27.38333 26.33333
## 205 HGO 2016 14.55000 16.65000 18.73333 20.80000 21.81667 20.76667
## 206 JAL 2016 16.88333 18.78333 20.93333 22.23333 24.16667 24.35000
## 207 MEX 2016 11.33333 13.36667 15.45000 16.63333 17.53333 16.76667
## 208 MICH 2016 16.46667 18.06667 20.45000 22.40000 23.18333 22.41667
## 209 MOR 2016 18.73333 20.91667 23.75000 24.76667 25.06667 23.63333
## 210 NAY 2016 21.50000 22.60000 23.73333 25.01667 27.15000 28.88333
## 211 NL 2016 14.01667 16.65000 20.75000 23.40000 26.51667 27.68333
## 212 OAX 2016 20.95000 22.76667 24.25000 25.90000 26.75000 25.13333
## 213 PUE 2016 14.50000 16.60000 18.63333 20.36667 21.01667 20.20000
## 214 QRO 2016 15.13333 17.41667 19.93333 22.20000 23.50000 22.08333
## 215 QROO 2016 23.90000 25.48333 26.08333 28.35000 29.18333 29.15000
## 216 SLP 2016 17.26667 19.56667 22.83333 25.81667 27.55000 27.23333
## 217 SIN 2016 19.71667 20.38333 22.30000 24.28333 26.96667 30.03333
## 218 SON 2016 14.63333 15.15000 18.13333 21.46667 24.31667 29.41667
## 219 TAB 2016 23.01667 24.85000 26.40000 28.95000 29.86667 28.93333
## 220 TAMPS 2016 17.15000 19.03333 22.93333 25.86667 28.33333 29.18333
## 221 TLAX 2016 11.65000 13.66667 15.63333 16.95000 17.61667 16.86667
## 222 VER 2016 18.38333 20.18333 22.35000 24.83333 26.23333 25.66667
## 223 YUC 2016 22.53333 24.60000 25.83333 28.71667 29.33333 28.75000
## 224 ZAC 2016 12.31667 14.55000 17.50000 19.21667 21.40000 21.83333
## 225 AGS 2017 12.85000 15.15000 18.03333 19.70000 21.53333 21.80000
## 226 BC 2017 14.30000 13.56667 15.30000 18.48333 20.41667 24.01667
## 227 BCS 2017 17.95000 18.25000 19.75000 21.83333 23.50000 26.25000
## 228 CAMP 2017 23.21667 25.33333 26.81667 29.33333 30.10000 29.10000
## 229 COAH 2017 12.91667 15.73333 20.01667 23.35000 26.78333 28.40000
## 230 COL 2017 24.65000 24.70000 25.20000 25.45000 27.10000 28.13333
## 231 CHIS 2017 22.73333 24.20000 25.15000 26.76667 27.16667 26.00000
## 232 CHIH 2017 10.38333 12.51667 16.11667 19.48333 22.96667 26.38333
## 233 CDMX 2017 14.56667 16.80000 18.68333 19.78333 20.58333 19.56667
## 234 DGO 2017 11.63333 14.03333 17.25000 19.55000 22.03333 23.98333
## 235 GTO 2017 14.66667 16.76667 19.58333 21.40000 22.80000 21.91667
## 236 GRO 2017 23.28333 24.26667 25.61667 26.56667 27.38333 26.33333
## 237 HGO 2017 14.55000 16.65000 18.73333 20.80000 21.81667 20.76667
## 238 JAL 2017 16.88333 18.78333 20.93333 22.23333 24.16667 24.35000
## 239 MEX 2017 11.33333 13.36667 15.45000 16.63333 17.53333 16.76667
## 240 MICH 2017 16.46667 18.06667 20.45000 22.40000 23.18333 22.41667
## 241 MOR 2017 18.73333 20.91667 23.75000 24.76667 25.06667 23.63333
## 242 NAY 2017 21.50000 22.60000 23.73333 25.01667 27.15000 28.88333
## 243 NL 2017 14.01667 16.65000 20.75000 23.40000 26.51667 27.68333
## 244 OAX 2017 20.95000 22.76667 24.25000 25.90000 26.75000 25.13333
## 245 PUE 2017 14.50000 16.60000 18.63333 20.36667 21.01667 20.20000
## 246 QRO 2017 15.13333 17.41667 19.93333 22.20000 23.50000 22.08333
## 247 QROO 2017 23.90000 25.48333 26.08333 28.35000 29.18333 29.15000
## 248 SLP 2017 17.26667 19.56667 22.83333 25.81667 27.55000 27.23333
## 249 SIN 2017 19.71667 20.38333 22.30000 24.28333 26.96667 30.03333
## 250 SON 2017 14.63333 15.15000 18.13333 21.46667 24.31667 29.41667
## 251 TAB 2017 23.01667 24.85000 26.40000 28.95000 29.86667 28.93333
## 252 TAMPS 2017 17.15000 19.03333 22.93333 25.86667 28.33333 29.18333
## 253 TLAX 2017 11.65000 13.66667 15.63333 16.95000 17.61667 16.86667
## 254 VER 2017 18.38333 20.18333 22.35000 24.83333 26.23333 25.66667
## 255 YUC 2017 22.53333 24.60000 25.83333 28.71667 29.33333 28.75000
## 256 ZAC 2017 12.31667 14.55000 17.50000 19.21667 21.40000 21.83333
## 257 AGS 2018 13.00000 16.70000 18.80000 19.90000 21.90000 21.30000
## 258 BC 2018 16.30000 15.50000 16.60000 20.40000 20.50000 24.30000
## 259 BCS 2018 19.70000 19.90000 20.70000 22.90000 24.80000 26.90000
## 260 CAMP 2018 22.30000 26.10000 27.50000 28.50000 28.90000 28.80000
## 261 COAH 2018 11.70000 18.00000 20.50000 22.20000 27.40000 29.40000
## 262 COL 2018 25.20000 26.20000 25.80000 25.80000 28.70000 28.40000
## 263 CHIS 2018 21.80000 24.70000 26.10000 26.50000 26.90000 25.80000
## 264 CHIH 2018 11.00000 14.80000 17.00000 20.40000 24.70000 26.70000
## 265 CDMX 2018 13.40000 17.00000 19.20000 19.30000 20.30000 19.60000
## 266 DGO 2018 12.10000 15.90000 18.80000 20.40000 23.40000 24.50000
## 267 GTO 2018 13.90000 17.40000 20.30000 21.30000 22.80000 21.40000
## 268 GRO 2018 22.90000 24.40000 25.70000 26.50000 27.10000 26.00000
## 269 HGO 2018 13.40000 16.70000 18.50000 19.50000 20.40000 20.70000
## 270 JAL 2018 16.80000 19.50000 21.10000 22.40000 24.80000 23.80000
## 271 MEX 2018 10.50000 13.80000 15.50000 16.00000 16.90000 16.70000
## 272 MICH 2018 16.50000 19.20000 21.80000 22.90000 24.10000 22.70000
## 273 MOR 2018 18.40000 22.10000 24.60000 25.00000 24.00000 23.20000
## 274 NAY 2018 21.70000 24.70000 24.60000 25.40000 28.60000 29.30000
## 275 NL 2018 12.30000 18.60000 21.50000 21.90000 26.10000 27.80000
## 276 OAX 2018 20.20000 23.10000 24.90000 24.90000 26.60000 24.10000
## 277 PUE 2018 13.10000 17.00000 19.10000 19.30000 20.10000 20.40000
## 278 QRO 2018 13.50000 18.50000 21.00000 22.30000 23.70000 22.00000
## 279 QROO 2018 23.10000 26.40000 26.70000 28.00000 28.50000 29.20000
## 280 SLP 2018 15.50000 21.90000 23.70000 24.10000 26.80000 27.40000
## 281 SIN 2018 20.90000 22.40000 23.00000 25.10000 28.20000 30.40000
## 282 SON 2018 16.70000 16.40000 19.20000 22.70000 25.40000 30.00000
## 283 TAB 2018 22.10000 25.80000 27.50000 28.30000 29.30000 29.00000
## 284 TAMPS 2018 15.10000 22.00000 23.90000 24.50000 28.00000 29.30000
## 285 TLAX 2018 11.10000 14.40000 16.40000 16.40000 17.60000 17.00000
## 286 VER 2018 16.90000 21.30000 22.80000 23.00000 25.10000 25.70000
## 287 YUC 2018 21.70000 25.50000 26.30000 27.70000 28.10000 28.20000
## 288 ZAC 2018 12.50000 15.80000 18.10000 19.30000 21.90000 21.00000
## 289 AGS 2019 14.00000 16.90000 19.00000 19.60000 22.30000 23.20000
## 290 BC 2019 14.30000 12.20000 15.60000 20.40000 20.40000 24.10000
## 291 BCS 2019 18.70000 18.40000 20.30000 22.50000 22.60000 26.50000
## 292 CAMP 2019 23.30000 26.60000 26.90000 28.70000 31.10000 29.90000
## 293 COAH 2019 13.50000 17.10000 18.80000 22.80000 26.40000 28.30000
## 294 COL 2019 25.90000 25.50000 26.20000 25.40000 26.70000 29.30000
## 295 CHIS 2019 23.00000 24.80000 25.40000 26.50000 27.70000 26.60000
## 296 CHIH 2019 11.00000 12.80000 16.40000 18.90000 22.00000 26.30000
## 297 CDMX 2019 15.40000 18.10000 19.20000 20.20000 21.40000 20.10000
## 298 DGO 2019 12.60000 15.60000 17.60000 19.00000 20.90000 24.50000
## 299 GTO 2019 15.50000 18.00000 20.20000 20.90000 23.40000 22.60000
## 300 GRO 2019 23.30000 24.60000 25.90000 25.90000 26.70000 26.50000
## 301 HGO 2019 15.40000 19.00000 19.50000 21.40000 23.70000 22.00000
## 302 JAL 2019 17.30000 19.60000 21.40000 21.80000 24.20000 25.40000
## 303 MEX 2019 12.30000 14.60000 16.10000 16.80000 18.30000 17.70000
## 304 MICH 2019 17.50000 19.90000 21.50000 21.80000 23.90000 23.50000
## 305 MOR 2019 19.20000 21.90000 24.40000 24.60000 25.40000 23.60000
## 306 NAY 2019 22.90000 23.60000 24.40000 25.30000 26.70000 29.90000
## 307 NL 2019 14.20000 18.20000 19.40000 22.70000 26.50000 28.20000
## 308 OAX 2019 21.40000 24.30000 24.40000 25.60000 26.70000 25.80000
## 309 PUE 2019 15.20000 18.10000 18.90000 20.40000 22.10000 20.80000
## 310 QRO 2019 16.60000 19.20000 20.80000 22.30000 25.00000 23.20000
## 311 QROO 2019 23.90000 26.70000 27.00000 28.20000 30.10000 30.60000
## 312 SLP 2019 18.40000 21.80000 22.20000 25.50000 29.20000 28.50000
## 313 SIN 2019 20.40000 20.80000 22.70000 24.20000 26.00000 30.00000
## 314 SON 2019 14.60000 14.40000 18.50000 21.40000 22.50000 28.70000
## 315 TAB 2019 23.50000 26.00000 26.40000 28.10000 31.30000 29.80000
## 316 TAMPS 2019 17.40000 21.00000 22.20000 25.10000 29.30000 30.40000
## 317 TLAX 2019 12.30000 14.90000 16.40000 17.40000 18.60000 17.80000
## 318 VER 2019 18.90000 21.90000 22.00000 23.80000 27.20000 26.20000
## 319 YUC 2019 22.50000 25.90000 26.30000 28.30000 30.40000 30.20000
## 320 ZAC 2019 13.10000 16.00000 18.00000 18.50000 21.10000 22.60000
## 321 AGS 2020 13.00000 15.00000 19.30000 20.50000 20.70000 22.10000
## 322 BC 2020 13.60000 14.40000 14.40000 18.10000 22.70000 24.20000
## 323 BCS 2020 17.80000 18.40000 19.80000 21.80000 23.90000 26.80000
## 324 CAMP 2020 24.60000 26.00000 28.00000 31.10000 30.20000 28.90000
## 325 COAH 2020 14.30000 15.60000 22.10000 23.90000 26.80000 27.90000
## 326 COL 2020 25.80000 25.40000 26.60000 25.90000 26.30000 28.30000
## 327 CHIS 2020 24.50000 25.30000 25.60000 27.80000 27.30000 25.80000
## 328 CHIH 2020 10.80000 12.00000 16.70000 19.40000 23.70000 26.40000
## 329 CDMX 2020 15.60000 18.10000 19.40000 20.70000 19.90000 19.80000
## 330 DGO 2020 11.80000 13.80000 18.40000 20.20000 22.20000 23.70000
## 331 GTO 2020 15.20000 17.30000 20.60000 22.80000 22.20000 22.10000
## 332 GRO 2020 24.20000 24.80000 26.20000 27.10000 27.00000 26.90000
## 333 HGO 2020 15.50000 17.10000 20.50000 22.80000 22.10000 21.20000
## 334 JAL 2020 17.80000 19.50000 22.40000 22.80000 23.50000 24.90000
## 335 MEX 2020 11.80000 14.00000 16.30000 17.60000 16.80000 16.80000
## 336 MICH 2020 17.70000 19.50000 21.70000 23.20000 23.00000 22.90000
## 337 MOR 2020 19.40000 21.40000 24.70000 26.00000 25.30000 24.80000
## 338 NAY 2020 22.60000 22.80000 24.70000 24.80000 26.60000 29.10000
## 339 NL 2020 16.20000 16.50000 22.90000 24.60000 26.00000 26.70000
## 340 OAX 2020 21.80000 22.70000 24.60000 26.70000 25.80000 25.00000
## 341 PUE 2020 15.80000 17.30000 20.00000 22.40000 21.40000 20.90000
## 342 QRO 2020 15.80000 18.70000 22.00000 24.10000 23.80000 22.90000
## 343 QROO 2020 25.30000 26.00000 26.80000 29.60000 29.30000 29.00000
## 344 SLP 2020 18.80000 20.00000 24.60000 28.20000 27.60000 27.90000
## 345 SIN 2020 19.90000 20.50000 22.90000 24.40000 27.30000 30.60000
## 346 SON 2020 14.70000 15.70000 17.70000 21.00000 25.80000 29.80000
## 347 TAB 2020 24.70000 25.80000 27.60000 30.80000 30.00000 28.70000
## 348 TAMPS 2020 19.50000 19.10000 25.20000 27.70000 28.20000 28.70000
## 349 TLAX 2020 11.80000 14.20000 16.30000 18.00000 17.10000 16.90000
## 350 VER 2020 19.40000 20.00000 23.70000 26.90000 25.90000 25.20000
## 351 YUC 2020 23.70000 25.10000 26.90000 30.90000 29.40000 28.40000
## 352 ZAC 2020 12.70000 14.70000 19.10000 20.30000 21.00000 22.60000
## 353 AGS 2021 12.90000 14.90000 17.90000 19.40000 20.50000 19.80000
## 354 BC 2021 13.60000 14.40000 14.10000 18.00000 20.50000 24.40000
## 355 BCS 2021 17.30000 18.20000 19.00000 21.90000 23.80000 26.90000
## 356 CAMP 2021 24.10000 25.20000 27.40000 29.60000 29.80000 29.20000
## 357 COAH 2021 13.50000 15.50000 19.80000 23.00000 26.20000 28.10000
## 358 COL 2021 24.80000 24.20000 24.90000 25.50000 27.20000 28.20000
## 359 CHIS 2021 23.90000 24.00000 25.40000 27.00000 26.70000 26.00000
## 360 CHIH 2021 9.90000 13.40000 15.40000 19.30000 22.80000 26.50000
## 361 CDMX 2021 15.30000 16.30000 18.90000 19.60000 19.70000 18.50000
## 362 DGO 2021 11.80000 15.00000 17.20000 19.70000 22.00000 23.20000
## 363 GTO 2021 15.50000 17.00000 20.10000 21.60000 22.10000 20.50000
## 364 GRO 2021 24.00000 24.00000 26.10000 26.90000 27.50000 25.40000
## 365 HGO 2021 15.40000 16.90000 19.50000 20.80000 21.70000 20.20000
## 366 JAL 2021 17.50000 19.30000 21.20000 22.80000 23.90000 23.60000
## 367 MEX 2021 12.40000 13.20000 16.20000 16.90000 17.10000 16.10000
## 368 MICH 2021 17.50000 18.10000 21.00000 21.80000 22.30000 21.50000
## 369 MOR 2021 19.70000 20.70000 23.70000 24.80000 24.50000 22.60000
## 370 NAY 2021 20.70000 22.40000 22.80000 25.40000 27.10000 28.10000
## 371 NL 2021 14.90000 16.30000 20.80000 24.10000 26.00000 26.90000
## 372 OAX 2021 20.80000 21.90000 23.70000 25.30000 25.60000 24.00000
## 373 PUE 2021 16.00000 16.80000 19.30000 20.90000 20.70000 19.50000
## 374 QRO 2021 16.50000 17.70000 20.70000 23.00000 23.00000 21.80000
## 375 QROO 2021 24.60000 25.50000 26.50000 28.50000 29.30000 29.00000
## 376 SLP 2021 18.60000 19.70000 23.60000 26.50000 27.10000 26.20000
## 377 SIN 2021 19.20000 20.50000 21.40000 24.60000 27.60000 30.60000
## 378 SON 2021 14.20000 16.00000 17.10000 21.90000 24.90000 30.40000
## 379 TAB 2021 24.20000 25.00000 27.30000 29.50000 29.40000 28.80000
## 380 TAMPS 2021 18.40000 18.30000 23.00000 26.30000 28.20000 28.70000
## 381 TLAX 2021 12.60000 13.00000 16.20000 16.80000 16.90000 16.00000
## 382 VER 2021 19.00000 19.90000 22.50000 24.90000 25.80000 25.10000
## 383 YUC 2021 23.30000 24.70000 26.60000 29.10000 29.50000 28.60000
## 384 ZAC 2021 13.00000 15.50000 18.20000 19.90000 21.60000 21.20000Significa hacer un filtro a nivel de registro u opservaciones. El filtro o subconjunto de datos se hace con una expresión booleana que el resultado sea verdadero entonces se aplica el filtro.
estado <- filter(datos.temperaturas, abreviatura == 'COAH')
estado## X abreviatura entidad ene feb mar abr may
## 1 5 COAH COAHUILA 11.50000 12.40000 17.10000 22.30000 26.40000
## 2 37 COAH COAHUILA 13.00000 15.80000 21.80000 25.90000 27.50000
## 3 69 COAH COAHUILA 14.60000 15.50000 20.70000 24.30000 26.50000
## 4 101 COAH Coahuila 13.03603 15.62963 20.05017 23.47424 26.76599
## 5 133 COAH Coahuila 12.87963 15.64259 19.98519 23.39167 26.79259
## 6 165 COAH Coahuila 12.58333 14.91667 19.73333 23.72500 26.86667
## 7 197 COAH Coahuila 12.91667 15.73333 20.01667 23.35000 26.78333
## 8 229 COAH Coahuila 12.91667 15.73333 20.01667 23.35000 26.78333
## 9 261 COAH Coahuila 11.70000 18.00000 20.50000 22.20000 27.40000
## 10 293 COAH Coahuila 13.50000 17.10000 18.80000 22.80000 26.40000
## 11 325 COAH Coahuila 14.30000 15.60000 22.10000 23.90000 26.80000
## 12 357 COAH Coahuila 13.50000 15.50000 19.80000 23.00000 26.20000
## jun jul ago sep oct nov dic anual agnio
## 1 28.50000 26.20000 28.00000 22.20000 22.00000 17.40000 13.90000 20.7 2010
## 2 28.20000 28.80000 29.10000 26.90000 22.70000 17.80000 12.90000 22.5 2011
## 3 26.50000 28.30000 29.50000 26.10000 23.20000 18.50000 15.70000 22.4 2012
## 4 28.22475 28.15943 28.82239 25.36347 22.39281 17.63938 13.86625 NA 2013
## 5 28.39722 28.14537 28.75463 25.28981 22.30313 17.54375 13.66250 NA 2014
## 6 28.37500 27.84167 28.65833 24.94167 22.32500 17.57000 13.54000 NA 2015
## 7 28.40000 28.18333 28.76667 25.33333 22.30000 17.54000 13.68000 NA 2016
## 8 28.40000 28.18333 28.76667 25.33333 22.30000 17.54000 13.68000 NA 2017
## 9 29.40000 28.70000 28.70000 24.70000 21.50000 15.50000 13.60000 21.8 2018
## 10 28.30000 28.70000 30.50000 27.40000 22.80000 17.60000 14.70000 22.4 2019
## 11 27.90000 29.20000 28.50000 24.20000 22.50000 19.40000 13.30000 22.3 2020
## 12 28.10000 27.50000 27.80000 26.60000 NA NA NA NA 2021En R el símbolo de %>% usando la librería dplyr significa que el resultado de una expresión es la entrada de otra expresión
estado <- filter(datos.temperaturas, abreviatura == 'YUC' ) %>%
select(abreviatura, agnio, ene, feb, mar, abr, may, jun)
estado## abreviatura agnio ene feb mar abr may jun
## 1 YUC 2010 21.60000 22.30000 22.90000 27.50000 28.90000 29.40000
## 2 YUC 2011 22.40000 24.10000 26.00000 28.80000 29.70000 27.70000
## 3 YUC 2012 22.80000 24.30000 26.00000 26.80000 28.40000 27.60000
## 4 YUC 2013 22.53064 24.50202 25.77862 28.51380 29.24680 28.63535
## 5 YUC 2014 22.50370 24.52222 25.75648 28.68519 29.33148 28.73889
## 6 YUC 2015 22.26667 23.90000 25.14167 28.43333 29.31667 28.65000
## 7 YUC 2016 22.53333 24.60000 25.83333 28.71667 29.33333 28.75000
## 8 YUC 2017 22.53333 24.60000 25.83333 28.71667 29.33333 28.75000
## 9 YUC 2018 21.70000 25.50000 26.30000 27.70000 28.10000 28.20000
## 10 YUC 2019 22.50000 25.90000 26.30000 28.30000 30.40000 30.20000
## 11 YUC 2020 23.70000 25.10000 26.90000 30.90000 29.40000 28.40000
## 12 YUC 2021 23.30000 24.70000 26.60000 29.10000 29.50000 28.60000estados.frontera <- c('BC', 'SON', 'CHIH', 'COAH', 'NL', 'TAMPS')
estado <- filter(datos.temperaturas, abreviatura %in% estados.frontera ) %>%
select(abreviatura, agnio, ene, feb, mar, abr, may, jun)
#estado <- filter(datos.temperaturas, abreviatura == 'BC' | abreviatura == 'SON' | abreviatura == 'CHIH' | abreviatura == 'COAH' | abreviatura == 'NL' | abreviatura == 'TAMPS') %>%
# select(abreviatura, agnio, ene, feb, mar, abr, may, jun)arrange(estado, abreviatura, desc(agnio))## abreviatura agnio ene feb mar abr may jun
## 1 BC 2021 13.60000 14.40000 14.10000 18.00000 20.50000 24.40000
## 2 BC 2020 13.60000 14.40000 14.40000 18.10000 22.70000 24.20000
## 3 BC 2019 14.30000 12.20000 15.60000 20.40000 20.40000 24.10000
## 4 BC 2018 16.30000 15.50000 16.60000 20.40000 20.50000 24.30000
## 5 BC 2017 14.30000 13.56667 15.30000 18.48333 20.41667 24.01667
## 6 BC 2016 14.30000 13.56667 15.30000 18.48333 20.41667 24.01667
## 7 BC 2015 14.15000 13.00833 15.42500 17.74167 19.80833 23.78333
## 8 BC 2014 14.28333 13.50463 15.31389 18.40093 20.34907 23.99074
## 9 BC 2013 14.40303 13.49512 15.20354 18.32811 20.49916 23.98249
## 10 BC 2012 15.60000 13.40000 14.10000 17.60000 22.00000 23.90000
## 11 BC 2011 14.10000 11.10000 16.30000 18.10000 19.60000 23.70000
## 12 BC 2010 13.90000 13.80000 14.80000 15.90000 18.80000 23.40000
## 13 CHIH 2021 9.90000 13.40000 15.40000 19.30000 22.80000 26.50000
## 14 CHIH 2020 10.80000 12.00000 16.70000 19.40000 23.70000 26.40000
## 15 CHIH 2019 11.00000 12.80000 16.40000 18.90000 22.00000 26.30000
## 16 CHIH 2018 11.00000 14.80000 17.00000 20.40000 24.70000 26.70000
## 17 CHIH 2017 10.38333 12.51667 16.11667 19.48333 22.96667 26.38333
## 18 CHIH 2016 10.38333 12.51667 16.11667 19.48333 22.96667 26.38333
## 19 CHIH 2015 10.09167 11.78333 15.85833 19.46667 22.63333 26.29167
## 20 CHIH 2014 10.35093 12.43519 16.08796 19.48148 22.92963 26.37315
## 21 CHIH 2013 10.42811 12.42290 16.01633 19.99226 22.96330 26.38468
## 22 CHIH 2012 11.20000 12.30000 15.30000 25.10000 23.30000 26.50000
## 23 CHIH 2011 10.50000 12.00000 17.80000 20.80000 23.00000 26.70000
## 24 CHIH 2010 9.10000 10.10000 13.40000 18.10000 21.60000 25.70000
## 25 COAH 2021 13.50000 15.50000 19.80000 23.00000 26.20000 28.10000
## 26 COAH 2020 14.30000 15.60000 22.10000 23.90000 26.80000 27.90000
## 27 COAH 2019 13.50000 17.10000 18.80000 22.80000 26.40000 28.30000
## 28 COAH 2018 11.70000 18.00000 20.50000 22.20000 27.40000 29.40000
## 29 COAH 2017 12.91667 15.73333 20.01667 23.35000 26.78333 28.40000
## 30 COAH 2016 12.91667 15.73333 20.01667 23.35000 26.78333 28.40000
## 31 COAH 2015 12.58333 14.91667 19.73333 23.72500 26.86667 28.37500
## 32 COAH 2014 12.87963 15.64259 19.98519 23.39167 26.79259 28.39722
## 33 COAH 2013 13.03603 15.62963 20.05017 23.47424 26.76599 28.22475
## 34 COAH 2012 14.60000 15.50000 20.70000 24.30000 26.50000 26.50000
## 35 COAH 2011 13.00000 15.80000 21.80000 25.90000 27.50000 28.20000
## 36 COAH 2010 11.50000 12.40000 17.10000 22.30000 26.40000 28.50000
## 37 NL 2021 14.90000 16.30000 20.80000 24.10000 26.00000 26.90000
## 38 NL 2020 16.20000 16.50000 22.90000 24.60000 26.00000 26.70000
## 39 NL 2019 14.20000 18.20000 19.40000 22.70000 26.50000 28.20000
## 40 NL 2018 12.30000 18.60000 21.50000 21.90000 26.10000 27.80000
## 41 NL 2017 14.01667 16.65000 20.75000 23.40000 26.51667 27.68333
## 42 NL 2016 14.01667 16.65000 20.75000 23.40000 26.51667 27.68333
## 43 NL 2015 13.63333 15.90000 20.35000 23.47500 26.88333 27.96667
## 44 NL 2014 13.97407 16.56667 20.70556 23.40833 26.55741 27.71481
## 45 NL 2013 14.14007 16.53333 20.72323 23.49848 26.53401 27.71347
## 46 NL 2012 15.80000 16.20000 20.90000 24.40000 26.30000 27.70000
## 47 NL 2011 14.00000 17.00000 22.30000 24.70000 28.10000 27.90000
## 48 NL 2010 12.50000 13.30000 17.60000 22.40000 26.40000 28.60000
## 49 SON 2021 14.20000 16.00000 17.10000 21.90000 24.90000 30.40000
## 50 SON 2020 14.70000 15.70000 17.70000 21.00000 25.80000 29.80000
## 51 SON 2019 14.60000 14.40000 18.50000 21.40000 22.50000 28.70000
## 52 SON 2018 16.70000 16.40000 19.20000 22.70000 25.40000 30.00000
## 53 SON 2017 14.63333 15.15000 18.13333 21.46667 24.31667 29.41667
## 54 SON 2016 14.63333 15.15000 18.13333 21.46667 24.31667 29.41667
## 55 SON 2015 14.21667 14.67500 18.14167 21.18333 23.98333 29.10833
## 56 SON 2014 14.58704 15.09722 18.13426 21.43519 24.27963 29.38241
## 57 SON 2013 14.64276 15.07020 18.04024 21.45926 24.43603 29.41128
## 58 SON 2012 15.20000 14.80000 17.10000 21.70000 26.00000 29.70000
## 59 SON 2011 13.90000 14.00000 19.50000 21.80000 23.90000 28.90000
## 60 SON 2010 13.70000 14.40000 16.80000 20.00000 23.40000 28.70000
## 61 TAMPS 2021 18.40000 18.30000 23.00000 26.30000 28.20000 28.70000
## 62 TAMPS 2020 19.50000 19.10000 25.20000 27.70000 28.20000 28.70000
## 63 TAMPS 2019 17.40000 21.00000 22.20000 25.10000 29.30000 30.40000
## 64 TAMPS 2018 15.10000 22.00000 23.90000 24.50000 28.00000 29.30000
## 65 TAMPS 2017 17.15000 19.03333 22.93333 25.86667 28.33333 29.18333
## 66 TAMPS 2016 17.15000 19.03333 22.93333 25.86667 28.33333 29.18333
## 67 TAMPS 2015 16.70000 17.96667 22.29167 25.83333 28.24167 29.09167
## 68 TAMPS 2014 17.10000 18.91481 22.86204 25.86296 28.32315 29.17315
## 69 TAMPS 2013 17.20909 18.89529 22.86549 25.85724 28.28468 29.16650
## 70 TAMPS 2012 18.30000 18.70000 22.90000 25.80000 27.90000 29.10000
## 71 TAMPS 2011 17.00000 18.20000 23.80000 27.40000 28.60000 28.60000
## 72 TAMPS 2010 15.50000 15.60000 19.50000 24.20000 27.70000 29.40000Con la función mutate se agregan columnas o modifica valores de variables en el conjunto de datos
estado.modificado <- mutate(estado, abrev.minusc = tolower(abreviatura))
estado.modificado## abreviatura agnio ene feb mar abr may jun
## 1 BC 2010 13.90000 13.80000 14.80000 15.90000 18.80000 23.40000
## 2 COAH 2010 11.50000 12.40000 17.10000 22.30000 26.40000 28.50000
## 3 CHIH 2010 9.10000 10.10000 13.40000 18.10000 21.60000 25.70000
## 4 NL 2010 12.50000 13.30000 17.60000 22.40000 26.40000 28.60000
## 5 SON 2010 13.70000 14.40000 16.80000 20.00000 23.40000 28.70000
## 6 TAMPS 2010 15.50000 15.60000 19.50000 24.20000 27.70000 29.40000
## 7 BC 2011 14.10000 11.10000 16.30000 18.10000 19.60000 23.70000
## 8 COAH 2011 13.00000 15.80000 21.80000 25.90000 27.50000 28.20000
## 9 CHIH 2011 10.50000 12.00000 17.80000 20.80000 23.00000 26.70000
## 10 NL 2011 14.00000 17.00000 22.30000 24.70000 28.10000 27.90000
## 11 SON 2011 13.90000 14.00000 19.50000 21.80000 23.90000 28.90000
## 12 TAMPS 2011 17.00000 18.20000 23.80000 27.40000 28.60000 28.60000
## 13 BC 2012 15.60000 13.40000 14.10000 17.60000 22.00000 23.90000
## 14 COAH 2012 14.60000 15.50000 20.70000 24.30000 26.50000 26.50000
## 15 CHIH 2012 11.20000 12.30000 15.30000 25.10000 23.30000 26.50000
## 16 NL 2012 15.80000 16.20000 20.90000 24.40000 26.30000 27.70000
## 17 SON 2012 15.20000 14.80000 17.10000 21.70000 26.00000 29.70000
## 18 TAMPS 2012 18.30000 18.70000 22.90000 25.80000 27.90000 29.10000
## 19 BC 2013 14.40303 13.49512 15.20354 18.32811 20.49916 23.98249
## 20 COAH 2013 13.03603 15.62963 20.05017 23.47424 26.76599 28.22475
## 21 CHIH 2013 10.42811 12.42290 16.01633 19.99226 22.96330 26.38468
## 22 NL 2013 14.14007 16.53333 20.72323 23.49848 26.53401 27.71347
## 23 SON 2013 14.64276 15.07020 18.04024 21.45926 24.43603 29.41128
## 24 TAMPS 2013 17.20909 18.89529 22.86549 25.85724 28.28468 29.16650
## 25 BC 2014 14.28333 13.50463 15.31389 18.40093 20.34907 23.99074
## 26 COAH 2014 12.87963 15.64259 19.98519 23.39167 26.79259 28.39722
## 27 CHIH 2014 10.35093 12.43519 16.08796 19.48148 22.92963 26.37315
## 28 NL 2014 13.97407 16.56667 20.70556 23.40833 26.55741 27.71481
## 29 SON 2014 14.58704 15.09722 18.13426 21.43519 24.27963 29.38241
## 30 TAMPS 2014 17.10000 18.91481 22.86204 25.86296 28.32315 29.17315
## 31 BC 2015 14.15000 13.00833 15.42500 17.74167 19.80833 23.78333
## 32 COAH 2015 12.58333 14.91667 19.73333 23.72500 26.86667 28.37500
## 33 CHIH 2015 10.09167 11.78333 15.85833 19.46667 22.63333 26.29167
## 34 NL 2015 13.63333 15.90000 20.35000 23.47500 26.88333 27.96667
## 35 SON 2015 14.21667 14.67500 18.14167 21.18333 23.98333 29.10833
## 36 TAMPS 2015 16.70000 17.96667 22.29167 25.83333 28.24167 29.09167
## 37 BC 2016 14.30000 13.56667 15.30000 18.48333 20.41667 24.01667
## 38 COAH 2016 12.91667 15.73333 20.01667 23.35000 26.78333 28.40000
## 39 CHIH 2016 10.38333 12.51667 16.11667 19.48333 22.96667 26.38333
## 40 NL 2016 14.01667 16.65000 20.75000 23.40000 26.51667 27.68333
## 41 SON 2016 14.63333 15.15000 18.13333 21.46667 24.31667 29.41667
## 42 TAMPS 2016 17.15000 19.03333 22.93333 25.86667 28.33333 29.18333
## 43 BC 2017 14.30000 13.56667 15.30000 18.48333 20.41667 24.01667
## 44 COAH 2017 12.91667 15.73333 20.01667 23.35000 26.78333 28.40000
## 45 CHIH 2017 10.38333 12.51667 16.11667 19.48333 22.96667 26.38333
## 46 NL 2017 14.01667 16.65000 20.75000 23.40000 26.51667 27.68333
## 47 SON 2017 14.63333 15.15000 18.13333 21.46667 24.31667 29.41667
## 48 TAMPS 2017 17.15000 19.03333 22.93333 25.86667 28.33333 29.18333
## 49 BC 2018 16.30000 15.50000 16.60000 20.40000 20.50000 24.30000
## 50 COAH 2018 11.70000 18.00000 20.50000 22.20000 27.40000 29.40000
## 51 CHIH 2018 11.00000 14.80000 17.00000 20.40000 24.70000 26.70000
## 52 NL 2018 12.30000 18.60000 21.50000 21.90000 26.10000 27.80000
## 53 SON 2018 16.70000 16.40000 19.20000 22.70000 25.40000 30.00000
## 54 TAMPS 2018 15.10000 22.00000 23.90000 24.50000 28.00000 29.30000
## 55 BC 2019 14.30000 12.20000 15.60000 20.40000 20.40000 24.10000
## 56 COAH 2019 13.50000 17.10000 18.80000 22.80000 26.40000 28.30000
## 57 CHIH 2019 11.00000 12.80000 16.40000 18.90000 22.00000 26.30000
## 58 NL 2019 14.20000 18.20000 19.40000 22.70000 26.50000 28.20000
## 59 SON 2019 14.60000 14.40000 18.50000 21.40000 22.50000 28.70000
## 60 TAMPS 2019 17.40000 21.00000 22.20000 25.10000 29.30000 30.40000
## 61 BC 2020 13.60000 14.40000 14.40000 18.10000 22.70000 24.20000
## 62 COAH 2020 14.30000 15.60000 22.10000 23.90000 26.80000 27.90000
## 63 CHIH 2020 10.80000 12.00000 16.70000 19.40000 23.70000 26.40000
## 64 NL 2020 16.20000 16.50000 22.90000 24.60000 26.00000 26.70000
## 65 SON 2020 14.70000 15.70000 17.70000 21.00000 25.80000 29.80000
## 66 TAMPS 2020 19.50000 19.10000 25.20000 27.70000 28.20000 28.70000
## 67 BC 2021 13.60000 14.40000 14.10000 18.00000 20.50000 24.40000
## 68 COAH 2021 13.50000 15.50000 19.80000 23.00000 26.20000 28.10000
## 69 CHIH 2021 9.90000 13.40000 15.40000 19.30000 22.80000 26.50000
## 70 NL 2021 14.90000 16.30000 20.80000 24.10000 26.00000 26.90000
## 71 SON 2021 14.20000 16.00000 17.10000 21.90000 24.90000 30.40000
## 72 TAMPS 2021 18.40000 18.30000 23.00000 26.30000 28.20000 28.70000
## abrev.minusc
## 1 bc
## 2 coah
## 3 chih
## 4 nl
## 5 son
## 6 tamps
## 7 bc
## 8 coah
## 9 chih
## 10 nl
## 11 son
## 12 tamps
## 13 bc
## 14 coah
## 15 chih
## 16 nl
## 17 son
## 18 tamps
## 19 bc
## 20 coah
## 21 chih
## 22 nl
## 23 son
## 24 tamps
## 25 bc
## 26 coah
## 27 chih
## 28 nl
## 29 son
## 30 tamps
## 31 bc
## 32 coah
## 33 chih
## 34 nl
## 35 son
## 36 tamps
## 37 bc
## 38 coah
## 39 chih
## 40 nl
## 41 son
## 42 tamps
## 43 bc
## 44 coah
## 45 chih
## 46 nl
## 47 son
## 48 tamps
## 49 bc
## 50 coah
## 51 chih
## 52 nl
## 53 son
## 54 tamps
## 55 bc
## 56 coah
## 57 chih
## 58 nl
## 59 son
## 60 tamps
## 61 bc
## 62 coah
## 63 chih
## 64 nl
## 65 son
## 66 tamps
## 67 bc
## 68 coah
## 69 chih
## 70 nl
## 71 son
## 72 tampsAgrupar datos y calcular alguna función mean(), n() o sd()
group_by summarize()
estado %>%
summarise(media.ene = mean(ene), n = n())## media.ene n
## 1 13.97652 72Ahora agrupados por estado
estado %>%
group_by(abreviatura) %>%
summarise(media.ene = mean(ene), n = n())## # A tibble: 6 x 3
## abreviatura media.ene n
## <fct> <dbl> <int>
## 1 BC 14.4 12
## 2 CHIH 10.4 12
## 3 COAH 13.0 12
## 4 NL 14.1 12
## 5 SON 14.6 12
## 6 TAMPS 17.2 12personas <- read.csv("https://raw.githubusercontent.com/rpizarrog/CIIT.-Diplomado-en-Ciencia-de-los-Datos-e-IoT/main/M%C3%B3dulo%20I/datos/datos.personas.csv", encoding = "1859-1", stringsAsFactors =TRUE)summary(personas)## X edad genero estado
## Min. : 1 Min. :18.0 FEMENINO :5215 DURANGO :1278
## 1st Qu.: 2501 1st Qu.:30.0 MASCULINO:4785 NUEVO LEÓN :1276
## Median : 5000 Median :41.0 CHIHUAHUA :1271
## Mean : 5000 Mean :41.5 COAHUILA :1267
## 3rd Qu.: 7500 3rd Qu.:53.0 BAJA CALIFORNIA:1257
## Max. :10000 Max. :65.0 TAMAULIPAS :1251
## (Other) :2400
## feliz
## FELIZ :4950
## NO FELIZ:5050
##
##
##
##
## str(personas)## 'data.frame': 10000 obs. of 5 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ edad : int 21 18 30 23 47 38 63 56 30 54 ...
## $ genero: Factor w/ 2 levels "FEMENINO","MASCULINO": 1 1 1 1 2 1 1 2 1 2 ...
## $ estado: Factor w/ 8 levels "BAJA CALIFORNIA",..: 1 6 8 6 8 5 2 1 4 3 ...
## $ feliz : Factor w/ 2 levels "FELIZ","NO FELIZ": 2 2 1 2 1 2 1 1 2 1 ...head(personas)## X edad genero estado feliz
## 1 1 21 FEMENINO BAJA CALIFORNIA NO FELIZ
## 2 2 18 FEMENINO NUEVO LEÓN NO FELIZ
## 3 3 30 FEMENINO TAMAULIPAS FELIZ
## 4 4 23 FEMENINO NUEVO LEÓN NO FELIZ
## 5 5 47 MASCULINO TAMAULIPAS FELIZ
## 6 6 38 FEMENINO DURANGO NO FELIZtail(personas)## X edad genero estado feliz
## 9995 9995 28 FEMENINO BAJA CALIFORNIA FELIZ
## 9996 9996 58 MASCULINO BAJA CALIFORNIA NO FELIZ
## 9997 9997 44 FEMENINO SONORA FELIZ
## 9998 9998 23 FEMENINO COAHUILA NO FELIZ
## 9999 9999 23 FEMENINO SONORA NO FELIZ
## 10000 10000 39 MASCULINO NUEVO LEÓN FELIZ¿Cuáles y cuántas personas son del genero FEMENINO del estado de BAJA CALIFORNIA que sean FELIZ?
Se utiliza operador and &
filtro <- filter(personas, genero == 'FEMENINO' & estado == 'BAJA CALIFORNIA' & feliz =='FELIZ' ) %>%
select(genero, estado, feliz)
summary(filtro)## genero estado feliz
## FEMENINO :320 BAJA CALIFORNIA :320 FELIZ :320
## MASCULINO: 0 BAJA CALIFORNIA SUR: 0 NO FELIZ: 0
## CHIHUAHUA : 0
## COAHUILA : 0
## DURANGO : 0
## NUEVO LEÓN : 0
## (Other) : 0