Change in Household Income between 2007-11 and 2012-16
Daniel Lee
March 29, 2018
Import and get a sense of data
# Import data
data <- read.csv("data/census2.csv")
str(data)
## 'data.frame': 64 obs. of 56 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ Town : Factor w/ 32 levels "Alexandria","Alton",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ County : Factor w/ 6 levels " Belknap"," Carroll",..: 3 1 4 3 1 1 3 3 1 4 ...
## $ popTotal : int 1836 5214 2422 1507 4564 7350 1179 3063 960 1120 ...
## $ medianAge : num 39.2 44.6 47.3 39.6 38.4 41.1 47.7 47.1 49.2 40.5 ...
## $ popNative_bornUSA : int 1783 5023 2339 1445 4472 7141 1143 2961 920 1106 ...
## $ popNative : int 1790 5040 2357 1445 4492 7170 1153 2992 924 1120 ...
## $ popNaitve_bornNH : int 1047 2160 1359 782 2247 4334 545 1538 453 548 ...
## $ popMoved_otherState : int 27 26 63 20 42 26 44 45 5 16 ...
## $ popMoved_abroad : int 0 34 39 29 0 0 0 8 0 0 ...
## $ popCommute_car : int 749 2312 1146 611 2304 3359 575 1337 453 556 ...
## $ popCommute_publicT : int 0 0 0 0 0 0 5 0 0 0 ...
## $ popCommute_bicycle : int 0 0 0 0 0 0 0 10 0 0 ...
## $ popCommute_foot : int 10 80 86 22 24 88 10 58 29 7 ...
## $ popCommute_other : int 10 0 95 0 25 24 21 0 0 5 ...
## $ popCommute_home : int 31 352 79 6 89 123 52 47 6 22 ...
## $ popBA : int 217 1119 473 218 890 994 272 518 319 123 ...
## $ popPov : int 147 288 180 187 134 502 79 437 95 208 ...
## $ medianIncome : int 56667 60045 67900 38821 65221 58561 55208 43242 58571 46845 ...
## $ incomeLabor : num 3.07e+07 1.27e+08 5.73e+07 2.32e+07 1.00e+08 ...
## $ incomeLabor_WageSalary : num 2.76e+07 1.12e+08 5.04e+07 1.99e+07 9.03e+07 ...
## $ incomeLabor_SelfEmpl : num 3107600 14389400 6898600 3321700 9786700 ...
## $ incomeInvest : num 1733400 5898900 1834700 611700 3353800 ...
## $ incomeTotal : num 4.06e+07 1.56e+08 7.15e+07 3.20e+07 1.20e+08 ...
## $ LF : int 919 3007 1502 691 2692 3782 723 1512 501 663 ...
## $ LF_Civilian : int 919 3007 1494 691 2692 3782 723 1512 501 663 ...
## $ LF_Civilian_Unemployed : int 85 163 49 52 108 165 36 36 13 40 ...
## $ LF_Not : int 464 1237 531 544 931 2027 324 997 318 210 ...
## $ housingTotal : int 945 4219 1124 1261 2344 3640 968 2481 730 658 ...
## $ housingVacant_rent : int 0 31 18 65 31 30 12 87 0 0 ...
## $ housingVacant_seasonal : int 240 2016 122 395 557 317 427 1039 306 150 ...
## $ medianHomeValue : int 206500 263000 228500 167900 205500 184900 257400 186700 329200 203500 ...
## $ medianGrossRent : int 918 822 937 552 1133 922 760 704 786 945 ...
## $ unemplRate : num 9.25 5.42 3.28 7.53 4.01 ...
## $ LFparticipationRate : num 66.4 70.9 73.9 56 74.3 ...
## $ housingVacant_seasonal_percent: num 25.4 47.8 10.9 31.3 23.8 ...
## $ housingVacant_rent_percent : num 0 0.735 1.601 5.155 1.323 ...
## $ incomeNonLabor : num 9897700 28775100 14222800 8804000 19797800 ...
## $ incomeTransferPayment : num 8164300 22876200 12388100 8192300 16444000 ...
## $ incomeNonLabor_percent : num 24.4 18.5 19.9 27.5 16.5 ...
## $ incomeInvest_percent : num 4.26 3.79 2.57 1.91 2.8 ...
## $ incomeTransferPayment_percent : num 20.1 14.7 17.3 25.6 13.7 ...
## $ incomeLabor_percent : num 75.6 81.5 80.1 72.5 83.5 ...
## $ popPov_percent : num 8.01 5.52 7.43 12.41 2.94 ...
## $ popBA_percent : num 11.8 21.5 19.5 14.5 19.5 ...
## $ popMoved_otherState_percent : num 1.471 0.499 2.601 1.327 0.92 ...
## $ popMoved_abroad_percent : num 0 0.652 1.61 1.924 0 ...
## $ popMoved_percent : num 1.47 1.15 4.21 3.25 0.92 ...
## $ popCommute_car_percent : num 40.8 44.3 47.3 40.5 50.5 ...
## $ popCommute_publicT_percent : num 0 0 0 0 0 ...
## $ popCommute_bicycle_percent : num 0 0 0 0 0 ...
## $ popCommute_foot_percent : num 0.545 1.534 3.551 1.46 0.526 ...
## $ popCommute_other_percent : num 0.545 0 3.922 0 0.548 ...
## $ popCommute_home_percent : num 1.688 6.751 3.262 0.398 1.95 ...
## $ Year : int 2011 2011 2011 2011 2011 2011 2011 2011 2011 2011 ...
## $ benchM : int NA NA NA NA NA NA NA NA NA NA ...
summary(data)
## X Town County popTotal
## Min. : 1.00 Alexandria: 2 Belknap :22 Min. : 541
## 1st Qu.:16.75 Alton : 2 Carroll :16 1st Qu.: 1496
## Median :32.50 Andover : 2 Grafton :12 Median : 3013
## Mean :32.50 Ashland : 2 Merrimack :10 Mean : 9812983
## 3rd Qu.:48.25 Barnstead : 2 New Hampshire: 2 3rd Qu.: 5516
## Max. :64.00 Belmont : 2 United States: 2 Max. :318558162
## (Other) :52
## medianAge popNative_bornUSA popNative
## Min. :37.00 Min. : 481 Min. : 487
## 1st Qu.:42.27 1st Qu.: 1433 1st Qu.: 1433
## Median :46.30 Median : 2942 Median : 2966
## Mean :46.82 Mean : 8398579 Mean : 8537742
## 3rd Qu.:50.25 3rd Qu.: 5246 3rd Qu.: 5272
## Max. :59.50 Max. :271639606 Max. :276363808
##
## popNaitve_bornNH popMoved_otherState popMoved_abroad
## Min. : 145 Min. : 5 Min. : 0.0
## 1st Qu.: 664 1st Qu.: 27 1st Qu.: 0.0
## Median : 1388 Median : 47 Median : 0.0
## Mean : 5746994 Mean : 188730 Mean : 50896.0
## 3rd Qu.: 2608 3rd Qu.: 103 3rd Qu.: 13.8
## Max. :186708691 Max. :6111964 Max. :1695894.0
##
## popCommute_car popCommute_publicT popCommute_bicycle
## Min. : 173 Min. : 0 Min. : 0.0
## 1st Qu.: 675 1st Qu.: 0 1st Qu.: 0.0
## Median : 1418 Median : 0 Median : 0.0
## Mean : 3854261 Mean : 225044 Mean : 25412.4
## 3rd Qu.: 2323 3rd Qu.: 4 3rd Qu.: 0.2
## Max. :125037241 Max. :7476312 Max. :877995.0
##
## popCommute_foot popCommute_other popCommute_home
## Min. : 0 Min. : 0.0 Min. : 6
## 1st Qu.: 10 1st Qu.: 4.8 1st Qu.: 39
## Median : 24 Median : 13.5 Median : 70
## Mean : 125354 Mean : 54174.8 Mean : 197434
## 3rd Qu.: 74 3rd Qu.: 49.0 3rd Qu.: 145
## Max. :4030730 Max. :1777051.0 Max. :6661892
##
## popBA popPov medianIncome incomeLabor
## Min. : 123 Min. : 30 Min. :38821 Min. :9.157e+06
## 1st Qu.: 360 1st Qu.: 141 1st Qu.:51477 1st Qu.:3.024e+07
## Median : 628 Median : 242 Median :58464 Median :7.037e+07
## Mean : 1912784 Mean : 1404789 Mean :57864 Mean :2.198e+11
## 3rd Qu.: 1025 3rd Qu.: 551 3rd Qu.:63981 3rd Qu.:1.311e+08
## Max. :64767787 Max. :46932225 Max. :76676 Max. :7.290e+12
##
## incomeLabor_WageSalary incomeLabor_SelfEmpl incomeInvest
## Min. :6.118e+06 Min. :1.200e+06 Min. :2.723e+05
## 1st Qu.:2.618e+07 1st Qu.:4.139e+06 1st Qu.:2.141e+06
## Median :6.255e+07 Median :6.469e+06 Median :3.740e+06
## Mean :2.056e+11 Mean :1.412e+10 Mean :1.401e+10
## 3rd Qu.:1.138e+08 3rd Qu.:1.071e+07 3rd Qu.:1.041e+07
## Max. :6.845e+12 Max. :4.534e+11 Max. :4.644e+11
##
## incomeTotal LF LF_Civilian
## Min. :1.554e+07 Min. : 288 Min. : 288
## 1st Qu.:4.338e+07 1st Qu.: 778 1st Qu.: 778
## Median :8.854e+07 Median : 1677 Median : 1677
## Mean :2.837e+11 Mean : 4982562 Mean : 4948950
## 3rd Qu.:1.850e+08 3rd Qu.: 2977 3rd Qu.: 2977
## Max. :9.502e+12 Max. :160818740 Max. :159807099
##
## LF_Civilian_Unemployed LF_Not housingTotal
## Min. : 13 Min. : 187 Min. : 498
## 1st Qu.: 39 1st Qu.: 506 1st Qu.: 1097
## Median : 70 Median : 866 Median : 1948
## Mean : 396637 Mean : 2782613 Mean : 4163607
## 3rd Qu.: 153 3rd Qu.: 1987 3rd Qu.: 4143
## Max. :13488016 Max. :92504969 Max. :134054899
##
## housingVacant_rent housingVacant_seasonal medianHomeValue
## Min. : 0 Min. : 27 Min. :155600
## 1st Qu.: 0 1st Qu.: 300 1st Qu.:184900
## Median : 6 Median : 543 Median :218250
## Mean : 96786 Mean : 162998 Mean :231338
## 3rd Qu.: 38 3rd Qu.: 1244 3rd Qu.:268075
## Max. :3321254 Max. :5368085 Max. :360800
##
## medianGrossRent unemplRate LFparticipationRate
## Min. : 552.0 Min. : 1.310 Min. :45.93
## 1st Qu.: 823.5 1st Qu.: 3.895 1st Qu.:59.26
## Median : 922.0 Median : 4.963 Median :64.54
## Mean : 926.8 Mean : 5.360 Mean :63.78
## 3rd Qu.:1000.5 3rd Qu.: 6.797 3rd Qu.:67.65
## Max. :1315.0 Max. :10.935 Max. :75.95
## NA's :1
## housingVacant_seasonal_percent housingVacant_rent_percent
## Min. : 1.477 Min. :0.0000
## 1st Qu.:16.565 1st Qu.:0.0000
## Median :27.925 Median :0.1363
## Mean :29.913 Mean :0.8662
## 3rd Qu.:41.980 3rd Qu.:1.2604
## Max. :68.020 Max. :5.1546
##
## incomeNonLabor incomeTransferPayment incomeNonLabor_percent
## Min. :4.101e+06 Min. :3.828e+06 Min. :13.60
## 1st Qu.:1.312e+07 1st Qu.:1.012e+07 1st Qu.:19.80
## Median :2.047e+07 Median :1.686e+07 Median :25.93
## Mean :6.394e+10 Mean :4.993e+10 Mean :27.09
## 3rd Qu.:4.423e+07 3rd Qu.:3.312e+07 3rd Qu.:31.85
## Max. :2.212e+12 Max. :1.748e+12 Max. :53.67
##
## incomeInvest_percent incomeTransferPayment_percent incomeLabor_percent
## Min. : 1.031 Min. :10.58 Min. :46.33
## 1st Qu.: 2.542 1st Qu.:15.94 1st Qu.:68.15
## Median : 4.928 Median :18.44 Median :74.07
## Mean : 6.657 Mean :20.43 Mean :72.91
## 3rd Qu.: 8.735 3rd Qu.:24.75 3rd Qu.:80.20
## Max. :36.817 Max. :36.41 Max. :86.40
##
## popPov_percent popBA_percent popMoved_otherState_percent
## Min. : 1.157 Min. :10.58 Min. :0.3537
## 1st Qu.: 6.630 1st Qu.:15.79 1st Qu.:1.1786
## Median : 8.495 Median :21.53 Median :1.9088
## Mean : 9.681 Mean :22.60 Mean :2.1631
## 3rd Qu.:12.705 3rd Qu.:27.98 3rd Qu.:2.7998
## Max. :21.167 Max. :43.13 Max. :7.7385
##
## popMoved_abroad_percent popMoved_percent popCommute_car_percent
## Min. :0.0000 Min. : 0.3537 Min. :31.98
## 1st Qu.:0.0000 1st Qu.: 1.2728 1st Qu.:40.47
## Median :0.0000 Median : 2.0825 Median :44.18
## Mean :0.3554 Mean : 2.5185 Mean :43.82
## 3rd Qu.:0.3727 3rd Qu.: 3.2062 3rd Qu.:47.22
## Max. :7.7634 Max. :11.0906 Max. :54.78
##
## popCommute_publicT_percent popCommute_bicycle_percent
## Min. :0.0000 Min. :0.00000
## 1st Qu.:0.0000 1st Qu.:0.00000
## Median :0.0000 Median :0.00000
## Mean :0.1775 Mean :0.08443
## 3rd Qu.:0.1488 3rd Qu.:0.00840
## Max. :2.3469 Max. :1.08887
##
## popCommute_foot_percent popCommute_other_percent popCommute_home_percent
## Min. :0.0000 Min. :0.0000 Min. : 0.3981
## 1st Qu.:0.4395 1st Qu.:0.2175 1st Qu.: 1.6705
## Median :0.8309 Median :0.5455 Median : 2.3043
## Mean :1.2211 Mean :0.7564 Mean : 2.9100
## 3rd Qu.:1.5008 3rd Qu.:0.8935 3rd Qu.: 3.6064
## Max. :6.6234 Max. :3.9224 Max. :15.8965
##
## Year benchM
## Min. :2011 Min. :1.0
## 1st Qu.:2011 1st Qu.:1.0
## Median :2014 Median :1.5
## Mean :2014 Mean :1.5
## 3rd Qu.:2016 3rd Qu.:2.0
## Max. :2016 Max. :2.0
## NA's :60
levels(data$Town)
## [1] "Alexandria" "Alton" "Andover" "Ashland"
## [5] "Barnstead" "Belmont" "Bridgewater" "Bristol"
## [9] "Center Harbor" "Danbury" "Effingham" "Franklin"
## [13] "Freedom" "Gilford" "Gilmanton" "Hebron"
## [17] "Hill" "Holderness" "Laconia" "Meredith"
## [21] "Moultonborough" "New Hampshire" "New Hampton" "Northfield"
## [25] "Ossipee" "Sanbornton" "Sandwich" "Tamworth"
## [29] "Tilton" "Tuftonboro" "United States" "Wolfeboro"Exploratory data analysis
What are some graphical tools for numerical data? When is one more appropriate than another?
# Load packages
library(ggplot2)
library(dplyr)
library(tidyr)
data %>%
filter(!Town %in% c("United States", "New Hampshire")) %>%
select(Town, medianIncome, Year) %>%
mutate(Year = paste0("Yr",Year)) %>%
spread(Year, medianIncome) %>%
ggplot(aes(reorder(x = Town, Yr2016-Yr2011), y = Yr2016-Yr2011, fill = Yr2016-Yr2011 > 0)) +
geom_col(show.legend = FALSE) +
coord_flip() +
labs(title = "Change in Median Household Income between 2007-11 and 2012-16",
x = NULL,
y = "Change in Income")
data %>%
filter(!Town %in% c("United States", "New Hampshire")) %>%
select(Town, medianIncome, Year) %>%
mutate(Year = paste0("Yr",Year)) %>%
spread(Year, medianIncome) %>%
ggplot(aes(reorder(x = Town, (Yr2016-Yr2011)/Yr2011), y = (Yr2016-Yr2011)/Yr2011, fill = Yr2016-Yr2011 > 0)) +
geom_col(show.legend = FALSE) +
coord_flip() +
labs(title = "Percent Change in Median Household Income between 2007-11 and 2012-16",
x = NULL,
y = "Percent Change in Income")