Tutorial 4
Matthew Kirwan
2023-03-13
In class
Loading packages
library(tidyr)
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.4.1 ✔ dplyr 1.0.10
## ✔ tibble 3.1.8 ✔ stringr 1.5.0
## ✔ readr 2.1.3 ✔ forcats 1.0.0
## ✔ purrr 1.0.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()library(ggplot2)
library(dplyr)
library(tibble)Interpreting regressions
Collinearity
energy=read.csv("recs2015_public_v4.csv")
lm(KWH~UATYP10, energy) %>% summary()##
## Call:
## lm(formula = KWH ~ UATYP10, data = energy)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13718 -4848 -1385 3391 53132
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10772.6 279.8 38.494 <2e-16 ***
## UATYP10R 3584.6 344.5 10.405 <2e-16 ***
## UATYP10U -687.5 300.4 -2.289 0.0221 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6843 on 5683 degrees of freedom
## Multiple R-squared: 0.058, Adjusted R-squared: 0.05767
## F-statistic: 175 on 2 and 5683 DF, p-value: < 2.2e-16loc.lm=lm(KWH~UATYP10, energy)Collinearity for text categries
lm(KWH~REGIONC, energy) %>% summary()##
## Call:
## lm(formula = KWH ~ REGIONC, data = energy)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11046 -5158 -1460 3565 52112
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10148.25 273.27 37.136 < 2e-16 ***
## REGIONC 319.00 93.02 3.429 0.000609 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7043 on 5684 degrees of freedom
## Multiple R-squared: 0.002065, Adjusted R-squared: 0.001889
## F-statistic: 11.76 on 1 and 5684 DF, p-value: 0.0006095regn.lm=lm(KWH~as.factor(REGIONC), energy)Average electricity consumption by a house at each region
region1=round(coef(regn.lm)["(Intercept)"]/10^3,3)
region2=round((coef(regn.lm)["(Intercept)"]+coef(regn.lm)["as.factor(REGIONC)2"])/10^3,3)%>% as.numeric
region3=round((coef(regn.lm)["(Intercept)"]+coef(regn.lm)["as.factor(REGIONC)3"])/10^3,3)%>% as.numeric
region4=round((coef(regn.lm)["(Intercept)"]+coef(regn.lm)["as.factor(REGIONC)4"])/10^3,3)%>% as.numericAssignment
Data import and exploration
energy=read.csv("recs2015_public_v4.csv")
head(energy, 10)## DOEID REGIONC DIVISION METROMICRO UATYP10 TYPEHUQ ZTYPEHUQ CELLAR ZCELLAR
## 1 10001 4 10 METRO U 2 0 0 0
## 2 10002 3 7 NONE R 2 0 0 0
## 3 10003 3 6 METRO U 2 0 1 0
## 4 10004 2 4 MICRO C 2 0 1 0
## 5 10005 1 2 METRO U 2 0 1 0
## 6 10006 1 1 NONE C 5 0 -2 -2
## 7 10007 3 5 METRO U 4 0 -2 -2
## 8 10008 2 3 METRO R 2 0 1 0
## 9 10009 1 2 METRO U 2 0 0 0
## 10 10010 3 7 METRO U 2 0 0 0
## BASEFIN ZBASEFIN ATTIC ZATTIC ATTICFIN ZATTICFIN STORIES ZSTORIES PRKGPLC1
## 1 -2 -2 0 0 -2 -2 20 0 1
## 2 -2 -2 0 0 -2 -2 10 0 0
## 3 1 0 0 0 -2 -2 10 0 0
## 4 1 0 0 0 -2 -2 10 0 1
## 5 0 0 1 0 0 0 20 0 1
## 6 -2 -2 -2 -2 -2 -2 -2 -2 -2
## 7 -2 -2 -2 -2 -2 -2 -2 -2 -2
## 8 1 0 1 0 1 0 10 0 1
## 9 -2 -2 0 0 -2 -2 20 0 1
## 10 -2 -2 1 0 0 0 10 0 1
## ZPRKGPLC1 SIZEOFGARAGE ZSIZEOFGARAGE KOWNRENT ZKOWNRENT YEARMADERANGE
## 1 0 2 0 1 0 7
## 2 0 -2 -2 1 0 5
## 3 0 -2 -2 1 0 4
## 4 0 2 0 1 0 2
## 5 0 1 0 1 0 4
## 6 -2 -2 -2 2 0 5
## 7 -2 -2 -2 2 0 3
## 8 0 1 0 1 0 4
## 9 0 2 0 1 0 5
## 10 0 2 0 2 0 2
## ZYEARMADERANGE OCCUPYYRANGE ZOCCUPYYRANGE STUDIO ZSTUDIO BEDROOMS ZBEDROOMS
## 1 0 8 0 -2 -2 3 0
## 2 0 6 0 -2 -2 2 0
## 3 0 7 0 -2 -2 4 0
## 4 0 7 0 -2 -2 3 0
## 5 0 8 0 -2 -2 3 0
## 6 0 7 0 1 0 0 0
## 7 0 7 0 0 0 2 0
## 8 0 6 0 -2 -2 3 0
## 9 0 6 0 -2 -2 4 0
## 10 0 7 0 -2 -2 3 0
## NCOMBATH ZNCOMBATH NHAFBATH ZNHAFBATH OTHROOMS ZOTHROOMS TOTROOMS ZTOTROOMS
## 1 2 0 1 0 4 0 7 0
## 2 1 0 0 0 2 0 4 0
## 3 2 0 0 0 5 0 9 0
## 4 2 0 0 0 4 0 7 0
## 5 2 0 0 0 3 0 6 0
## 6 1 0 0 0 1 0 1 0
## 7 1 0 0 0 2 0 4 0
## 8 1 0 0 0 2 0 5 0
## 9 2 0 0 0 5 0 9 0
## 10 2 0 0 0 3 0 6 0
## WALLTYPE ZWALLTYPE ROOFTYPE ZROOFTYPE HIGHCEIL ZHIGHCEIL DOOR1SUM ZDOOR1SUM
## 1 4 0 1 0 1 0 2 0
## 2 3 0 3 0 0 0 0 0
## 3 2 0 5 0 0 0 1 0
## 4 3 0 5 0 1 0 4 0
## 5 1 0 5 0 0 0 1 0
## 6 3 0 -2 -2 0 0 0 0
## 7 1 0 5 0 0 0 0 0
## 8 3 0 5 0 0 0 1 0
## 9 3 0 5 0 0 0 1 0
## 10 1 1 5 0 0 0 0 0
## WINDOWS ZWINDOWS TYPEGLASS ZTYPEGLASS WINFRAME ZWINFRAME ADQINSUL ZADQINSUL
## 1 41 0 2 0 2 0 2 0
## 2 20 0 1 0 2 0 2 0
## 3 41 0 1 0 1 0 2 0
## 4 42 0 2 0 2 0 2 0
## 5 30 0 1 0 3 0 2 0
## 6 20 0 2 0 1 0 1 0
## 7 30 0 1 0 1 0 3 0
## 8 30 0 2 0 1 0 2 0
## 9 41 0 2 0 3 0 2 0
## 10 42 0 1 0 1 0 3 0
## DRAFTY ZDRAFTY UGASHERE ZUGASHERE SWIMPOOL ZSWIMPOOL MONPOOL ZMONPOOL POOL
## 1 4 0 1 0 0 0 -2 -2 -2
## 2 4 0 1 0 0 0 -2 -2 -2
## 3 3 0 1 0 0 0 -2 -2 -2
## 4 4 0 0 0 0 0 -2 -2 -2
## 5 4 0 1 0 0 0 -2 -2 -2
## 6 4 0 1 1 -2 -2 -2 -2 -2
## 7 4 0 1 0 -2 -2 -2 -2 -2
## 8 3 0 1 0 0 0 -2 -2 -2
## 9 3 0 0 0 0 0 -2 -2 -2
## 10 3 0 1 0 0 0 -2 -2 -2
## ZPOOL FUELPOOL ZFUELPOOL RECBATH ZRECBATH MONTUB ZMONTUB FUELTUB ZFUELTUB
## 1 -2 -2 -2 0 0 -2 -2 -2 -2
## 2 -2 -2 -2 0 0 -2 -2 -2 -2
## 3 -2 -2 -2 0 0 -2 -2 -2 -2
## 4 -2 -2 -2 0 0 -2 -2 -2 -2
## 5 -2 -2 -2 0 0 -2 -2 -2 -2
## 6 -2 -2 -2 0 0 -2 -2 -2 -2
## 7 -2 -2 -2 0 0 -2 -2 -2 -2
## 8 -2 -2 -2 0 0 -2 -2 -2 -2
## 9 -2 -2 -2 0 0 -2 -2 -2 -2
## 10 -2 -2 -2 0 0 -2 -2 -2 -2
## OUTLET ZOUTLET ALTFUELPEV ZALTFUELPEV BACKUP ZBACKUP SOLAR NUMFRIG ZNUMFRIG
## 1 1 0 0 0 1 0 0 1 0
## 2 0 0 0 0 0 0 0 1 0
## 3 1 0 0 0 0 0 0 2 0
## 4 1 0 0 0 0 0 0 2 0
## 5 1 0 0 0 0 0 0 2 0
## 6 -2 -2 0 0 -2 -2 -2 1 0
## 7 0 0 0 0 0 0 -2 1 0
## 8 1 0 0 0 0 0 0 1 0
## 9 1 0 0 0 0 0 0 2 0
## 10 1 0 0 0 0 0 0 1 0
## SIZRFRI1 ZSIZRFRI1 TYPERFR1 ZTYPERFR1 AGERFRI1 ZAGERFRI1 ICE ZICE SIZRFRI2
## 1 3 0 5 0 3 0 0 0 -2
## 2 4 0 21 0 1 0 1 0 -2
## 3 4 0 21 0 41 0 1 0 4
## 4 3 0 22 0 3 0 0 0 1
## 5 3 0 23 0 1 0 0 0 2
## 6 3 0 22 0 1 0 0 0 -2
## 7 3 0 22 0 41 0 0 0 -2
## 8 3 0 21 0 42 0 0 0 -2
## 9 4 0 23 0 3 0 0 0 3
## 10 4 0 21 0 1 0 1 0 -2
## ZSIZRFRI2 TYPERFR2 ZTYPERFR2 AGERFRI2 ZAGERFRI2 LOCRFRI2 ZLOCRFRI2 NUMFREEZ
## 1 -2 -2 -2 -2 -2 -2 -2 1
## 2 -2 -2 -2 -2 -2 -2 -2 1
## 3 0 21 0 3 0 1 0 0
## 4 0 -2 -2 3 0 2 0 1
## 5 0 1 0 2 0 1 0 0
## 6 -2 -2 -2 -2 -2 -2 -2 0
## 7 -2 -2 -2 -2 -2 -2 -2 0
## 8 -2 -2 -2 -2 -2 -2 -2 1
## 9 1 21 1 3 1 2 1 1
## 10 -2 -2 -2 -2 -2 -2 -2 0
## ZNUMFREEZ UPRTFRZR ZUPRTFRZR SIZFREEZ ZSIZFREEZ AGEFRZR ZAGEFRZR STOVEN
## 1 0 2 0 2 0 41 0 1
## 2 0 2 0 2 0 41 0 1
## 3 0 -2 -2 -2 -2 -2 -2 2
## 4 0 1 0 3 0 42 0 1
## 5 0 -2 -2 -2 -2 -2 -2 1
## 6 0 -2 -2 -2 -2 -2 -2 1
## 7 0 -2 -2 -2 -2 -2 -2 1
## 8 0 1 0 3 0 41 0 1
## 9 0 2 0 2 0 3 0 1
## 10 0 -2 -2 -2 -2 -2 -2 1
## ZSTOVEN STOVENFUEL ZSTOVENFUEL DUALCOOKTFUEL ZDUALCOOKTFUEL DUALOVENFUEL
## 1 0 1 0 -2 -2 -2
## 2 0 5 0 -2 -2 -2
## 3 0 5 0 -2 -2 -2
## 4 0 5 0 -2 -2 -2
## 5 0 1 0 -2 -2 -2
## 6 0 5 0 -2 -2 -2
## 7 0 5 0 -2 -2 -2
## 8 0 5 0 -2 -2 -2
## 9 0 5 0 -2 -2 -2
## 10 0 5 0 -2 -2 -2
## ZDUALOVENFUEL COOKTUSE ZCOOKTUSE OVENUSE ZOVENUSE STOVE ZSTOVE STOVEFUEL
## 1 -2 5 0 0 0 0 0 -2
## 2 -2 6 0 5 0 0 0 -2
## 3 -2 14 0 14 0 0 1 -2
## 4 -2 2 0 2 0 0 0 -2
## 5 -2 6 0 0 0 1 0 1
## 6 -2 12 0 6 0 0 0 -2
## 7 -2 7 0 1 0 0 0 -2
## 8 -2 14 0 6 0 0 0 -2
## 9 -2 7 0 3 0 0 0 -2
## 10 -2 7 0 5 0 0 1 -2
## ZSTOVEFUEL SEPCOOKTUSE ZSEPCOOKTUSE OVEN ZOVEN OVENFUEL ZOVENFUEL SEPOVENUSE
## 1 -2 -2 -2 0 0 -2 -2 -2
## 2 -2 -2 -2 0 0 -2 -2 -2
## 3 -2 -2 -2 0 0 -2 -2 -2
## 4 -2 -2 -2 0 0 -2 -2 -2
## 5 0 6 0 1 0 1 0 0
## 6 -2 -2 -2 0 0 -2 -2 -2
## 7 -2 -2 -2 0 0 -2 -2 -2
## 8 -2 -2 -2 0 0 -2 -2 -2
## 9 -2 -2 -2 0 0 -2 -2 -2
## 10 -2 -2 -2 0 0 -2 -2 -2
## ZSEPOVENUSE MICRO ZMICRO AMTMICRO ZAMTMICRO OUTGRILL ZOUTGRILL OUTGRILLFUEL
## 1 -2 1 0 10 0 1 0 2
## 2 -2 1 0 20 0 1 0 23
## 3 -2 2 0 14 0 1 0 23
## 4 -2 1 0 0 0 1 0 2
## 5 0 1 0 6 0 1 0 1
## 6 -2 1 0 3 0 0 0 -2
## 7 -2 1 0 10 0 0 0 -2
## 8 -2 1 0 50 0 1 0 23
## 9 -2 2 0 12 0 1 0 2
## 10 -2 1 0 15 0 0 0 -2
## ZOUTGRILLFUEL NUMMEAL ZNUMMEAL TOAST ZTOAST TOASTOVN ZTOASTOVN COFFEE
## 1 0 3 0 1 0 0 0 1
## 2 0 3 0 1 0 0 0 0
## 3 0 2 0 1 0 1 0 1
## 4 0 6 0 1 0 0 0 1
## 5 0 0 0 1 0 1 0 1
## 6 -2 1 0 0 0 0 0 0
## 7 -2 3 0 0 0 0 0 0
## 8 0 1 0 1 0 0 0 1
## 9 0 3 0 1 0 0 0 1
## 10 -2 2 0 1 0 0 0 1
## ZCOFFEE CROCKPOT ZCROCKPOT FOODPROC ZFOODPROC RICECOOK ZRICECOOK BLENDER
## 1 0 0 0 0 0 1 0 0
## 2 0 1 0 0 0 0 0 0
## 3 0 1 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0
## 5 0 1 0 0 0 1 0 1
## 6 0 0 0 0 0 0 0 0
## 7 0 0 0 0 0 0 0 0
## 8 0 0 0 0 0 0 0 1
## 9 0 1 0 0 0 0 0 0
## 10 0 1 0 0 0 0 0 1
## ZBLENDER APPOTHER ZAPPOTHER DISHWASH ZDISHWASH DWASHUSE ZDWASHUSE DWCYCLE
## 1 0 0 0 1 0 6 0 1
## 2 0 1 0 0 0 -2 -2 -2
## 3 0 1 0 1 0 7 0 2
## 4 0 0 0 0 0 -2 -2 -2
## 5 0 0 0 0 0 -2 -2 -2
## 6 0 0 0 0 0 -2 -2 -2
## 7 0 0 0 0 0 -2 -2 -2
## 8 0 0 0 1 0 4 0 1
## 9 0 0 0 1 0 5 0 1
## 10 0 0 0 1 0 19 0 3
## ZDWCYCLE AGEDW ZAGEDW CWASHER ZCWASHER TOPFRONT ZTOPFRONT WASHLOAD ZWASHLOAD
## 1 0 3 0 1 0 2 0 3 0
## 2 -2 -2 -2 0 0 -2 -2 -2 -2
## 3 1 3 0 1 0 2 0 3 0
## 4 -2 -2 -2 1 0 1 0 3 0
## 5 -2 -2 -2 1 0 1 0 2 0
## 6 -2 -2 -2 0 0 -2 -2 -2 -2
## 7 -2 -2 -2 1 0 1 0 1 0
## 8 0 3 1 1 0 1 0 5 0
## 9 0 3 0 1 0 2 0 2 0
## 10 1 1 0 1 0 1 0 20 0
## WASHTEMP ZWASHTEMP RNSETEMP ZRNSETEMP AGECWASH ZAGECWASH DRYER ZDRYER
## 1 3 0 3 0 3 0 1 0
## 2 -2 -2 -2 -2 -2 -2 0 0
## 3 3 0 3 0 2 0 1 0
## 4 2 0 3 0 41 0 1 0
## 5 2 0 2 0 3 0 1 0
## 6 -2 -2 -2 -2 -2 -2 0 0
## 7 3 0 3 0 41 0 1 0
## 8 2 0 3 0 1 0 1 0
## 9 2 0 3 0 2 0 1 0
## 10 3 0 3 0 3 0 1 0
## DRYRFUEL ZDRYRFUEL DRYRUSE ZDRYRUSE AGECDRYER ZAGECDRYER TVCOLOR ZTVCOLOR
## 1 5 0 3 0 3 0 2 0
## 2 -2 -2 -2 -2 -2 -2 2 0
## 3 5 0 3 0 2 0 4 0
## 4 5 0 3 0 41 0 5 0
## 5 5 0 2 0 3 0 5 0
## 6 -2 -2 -2 -2 -2 -2 1 0
## 7 5 0 0 0 41 0 1 0
## 8 5 0 4 0 1 0 2 0
## 9 5 0 2 0 2 0 5 0
## 10 5 0 20 0 3 0 3 0
## TVSIZE1 ZTVSIZE1 TVTYPE1 ZTVTYPE1 TVONWD1 ZTVONWD1 TVONWE1 ZTVONWE1 TVSIZE2
## 1 3 0 1 0 2 0 3 0 1
## 2 2 0 1 0 5 0 5 0 1
## 3 2 0 2 1 4 0 4 0 2
## 4 3 0 3 0 2 0 1 0 2
## 5 2 0 3 0 2 0 2 0 3
## 6 2 0 1 0 3 0 3 0 -2
## 7 1 0 1 0 2 0 2 0 -2
## 8 3 0 1 0 4 0 4 0 3
## 9 3 0 3 0 4 0 5 0 2
## 10 3 0 3 0 3 0 3 0 2
## ZTVSIZE2 TVTYPE2 ZTVTYPE2 TVONWD2 ZTVONWD2 TVONWE2 ZTVONWE2 CABLESAT
## 1 0 1 0 1 0 2 0 1
## 2 0 1 0 1 0 2 0 1
## 3 0 1 1 3 0 3 0 4
## 4 0 3 0 1 0 1 0 2
## 5 0 3 0 2 0 2 0 0
## 6 -2 -2 -2 -2 -2 -2 -2 0
## 7 -2 -2 -2 -2 -2 -2 -2 0
## 8 0 1 0 1 0 1 0 1
## 9 0 3 0 3 0 3 0 4
## 10 0 3 0 2 0 3 0 3
## ZCABLESAT COMBODVR ZCOMBODVR SEPDVR ZSEPDVR PLAYSTA ZPLAYSTA DVD ZDVD VCR
## 1 0 0 0 0 0 0 0 1 0 0
## 2 0 0 0 0 0 0 0 1 0 0
## 3 0 2 0 0 1 2 0 2 1 2
## 4 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 1 0 5 0 0
## 6 0 0 0 0 0 1 0 1 0 0
## 7 0 0 0 1 0 0 0 0 0 0
## 8 0 1 0 0 0 0 0 1 0 0
## 9 0 1 0 0 0 1 0 5 0 1
## 10 0 1 0 0 0 3 0 1 0 0
## ZVCR INTSTREAM ZINTSTREAM TVAUDIOSYS ZTVAUDIOSYS DESKTOP ZDESKTOP NUMLAPTOP
## 1 0 0 0 0 0 0 0 2
## 2 0 0 0 0 0 0 0 0
## 3 0 1 1 0 0 1 0 2
## 4 0 0 0 0 0 1 0 0
## 5 0 0 0 2 0 0 0 3
## 6 0 1 0 1 0 0 0 1
## 7 0 0 0 0 0 0 0 0
## 8 0 0 0 1 0 1 0 1
## 9 0 0 0 0 0 1 0 3
## 10 0 2 0 0 0 1 0 1
## ZNUMLAPTOP NUMTABLET ZNUMTABLET ELPERIPH ZELPERIPH NUMSMPHONE ZNUMSMPHONE
## 1 0 2 0 1 0 2 0
## 2 0 0 0 0 0 0 0
## 3 0 2 0 2 1 2 0
## 4 0 1 0 1 0 1 0
## 5 0 2 0 1 0 2 0
## 6 0 0 0 0 0 1 0
## 7 0 0 0 0 0 1 0
## 8 0 0 0 2 0 1 0
## 9 0 4 0 2 0 4 0
## 10 0 4 0 1 0 2 0
## CELLPHONE ZCELLPHONE INTERNET ZINTERNET INWIRELESS ZINWIRELESS HEATHOME
## 1 0 0 1 0 1 0 1
## 2 2 0 1 0 0 0 1
## 3 0 0 1 0 1 1 1
## 4 0 0 1 0 0 0 1
## 5 0 0 1 0 1 0 1
## 6 0 0 1 0 1 0 1
## 7 0 0 0 0 -2 -2 1
## 8 1 0 1 0 1 0 1
## 9 0 0 1 0 1 1 1
## 10 0 0 1 0 1 0 1
## ZHEATHOME DNTHEAT ZDNTHEAT EQUIPM ZEQUIPM FUELHEAT ZFUELHEAT EQUIPAGE
## 1 0 -2 -2 3 0 1 0 41
## 2 0 -2 -2 9 0 5 0 1
## 3 0 -2 -2 3 0 1 0 42
## 4 0 -2 -2 3 0 2 0 3
## 5 0 -2 -2 3 0 1 0 3
## 6 0 -2 -2 3 0 2 0 3
## 7 0 -2 -2 3 0 1 0 41
## 8 0 -2 -2 3 0 1 0 5
## 9 0 -2 -2 3 0 3 0 5
## 10 0 -2 -2 3 0 5 0 42
## ZEQUIPAGE THERMAIN ZTHERMAIN PROTHERM ZPROTHERM EQUIPMUSE ZEQUIPMUSE
## 1 0 1 0 1 0 3 0
## 2 0 1 0 1 0 1 0
## 3 0 1 0 1 0 1 0
## 4 0 1 0 0 0 2 0
## 5 0 1 0 0 0 2 0
## 6 0 1 0 0 0 4 0
## 7 0 1 0 0 0 2 0
## 8 0 1 0 1 0 2 0
## 9 0 1 0 1 0 1 0
## 10 0 1 0 1 0 3 0
## TEMPHOME ZTEMPHOME TEMPGONE ZTEMPGONE TEMPNITE ZTEMPNITE EQUIPAUX ZEQUIPAUX
## 1 69 0 69 0 60 0 0 0
## 2 75 0 70 0 72 0 1 0
## 3 70 0 70 0 68 0 1 0
## 4 68 0 65 0 65 0 1 0
## 5 68 0 62 0 66 0 0 0
## 6 70 0 66 0 70 0 0 0
## 7 73 0 70 0 72 0 0 0
## 8 66 0 62 0 64 0 0 0
## 9 70 0 70 0 70 0 0 0
## 10 70 0 70 0 65 0 1 0
## EQUIPAUXTYPE ZEQUIPAUXTYPE FUELAUX ZFUELAUX BASEHEAT ZBASEHEAT ATTCHEAT
## 1 -2 -2 -2 -2 -2 -2 -2
## 2 1 0 5 0 -2 -2 -2
## 3 1 0 5 0 1 0 -2
## 4 9 0 5 0 1 0 -2
## 5 -2 -2 -2 -2 0 0 0
## 6 -2 -2 -2 -2 -2 -2 -2
## 7 -2 -2 -2 -2 -2 -2 -2
## 8 -2 -2 -2 -2 0 0 0
## 9 -2 -2 -2 -2 -2 -2 -2
## 10 1 0 5 0 -2 -2 0
## ZATTCHEAT GARGHEAT ZGARGHEAT MOISTURE ZMOISTURE USEMOISTURE ZUSEMOISTURE
## 1 -2 0 0 0 0 -2 -2
## 2 -2 -2 -2 1 0 1 0
## 3 -2 -2 -2 0 0 -2 -2
## 4 -2 0 0 0 0 -2 -2
## 5 0 0 0 0 0 -2 -2
## 6 -2 -2 -2 0 0 -2 -2
## 7 -2 -2 -2 0 0 -2 -2
## 8 0 0 0 0 0 -2 -2
## 9 -2 0 0 0 0 -2 -2
## 10 0 0 0 0 0 -2 -2
## AIRCOND ZAIRCOND COOLTYPE ZCOOLTYPE CENACHP ZCENACHP AGECENAC ZAGECENAC
## 1 1 0 1 0 0 0 41 0
## 2 1 0 2 0 -2 -2 -2 -2
## 3 1 0 3 0 0 0 42 0
## 4 1 0 1 0 0 0 3 0
## 5 1 0 1 0 0 0 3 0
## 6 1 0 2 0 -2 -2 -2 -2
## 7 1 0 1 0 1 0 41 0
## 8 1 0 2 0 -2 -2 -2 -2
## 9 1 0 1 0 0 0 3 0
## 10 1 0 1 0 0 0 42 0
## THERMAINAC ZTHERMAINAC PROTHERMAC ZPROTHERMAC USECENAC ZUSECENAC NUMBERAC
## 1 1 0 1 0 3 0 -2
## 2 -2 -2 -2 -2 -2 -2 4
## 3 1 0 1 0 1 0 2
## 4 1 0 0 0 2 0 -2
## 5 1 0 0 0 2 0 -2
## 6 -2 -2 -2 -2 -2 -2 1
## 7 1 0 0 0 2 0 -2
## 8 -2 -2 -2 -2 -2 -2 2
## 9 1 0 1 0 1 0 -2
## 10 1 0 1 0 2 0 -2
## ZNUMBERAC WWACAGE ZWWACAGE USEWWAC ZUSEWWAC TEMPHOMEAC ZTEMPHOMEAC
## 1 -2 -2 -2 -2 -2 78 0
## 2 0 3 0 1 0 76 0
## 3 0 1 0 4 0 75 0
## 4 -2 -2 -2 -2 -2 76 0
## 5 -2 -2 -2 -2 -2 72 0
## 6 0 1 0 1 0 60 0
## 7 -2 -2 -2 -2 -2 72 0
## 8 0 3 0 2 0 74 0
## 9 -2 -2 -2 -2 -2 72 0
## 10 -2 -2 -2 -2 -2 67 0
## TEMPGONEAC ZTEMPGONEAC TEMPNITEAC ZTEMPNITEAC BASECOOL ZBASECOOL ATTCCOOL
## 1 80 0 80 0 -2 -2 -2
## 2 80 0 74 0 -2 -2 -2
## 3 85 1 75 0 1 0 -2
## 4 85 0 72 0 1 0 -2
## 5 78 0 70 0 0 0 0
## 6 66 0 55 0 -2 -2 -2
## 7 75 0 73 0 -2 -2 -2
## 8 78 0 74 0 0 0 0
## 9 72 0 72 0 -2 -2 -2
## 10 70 0 65 0 -2 -2 0
## ZATTCCOOL GARGCOOL ZGARGCOOL SWAMPCOL ZSWAMPCOL NUMCFAN ZNUMCFAN NUMFLOORFAN
## 1 -2 0 0 0 0 5 0 0
## 2 -2 -2 -2 0 0 3 0 1
## 3 -2 -2 -2 0 1 7 0 0
## 4 -2 0 0 -2 -2 9 0 0
## 5 0 0 0 -2 -2 2 0 2
## 6 -2 -2 -2 -2 -2 0 0 2
## 7 -2 -2 -2 0 0 2 0 0
## 8 0 0 0 -2 -2 3 0 3
## 9 -2 0 0 -2 -2 2 0 0
## 10 0 0 0 0 0 4 0 0
## ZNUMFLOORFAN NUMWHOLEFAN ZNUMWHOLEFAN NUMATTICFAN ZNUMATTICFAN NOTMOIST
## 1 0 0 0 0 0 0
## 2 0 0 0 0 0 0
## 3 0 0 0 0 0 0
## 4 0 0 0 0 0 0
## 5 0 0 0 0 0 1
## 6 0 -2 -2 -2 -2 0
## 7 0 -2 -2 -2 -2 0
## 8 0 0 0 0 0 1
## 9 0 0 0 0 0 0
## 10 0 0 0 0 0 0
## ZNOTMOIST USENOTMOIST ZUSENOTMOIST FUELH2O ZFUELH2O H2OHEATAPT ZH2OHEATAPT
## 1 0 -2 -2 1 0 -2 -2
## 2 0 -2 -2 5 0 -2 -2
## 3 0 -2 -2 1 0 -2 -2
## 4 0 -2 -2 2 0 -2 -2
## 5 0 1 0 1 0 -2 -2
## 6 0 -2 -2 2 0 2 0
## 7 0 -2 -2 1 0 2 0
## 8 0 10 0 1 0 -2 -2
## 9 0 -2 -2 5 0 -2 -2
## 10 0 -2 -2 5 0 -2 -2
## WHEATAGE ZWHEATAGE WHEATSIZ ZWHEATSIZ MORETHAN1H2O ZMORETHAN1H2O FUELH2O2
## 1 41 0 1 0 0 0 -2
## 2 1 0 1 0 0 0 -2
## 3 41 0 3 0 0 0 -2
## 4 3 0 3 0 0 0 -2
## 5 3 0 2 0 0 0 -2
## 6 3 0 -2 -2 -2 -2 -2
## 7 41 0 -2 -2 -2 -2 -2
## 8 42 0 2 0 0 0 -2
## 9 41 0 3 0 0 0 -2
## 10 2 0 3 0 0 0 -2
## ZFUELH2O2 LGTINNUM ZLGTINNUM LGTIN4 ZLGTIN4 LGTINCAN ZLGTINCAN LGTINCFL
## 1 -2 2 0 2 0 4 0 4
## 2 -2 1 0 5 0 1 0 4
## 3 -2 2 0 8 0 0 0 1
## 4 -2 4 0 2 0 3 0 3
## 5 -2 2 0 10 0 4 0 4
## 6 -2 1 0 1 0 4 0 4
## 7 -2 1 0 3 0 0 0 2
## 8 -2 1 0 1 0 4 0 2
## 9 -2 2 0 3 0 1 0 0
## 10 -2 2 0 20 0 4 0 4
## ZLGTINCFL LGTINLED ZLGTINLED LGTINCNTL ZLGTINCNTL LGTOUTNUM ZLGTOUTNUM
## 1 0 0 0 0 0 1 0
## 2 0 4 0 0 0 1 0
## 3 0 0 1 1 0 1 0
## 4 0 0 0 1 0 2 0
## 5 0 3 0 1 0 2 0
## 6 0 0 0 0 0 -2 -2
## 7 0 4 0 0 0 -2 -2
## 8 0 0 0 0 0 2 0
## 9 0 0 0 0 0 2 0
## 10 0 0 0 0 0 1 0
## LGTOUTCNTL ZLGTOUTCNTL AUDIT AUDITCHG EELIGHTS FREEAUDIT REBATEAPP RECYCAPP
## 1 1 0 0 -2 0 0 0 0
## 2 1 0 0 -2 0 0 0 0
## 3 0 0 0 -2 0 0 0 0
## 4 1 0 0 -2 0 0 0 0
## 5 1 0 0 -2 0 0 0 0
## 6 -2 -2 1 1 -2 -2 -2 -2
## 7 -2 -2 0 -2 -2 -2 -2 -2
## 8 1 0 0 -2 1 0 0 0
## 9 1 0 0 -2 0 0 0 0
## 10 0 0 0 -2 -2 -2 -2 -2
## TAXCREDITAPP BENOTHER ESCWASH ESDISHW ESDRYER ESFREEZE ESFRIG ESLIGHT
## 1 0 1 1 0 1 0 1 0
## 2 0 0 -2 -2 -2 0 1 0
## 3 0 0 1 0 1 -2 0 1
## 4 0 0 1 -2 1 0 1 1
## 5 0 0 0 -2 0 -2 0 1
## 6 -2 -2 -2 -2 -2 -2 1 0
## 7 -2 -2 0 -2 0 -2 1 0
## 8 0 0 1 1 1 0 0 1
## 9 0 0 1 0 1 1 1 0
## 10 -2 -2 1 1 1 -2 1 1
## ESWATER ESWIN SMARTTHERM ELPAY ZELPAY NGPAY ZNGPAY LPGPAY ZLPGPAY FOPAY
## 1 0 0 0 1 0 1 0 -2 -2 -2
## 2 0 0 0 1 0 -2 -2 -2 -2 -2
## 3 0 0 0 1 0 1 0 -2 -2 -2
## 4 1 1 0 1 0 -2 -2 1 0 -2
## 5 0 0 0 1 0 1 0 -2 -2 -2
## 6 0 1 0 2 0 -2 -2 2 0 -2
## 7 0 0 0 1 0 1 0 -2 -2 -2
## 8 1 1 0 1 0 1 0 -2 -2 -2
## 9 0 1 0 1 0 -2 -2 -2 -2 1
## 10 1 0 0 1 0 -2 -2 -2 -2 -2
## ZFOPAY SMARTMETER INTDATA INTDATAACC HHSEX ZHHSEX HHAGE ZHHAGE EMPLOYHH
## 1 -2 1 1 0 2 0 42 0 1
## 2 -2 1 0 -2 1 0 60 0 2
## 3 -2 -9 -9 -9 1 0 73 0 1
## 4 -2 0 -2 -2 1 0 69 0 0
## 5 -2 0 -2 -2 2 0 51 0 1
## 6 -2 0 -2 -2 2 0 33 0 0
## 7 -2 0 -2 -2 2 0 53 0 1
## 8 -2 -9 -9 -9 1 0 67 0 0
## 9 0 0 -2 -2 1 0 56 0 1
## 10 -2 -9 -9 -9 1 0 48 0 1
## ZEMPLOYHH SDESCENT ZSDESCENT HOUSEHOLDER_RACE ZHOUSEHOLDER_RACE EDUCATION
## 1 0 0 0 1 0 2
## 2 0 0 0 1 0 2
## 3 0 0 0 1 0 1
## 4 0 0 0 3 0 4
## 5 0 0 0 4 0 2
## 6 0 0 0 1 0 1
## 7 0 0 0 1 0 5
## 8 0 0 0 1 0 2
## 9 0 0 0 1 0 3
## 10 0 0 0 1 0 4
## ZEDUCATION NHSLDMEM ZNHSLDMEM NUMADULT ZNUMADULT NUMCHILD ZNUMCHILD ATHOME
## 1 0 4 0 2 0 2 0 0
## 2 0 2 0 2 0 0 0 1
## 3 0 4 0 3 0 1 0 5
## 4 0 1 0 1 0 0 0 3
## 5 0 3 0 2 0 1 0 0
## 6 0 1 0 1 0 0 0 3
## 7 0 1 0 1 0 0 0 0
## 8 0 2 0 2 0 0 0 5
## 9 0 4 0 4 0 0 0 5
## 10 0 4 0 2 0 2 0 5
## ZATHOME MONEYPY ZMONEYPY ENERGYASST ZENERGYASST ENERGYASST11 ZENERGYASST11
## 1 0 8 1 0 0 -2 -2
## 2 0 2 0 0 1 -2 -2
## 3 0 2 0 0 0 -2 -2
## 4 0 3 0 0 0 -2 -2
## 5 0 3 0 0 0 -2 -2
## 6 0 1 0 0 0 -2 -2
## 7 0 4 0 0 0 -2 -2
## 8 0 3 0 1 0 1 0
## 9 0 5 1 0 0 -2 -2
## 10 0 6 0 0 0 -2 -2
## ENERGYASST12 ZENERGYASST12 ENERGYASST13 ZENERGYASST13 ENERGYASST14
## 1 -2 -2 -2 -2 -2
## 2 -2 -2 -2 -2 -2
## 3 -2 -2 -2 -2 -2
## 4 -2 -2 -2 -2 -2
## 5 -2 -2 -2 -2 -2
## 6 -2 -2 -2 -2 -2
## 7 -2 -2 -2 -2 -2
## 8 1 0 1 0 1
## 9 -2 -2 -2 -2 -2
## 10 -2 -2 -2 -2 -2
## ZENERGYASST14 ENERGYASST15 ZENERGYASST15 ENERGYASSTOTH ZENERGYASSTOTH SCALEB
## 1 -2 -2 -2 -2 -2 0
## 2 -2 -2 -2 -2 -2 0
## 3 -2 -2 -2 -2 -2 0
## 4 -2 -2 -2 -2 -2 0
## 5 -2 -2 -2 -2 -2 0
## 6 -2 -2 -2 -2 -2 0
## 7 -2 -2 -2 -2 -2 0
## 8 0 1 0 0 0 0
## 9 -2 -2 -2 -2 -2 0
## 10 -2 -2 -2 -2 -2 0
## ZSCALEB SCALEG ZSCALEG SCALEE ZSCALEE PAYHELP ZPAYHELP NOHEATBROKE
## 1 0 0 0 0 0 -2 -2 0
## 2 0 0 0 0 0 -2 -2 0
## 3 0 0 0 0 0 -2 -2 0
## 4 0 0 0 0 0 -2 -2 0
## 5 0 0 0 0 0 -2 -2 0
## 6 0 0 0 0 0 -2 -2 0
## 7 0 0 0 0 0 -2 -2 0
## 8 0 2 0 0 0 -2 -2 0
## 9 0 0 0 0 0 -2 -2 0
## 10 0 0 0 0 0 -2 -2 0
## ZNOHEATBROKE NOHEATEL ZNOHEATEL NOHEATNG ZNOHEATNG NOHEATBULK ZNOHEATBULK
## 1 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0
## 7 0 0 0 0 0 0 0
## 8 0 0 0 0 0 0 0
## 9 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0
## NOHEATDAYS ZNOHEATDAYS NOHEATHELP ZNOHEATHELP COLDMA ZCOLDMA NOACBROKE
## 1 -2 -2 -2 -2 0 0 0
## 2 -2 -2 -2 -2 0 0 1
## 3 -2 -2 -2 -2 0 0 0
## 4 -2 -2 -2 -2 0 0 0
## 5 -2 -2 -2 -2 0 0 0
## 6 -2 -2 -2 -2 0 0 0
## 7 -2 -2 -2 -2 0 0 0
## 8 -2 -2 -2 -2 0 0 0
## 9 -2 -2 -2 -2 0 0 0
## 10 -2 -2 -2 -2 0 0 0
## ZNOACBROKE NOACEL ZNOACEL NOACDAYS ZNOACDAYS NOACHELP ZNOACHELP HOTMA ZHOTMA
## 1 0 0 0 -2 -2 -2 -2 0 0
## 2 0 0 0 14 0 0 0 0 0
## 3 0 0 0 -2 -2 -2 -2 0 0
## 4 0 0 0 -2 -2 -2 -2 0 0
## 5 0 0 0 -2 -2 -2 -2 0 0
## 6 0 0 0 -2 -2 -2 -2 0 0
## 7 0 0 0 -2 -2 -2 -2 0 0
## 8 0 0 0 -2 -2 -2 -2 0 0
## 9 0 0 0 -2 -2 -2 -2 0 0
## 10 0 0 0 -2 -2 -2 -2 0 0
## USEEL ELWARM ELCOOL ELWATER ELFOOD ELOTHER USENG UGWARM UGWATER UGCOOK UGOTH
## 1 1 0 1 0 0 1 1 1 1 1 0
## 2 1 1 1 1 1 1 0 0 0 0 0
## 3 1 1 1 0 1 1 1 1 1 0 0
## 4 1 1 1 0 1 1 0 0 0 0 0
## 5 1 0 1 0 0 1 1 1 1 1 1
## 6 1 0 1 0 1 1 0 0 0 0 0
## 7 1 0 1 0 1 1 1 1 1 0 0
## 8 1 0 1 0 1 1 1 1 1 0 0
## 9 1 0 1 1 1 1 0 0 0 0 0
## 10 1 1 1 1 1 1 0 0 0 0 0
## USELP LPWARM LPWATER LPCOOK LPOTHER USEFO FOWARM FOWATER FOOTHER USEWOOD
## 1 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0
## 4 1 1 1 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0
## 6 1 1 1 0 0 0 0 0 0 0
## 7 0 0 0 0 0 0 0 0 0 0
## 8 0 0 0 0 0 0 0 0 0 0
## 9 0 0 0 0 0 1 1 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0
## WOODLOGS ZWOODLOGS WDPELLET ZWDPELLET WDOTHER WDWARM WDWATER USESOLAR
## 1 -2 -2 -2 -2 -2 0 0 0
## 2 -2 -2 -2 -2 -2 0 0 0
## 3 -2 -2 -2 -2 -2 0 0 0
## 4 -2 -2 -2 -2 -2 0 0 0
## 5 -2 -2 -2 -2 -2 0 0 0
## 6 -2 -2 -2 -2 -2 0 0 0
## 7 -2 -2 -2 -2 -2 0 0 0
## 8 -2 -2 -2 -2 -2 0 0 0
## 9 -2 -2 -2 -2 -2 0 0 0
## 10 -2 -2 -2 -2 -2 0 0 0
## SOLWATER SOLOTHER TOTCSQFT TOTHSQFT TOTSQFT_EN ZTOTSQFT_EN TOTUCSQFT
## 1 0 0 1808 1808 1808 1 400
## 2 0 0 759 759 759 1 0
## 3 0 0 1716 1430 2288 1 572
## 4 0 0 2573 2573 2573 0 400
## 5 0 0 933 933 1024 1 341
## 6 0 0 623 623 623 0 0
## 7 0 0 832 832 832 1 0
## 8 0 0 358 894 2682 0 2574
## 9 0 0 1900 1900 1900 1 400
## 10 0 0 1230 1230 1230 1 400
## TOTUSQFT NWEIGHT BRRWT1 BRRWT2 BRRWT3 BRRWT4 BRRWT5
## 1 400 12085.16 16555.311 5938.014 17725.586 17635.592 6032.801
## 2 0 14410.20 21486.287 19146.976 7320.376 23567.851 21926.554
## 3 858 23325.95 12297.437 36659.754 10476.220 10101.944 10291.104
## 4 400 12165.33 18553.959 5209.142 18041.476 5441.767 5815.606
## 5 341 16717.67 8075.744 8427.253 8335.558 23666.443 7674.488
## 6 0 26058.89 37004.087 34907.163 15314.899 33342.973 15332.520
## 7 0 45952.76 28077.392 71118.583 20106.888 68172.201 64424.780
## 8 2038 15280.98 22962.258 7067.475 25747.686 23842.533 7951.149
## 9 400 14034.71 6989.932 6954.717 7097.534 20873.026 8224.249
## 10 400 43359.16 73353.791 19161.079 16672.116 18551.024 81545.196
## BRRWT6 BRRWT7 BRRWT8 BRRWT9 BRRWT10 BRRWT11 BRRWT12
## 1 17095.361 6003.357 5994.109 5403.025 17569.634 16620.985 18815.84
## 2 7477.377 21544.004 8189.435 6616.364 7260.425 21416.978 21356.46
## 3 39732.041 11547.832 12678.450 38550.936 10754.494 44738.596 36050.57
## 4 4936.011 22136.115 18412.680 18910.608 6621.357 20070.603 23333.12
## 5 25586.815 23442.036 26866.377 8263.590 8210.546 8292.449 25607.72
## 6 14433.868 14590.917 32685.290 34548.360 33987.754 14716.949 32993.49
## 7 56769.939 22868.619 18690.821 27477.944 84209.790 22968.848 24615.35
## 8 26022.534 7984.623 6924.728 6676.508 23981.827 23687.481 24816.17
## 9 19524.236 21250.771 19723.164 5853.121 6368.905 7158.647 22569.41
## 10 63727.996 67868.970 19365.197 69789.937 64151.311 22341.634 67045.76
## BRRWT13 BRRWT14 BRRWT15 BRRWT16 BRRWT17 BRRWT18 BRRWT19
## 1 5660.360 20846.356 7251.431 6305.782 17556.877 5502.877 17874.881
## 2 7196.124 8036.602 21021.572 6465.171 7067.367 19909.662 7107.315
## 3 12305.637 36765.320 10564.846 10107.791 10336.977 40280.793 11448.875
## 4 18647.620 5191.860 17992.927 5299.330 5938.830 4850.357 21861.162
## 5 24152.584 25632.350 27171.846 7484.560 24470.176 8446.096 7888.243
## 6 36403.772 34958.618 14994.658 33526.677 15120.528 14266.978 14766.776
## 7 61313.403 24262.097 55609.969 31353.019 22056.806 21275.562 74685.129
## 8 22493.780 6726.533 25790.025 24029.772 6785.736 26481.625 7270.741
## 9 22462.298 22151.844 19986.184 7626.147 23286.179 6040.037 6770.155
## 10 19394.329 77443.655 83486.309 75867.969 17688.343 22775.673 21210.768
## BRRWT20 BRRWT21 BRRWT22 BRRWT23 BRRWT24 BRRWT25 BRRWT26
## 1 17451.189 17030.048 7275.919 6400.974 6151.373 6705.398 18503.444
## 2 19018.770 22595.883 21752.832 7500.772 7152.593 21478.760 18859.688
## 3 12917.423 38379.492 10780.913 44251.817 36588.754 12222.733 37014.112
## 4 18002.623 18250.704 6622.309 20087.161 22551.637 6004.821 21341.798
## 5 8830.740 26073.539 24965.832 26672.044 8319.093 7897.512 8402.612
## 6 32376.912 35316.988 33928.820 14958.953 32981.762 36774.465 34466.961
## 7 80576.478 70171.310 22270.785 73188.879 68396.990 62953.172 24897.669
## 8 6998.624 6977.522 22914.678 29645.954 23665.567 7703.731 25894.497
## 9 7081.399 19449.808 20462.225 20695.699 8116.199 7072.017 6841.469
## 10 74481.049 20238.178 21894.576 64258.484 22206.969 74876.470 19552.800
## BRRWT27 BRRWT28 BRRWT29 BRRWT30 BRRWT31 BRRWT32 BRRWT33
## 1 6297.252 6184.16 17977.633 6607.865 18256.832 18852.475 20878.198
## 2 7387.885 23539.85 21902.678 7631.062 22392.781 8173.637 6749.812
## 3 10440.073 10106.85 10218.847 39701.172 11106.929 12637.239 38222.725
## 4 6050.059 21256.76 18980.266 24295.083 5151.433 6426.631 6065.797
## 5 8305.634 23803.11 7608.350 26244.860 23640.612 27178.059 8290.589
## 6 14978.504 33670.62 15288.960 14115.451 14860.085 32563.263 34506.569
## 7 57145.428 31597.31 22155.613 20359.592 74020.876 80486.253 70908.259
## 8 6705.512 7264.53 25319.426 6729.783 24871.497 24607.200 24917.847
## 9 7132.981 20746.63 8248.711 19727.267 22132.579 19879.679 6001.543
## 10 16896.975 18447.38 80165.730 62841.057 66384.998 19228.345 70280.205
## BRRWT34 BRRWT35 BRRWT36 BRRWT37 BRRWT38 BRRWT39 BRRWT40
## 1 6389.165 6778.368 5860.646 19442.551 5341.872 15547.320 17705.661
## 2 7289.730 21361.095 20857.953 7287.374 7952.854 21287.488 6580.237
## 3 10721.895 45225.201 36294.411 12280.110 37137.315 10443.170 10101.028
## 4 16890.978 5495.542 5021.084 6042.867 21647.192 5943.324 21358.193
## 5 8236.846 8436.960 25605.331 24466.760 25387.180 27195.956 7526.401
## 6 34466.192 14458.219 33390.457 36530.039 34577.856 15025.949 33430.073
## 7 22522.778 72410.003 67914.777 28274.717 71482.426 19918.401 68816.641
## 8 7634.592 6162.223 7226.018 7498.270 24474.502 6818.859 7377.129
## 9 6387.133 7077.965 21887.893 22622.866 21913.571 20035.314 7734.796
## 10 64059.258 22149.905 67956.727 19064.605 76132.547 86621.608 76012.505
## BRRWT41 BRRWT42 BRRWT43 BRRWT44 BRRWT45 BRRWT46 BRRWT47
## 1 6247.487 20121.661 6082.009 6229.540 6435.381 15387.715 17357.448
## 2 7217.387 20227.646 7123.718 19074.912 22693.945 21767.523 7466.728
## 3 10072.374 39709.785 11412.832 12843.561 38828.054 10733.517 44079.443
## 4 19832.834 23857.718 4968.961 6301.514 5912.768 16933.112 5453.493
## 5 24139.195 8415.982 7738.799 8787.417 25444.675 24787.608 26505.393
## 6 15504.348 14217.577 14744.821 32279.325 34113.663 34112.285 15001.192
## 7 63505.766 56426.158 22523.866 18514.252 28017.120 86003.990 23545.722
## 8 21953.686 6722.853 22444.816 25701.458 26000.728 7220.457 7436.269
## 9 24383.780 6136.038 6763.337 7138.481 19723.178 20636.507 20440.237
## 10 17642.641 22877.687 21270.735 73263.887 20564.692 22333.501 65224.142
## BRRWT48 BRRWT49 BRRWT50 BRRWT51 BRRWT52 BRRWT53 BRRWT54
## 1 17755.367 6846.206 18367.765 6294.548 6189.488 18219.620 6499.157
## 2 7192.406 7330.267 7935.991 21284.438 6565.517 7090.929 20077.067
## 3 36095.733 31904.992 11473.823 40306.272 41226.171 39890.757 10735.878
## 4 5104.842 19286.819 5066.985 18125.456 5464.691 5938.565 4935.973
## 5 8227.120 8076.473 8437.369 8310.941 23695.683 7549.297 25512.206
## 6 33206.407 36945.264 34108.858 15064.418 33237.707 15537.102 14172.971
## 7 24656.044 28414.172 67864.258 27372.784 54139.011 77039.375 80214.483
## 8 7170.190 23572.987 6905.348 25888.357 23825.955 8074.230 25797.886
## 9 8228.444 7225.645 6808.247 7124.675 20786.453 8391.826 19275.006
## 10 22471.212 18856.740 77576.070 86456.278 75961.021 17722.157 22757.058
## BRRWT55 BRRWT56 BRRWT57 BRRWT58 BRRWT59 BRRWT60 BRRWT61
## 1 17820.585 18569.424 20761.907 6428.852 6768.231 5911.444 18925.21
## 2 7120.228 18743.339 23075.657 22033.524 7455.528 7178.817 21260.80
## 3 33985.034 33213.491 10758.639 37617.105 9669.441 11397.982 32806.24
## 4 22233.509 18220.653 19024.867 6709.704 20217.561 22954.863 18317.98
## 5 23256.642 26673.742 8226.518 8254.940 8167.152 25630.712 23986.69
## 6 14847.893 32109.295 34318.574 34350.705 14684.098 33029.070 36265.43
## 7 20919.053 20627.030 21916.828 69629.542 21635.238 23408.076 56517.85
## 8 8052.008 6750.158 6702.170 24316.350 23722.275 24510.466 22302.66
## 9 21347.066 19106.056 5967.114 6443.144 7162.832 22133.315 22016.57
## 10 21474.890 73252.820 20386.613 21899.578 64766.675 22016.568 75561.26
## BRRWT62 BRRWT63 BRRWT64 BRRWT65 BRRWT66 BRRWT67 BRRWT68
## 1 5344.386 15512.265 17562.181 6299.309 20108.439 6131.370 6279.366
## 2 19311.642 7370.956 23410.775 22271.962 7478.124 21903.295 8045.496
## 3 11365.521 40543.403 41214.707 39619.338 10658.259 33935.138 32836.115
## 4 5126.133 18103.390 5342.446 6109.292 4886.683 22277.019 18077.601
## 5 25434.756 26952.555 7537.584 24445.501 8510.726 7868.541 8892.969
## 6 34473.219 14795.522 33444.999 15539.092 14188.363 14722.228 32805.056
## 7 23771.932 79972.415 22753.570 25509.970 29619.173 67298.244 85030.593
## 8 6696.614 25946.092 24073.554 6937.478 26692.585 7330.036 7016.715
## 9 22113.644 20173.400 7651.129 24168.108 6065.427 6795.822 7102.605
## 10 19630.713 16831.266 18587.000 78449.616 64311.208 66528.944 19168.711
## BRRWT69 BRRWT70 BRRWT71 BRRWT72 BRRWT73 BRRWT74 BRRWT75
## 1 6573.608 15349.331 17246.880 17888.587 16771.843 5881.928 17695.101
## 2 6741.972 7209.181 21149.276 21104.178 7281.972 7989.091 21279.851
## 3 10640.151 37931.825 9777.236 11246.904 31915.927 11481.274 40590.631
## 4 18798.851 6543.978 19825.515 23085.536 6113.546 21409.382 6082.625
## 5 26143.480 24976.282 26679.512 8311.782 7975.864 8444.360 8273.016
## 6 35025.447 34328.756 14808.000 33422.257 37205.564 34487.504 14928.765
## 7 59098.651 20235.639 66700.570 67169.727 56360.788 23561.328 81316.384
## 8 7119.477 22922.023 29009.095 24140.918 7808.343 25938.381 6650.148
## 9 20168.290 20459.717 20134.655 8351.055 7187.068 6865.230 7124.160
## 10 69377.165 65009.632 22280.799 66775.203 19220.285 78263.799 84246.239
## BRRWT76 BRRWT77 BRRWT78 BRRWT79 BRRWT80 BRRWT81 BRRWT82
## 1 17373.137 6044.760 17014.47 6050.895 5889.57 5402.608 17313.850
## 2 6563.199 7100.971 20354.95 7161.521 18948.92 22955.422 21201.350
## 3 41214.892 40249.382 10605.48 34432.802 32965.77 10746.575 38172.243
## 4 21072.368 19140.833 24103.48 5037.624 6162.32 6045.608 16387.639
## 5 23497.871 7620.092 25619.90 23670.636 26803.82 8193.872 8123.054
## 6 33237.441 15431.557 14231.90 14464.968 32777.32 34521.261 34386.905
## 7 23612.380 25432.978 29567.16 66533.654 87689.72 59899.430 20685.944
## 8 7174.023 25465.458 6623.97 24223.907 23967.52 24754.636 7441.554
## 9 20771.644 8351.560 19819.22 21483.635 19037.60 5876.144 6195.761
## 10 78246.159 17504.329 22895.08 21200.682 74560.25 20430.789 22292.056
## BRRWT83 BRRWT84 BRRWT85 BRRWT86 BRRWT87 BRRWT88 BRRWT89
## 1 16937.998 18466.390 5675.986 21015.94 7256.770 6311.331 17711.27
## 2 7508.620 7130.909 21570.198 19300.38 7406.651 23379.950 22078.42
## 3 9567.936 11485.191 32355.198 11384.38 40354.809 41459.320 39725.75
## 4 5599.611 4966.972 5953.997 22241.02 6025.221 21026.244 19299.87
## 5 8294.433 25767.449 24432.227 25295.11 27262.893 7495.744 24432.43
## 6 14828.801 32831.705 36730.510 34555.56 14950.565 33125.225 15632.32
## 7 67255.385 69301.241 28716.309 66232.17 27006.191 54952.801 76400.62
## 8 6268.033 7134.579 7391.801 24872.34 6840.652 7255.295 21784.10
## 9 7192.953 21646.009 22359.598 22482.13 20187.617 7618.310 23814.97
## 10 63357.485 22175.492 73061.627 19059.81 16798.479 18771.780 81583.92
## BRRWT90 BRRWT91 BRRWT92 BRRWT93 BRRWT94 BRRWT95 BRRWT96
## 1 5517.710 17812.844 17483.082 17135.622 7305.994 6311.889 6200.078
## 2 7492.123 21567.224 8028.530 6600.739 7242.987 21107.678 21255.527
## 3 10544.423 34614.139 33074.557 10837.952 37756.114 9673.744 11342.911
## 4 23766.895 4923.027 6302.794 5957.332 16923.547 5483.992 5123.054
## 5 8370.279 7832.980 8760.150 25890.094 24907.848 26484.616 8290.542
## 6 14448.819 14517.486 32305.613 34995.513 34364.739 14823.531 32693.288
## 7 80513.846 20690.202 20963.533 21964.476 68862.319 21529.855 23930.526
## 8 6713.814 22238.068 25589.692 26260.344 7218.586 7357.843 7163.839
## 9 6214.182 6750.659 7108.469 19806.235 20622.657 20133.676 8223.503
## 10 64836.773 67226.823 19585.029 68982.875 64148.646 22349.228 67786.226
## CDD30YR CDD65 CDD80 CLIMATE_REGION_PUB IECC_CLIMATE_PUB HDD30YR HDD65 HDD50
## 1 1332 1768 118 Hot-Dry/Mixed-Dry 3B-4B 2640 2031 213
## 2 2494 2795 417 Hot-Humid 1A-2A 2178 1915 466
## 3 2059 2235 126 Mixed-Humid 3A 2714 2263 634
## 4 1327 1374 63 Mixed-Humid 4A 4205 3754 1321
## 5 871 993 9 Cold/Very Cold 5A 5397 5401 2462
## 6 396 408 10 Cold/Very Cold 6A-6B 7224 7597 3684
## 7 2546 2582 239 Hot-Humid 3A 1795 1579 353
## 8 597 673 0 Cold/Very Cold 6A-6B 7191 6560 3555
## 9 820 1083 52 Cold/Very Cold 5A 5583 5301 2391
## 10 3022 3390 598 Hot-Humid 1A-2A 1528 1400 241
## GNDHDD65 WSF OA_LAT GWT DBT1 DBT99 KWH KWHSPH KWHCOL KWHWTH
## 1 1666.36 0.50 0.003 62.27 97.9 33.0 5270.742 0.000 1991.505 0.000
## 2 871.92 0.40 13.189 67.36 96.8 31.7 12173.000 3390.979 2223.717 2089.679
## 3 1860.23 0.37 10.271 62.32 92.5 24.9 19655.394 3651.818 6837.336 0.000
## 4 3354.35 0.46 7.157 56.76 91.3 15.9 9852.535 1412.232 3534.948 0.000
## 5 5461.22 0.50 4.527 50.04 88.4 15.5 3115.655 0.000 332.701 0.000
## 6 7893.00 0.50 2.334 43.38 84.5 0.4 2777.000 0.000 157.203 0.000
## 7 698.82 0.43 19.303 69.19 86.2 34.6 2397.758 0.000 934.817 0.000
## 8 7232.66 0.61 2.011 45.18 86.6 -1.6 13890.899 0.000 676.650 0.000
## 9 5471.12 0.50 4.562 50.01 88.4 15.5 10422.424 0.000 804.897 3335.301
## 10 410.71 0.45 12.178 70.88 97.2 32.7 18505.802 2570.243 3102.518 3164.641
## KWHRFG KWHRFG1 KWHRFG2 KWHFRZ KWHCOK KWHMICRO KWHCW KWHCDR KWHDWH
## 1 422.951 422.951 0.000 272.055 0.000 100.304 24.930 506.178 185.124
## 2 752.709 752.709 0.000 270.167 295.082 197.841 0.000 0.000 0.000
## 3 1465.044 1093.210 371.834 0.000 1362.857 145.729 26.326 533.326 224.070
## 4 639.980 436.886 203.094 483.588 112.720 0.000 38.956 498.861 0.000
## 5 311.469 270.185 41.284 0.000 0.000 56.869 28.387 293.780 0.000
## 6 227.265 227.265 0.000 0.000 317.748 30.898 0.000 0.000 0.000
## 7 469.290 469.290 0.000 0.000 117.600 96.819 15.823 0.000 0.000
## 8 1032.569 1032.569 0.000 487.699 527.720 547.651 72.458 738.751 133.558
## 9 1241.351 483.232 758.119 262.156 230.676 117.623 15.296 313.609 150.466
## 10 750.257 750.257 0.000 0.000 303.823 145.645 236.660 2996.609 536.387
## KWHLGT KWHTVREL KWHTV1 KWHTV2 KWHAHUHEAT KWHAHUCOL KWHEVAPCOL KWHCFAN
## 1 409.651 261.761 115.220 20.904 133.102 101.854 0 348.590
## 2 1109.597 445.243 303.136 20.802 0.000 0.000 0 418.690
## 3 917.391 1857.856 297.742 114.187 200.526 264.038 0 1127.715
## 4 484.534 480.339 65.107 15.047 499.514 196.457 0 912.032
## 5 604.038 358.968 50.996 81.677 104.540 15.978 0 99.024
## 6 263.456 676.780 117.668 0.000 65.208 0.000 0 0.000
## 7 172.427 264.259 36.174 0.000 24.613 45.123 0 25.584
## 8 215.597 713.783 324.761 16.201 465.659 0.000 0 630.980
## 9 955.390 1550.730 372.146 108.726 225.954 41.062 0 284.833
## 10 2340.238 1149.311 189.129 68.834 37.881 150.168 0 235.539
## KWHDHUM KWHHUM KWHPLPMP KWHHTBPMP KWHHTBHEAT KWHNEC BTUEL BTUELSPH
## 1 0.000 0.000 0 0 0 512.736 17983.771 0.000
## 2 0.000 44.696 0 0 0 934.599 41534.000 11570.020
## 3 0.000 0.000 0 0 0 1041.363 67064.204 12460.003
## 4 0.000 0.000 0 0 0 558.375 33616.851 4818.534
## 5 156.175 0.000 0 0 0 753.726 10630.615 0.000
## 6 0.000 0.000 0 0 0 1038.441 9475.000 0.000
## 7 0.000 0.000 0 0 0 231.401 8181.149 0.000
## 8 2575.806 0.000 0 0 0 5072.016 47395.746 0.000
## 9 0.000 0.000 0 0 0 893.079 35561.312 0.000
## 10 0.000 0.000 0 0 0 785.883 63141.798 8769.670
## BTUELCOL BTUELWTH BTUELRFG BTUELRFG1 BTUELRFG2 BTUELFRZ BTUELCOK
## 1 6795.016 0.000 1443.108 1443.108 0.000 928.253 0.000
## 2 7587.322 7129.985 2568.243 2568.243 0.000 921.810 1006.820
## 3 23328.992 0.000 4998.729 3730.031 1268.698 0.000 4650.068
## 4 12061.243 0.000 2183.613 1490.655 692.958 1650.001 384.600
## 5 1135.176 0.000 1062.732 921.870 140.862 0.000 0.000
## 6 536.377 0.000 775.428 775.428 0.000 0.000 1084.156
## 7 3189.596 0.000 1601.216 1601.216 0.000 0.000 401.253
## 8 2308.731 0.000 3523.125 3523.125 0.000 1664.029 1800.581
## 9 2746.309 11380.048 4235.489 1648.789 2586.701 894.478 787.067
## 10 10585.792 10797.754 2559.876 2559.876 0.000 0.000 1036.644
## BTUELMICRO BTUELCW BTUELCDR BTUELDWH BTUELLGT BTUELTVREL BTUELTV1 BTUELTV2
## 1 342.236 85.063 1727.078 631.643 1397.731 893.129 393.131 71.324
## 2 675.033 0.000 0.000 0.000 3785.945 1519.169 1034.300 70.976
## 3 497.226 89.824 1819.709 764.525 3130.138 6339.003 1015.896 389.606
## 4 0.000 132.916 1702.112 0.000 1653.232 1638.915 222.145 51.340
## 5 194.038 96.856 1002.376 0.000 2060.978 1224.799 173.998 278.682
## 6 105.424 0.000 0.000 0.000 898.912 2309.173 401.483 0.000
## 7 330.348 53.989 0.000 0.000 588.322 901.652 123.426 0.000
## 8 1868.585 247.227 2520.619 455.701 735.618 2435.429 1108.085 55.278
## 9 401.328 52.191 1070.033 513.390 3259.791 5291.091 1269.762 370.973
## 10 496.941 807.483 10224.429 1830.152 7984.893 3921.450 645.308 234.862
## BTUELAHUHEAT BTUELAHUCOL BTUELEVAPCOL BTUELCFAN BTUELDHUM BTUELHUM
## 1 454.143 347.526 0 1189.388 0.000 0.000
## 2 0.000 0.000 0 1428.570 0.000 152.503
## 3 684.194 900.897 0 3847.765 0.000 0.000
## 4 1704.342 670.313 0 3111.853 0.000 0.000
## 5 356.691 54.517 0 337.870 532.870 0.000
## 6 222.490 0.000 0 0.000 0.000 0.000
## 7 83.981 153.961 0 87.293 0.000 0.000
## 8 1588.829 0.000 0 2152.904 8788.649 0.000
## 9 770.955 140.105 0 971.850 0.000 0.000
## 10 129.248 512.373 0 803.660 0.000 0.000
## BTUELPLPMP BTUELHTBPMP BTUELHTBHEAT BTUELNEC DOLLAREL DOLELSPH DOLELCOL
## 1 0 0 0 1749.457 967.23 0.00 365.46
## 2 0 0 0 3188.852 1366.00 380.52 249.54
## 3 0 0 0 3553.130 2428.08 451.12 844.63
## 4 0 0 0 1905.175 1313.12 188.22 471.13
## 5 0 0 0 2571.711 581.07 0.00 62.05
## 6 0 0 0 3543.161 494.00 0.00 27.96
## 7 0 0 0 789.539 371.61 0.00 144.88
## 8 0 0 0 17305.718 1737.17 0.00 84.62
## 9 0 0 0 3047.186 1531.91 0.00 118.31
## 10 0 0 0 2681.434 1973.72 274.13 330.90
## DOLELWTH DOLELRFG DOLELRFG1 DOLELRFG2 DOLELFRZ DOLELCOK DOLELMICRO DOLELCW
## 1 0.00 77.62 77.62 0.00 49.92 0.00 18.41 4.57
## 2 234.49 84.47 84.47 0.00 30.32 33.11 22.20 0.00
## 3 0.00 180.98 135.05 45.93 0.00 168.36 18.00 3.25
## 4 0.00 85.29 58.23 27.07 64.45 15.02 0.00 5.19
## 5 0.00 58.09 50.39 7.70 0.00 0.00 10.61 5.29
## 6 0.00 40.43 40.43 0.00 0.00 56.52 5.50 0.00
## 7 0.00 72.73 72.73 0.00 0.00 18.23 15.01 2.45
## 8 0.00 129.13 129.13 0.00 60.99 66.00 68.49 9.06
## 9 490.23 182.46 71.03 111.43 38.53 33.91 17.29 2.25
## 10 337.52 80.02 80.02 0.00 0.00 32.40 15.53 25.24
## DOLELCDR DOLELDWH DOLELLGT DOLELTVREL DOLELTV1 DOLELTV2 DOLELAHUHEAT
## 1 92.89 33.97 75.18 48.04 21.07 3.82 24.43
## 2 0.00 0.00 124.51 49.96 34.02 2.33 0.00
## 3 65.88 27.68 113.33 229.51 36.78 14.11 24.77
## 4 66.49 0.00 64.58 64.02 8.68 2.01 66.57
## 5 54.79 0.00 112.65 66.95 9.51 15.23 19.50
## 6 0.00 0.00 46.87 120.39 20.93 0.00 11.60
## 7 0.00 0.00 26.72 40.96 5.61 0.00 3.81
## 8 92.39 16.70 26.96 89.26 40.56 2.02 58.23
## 9 46.09 22.12 140.43 227.93 54.70 15.98 33.21
## 10 319.60 57.21 249.60 122.58 20.15 7.33 4.04
## DOLELAHUCOL DOLELEVAPCOL DOLELCFAN DOLELDHUM DOLELHUM DOLELPLPMP DOLELHTBPMP
## 1 18.69 0 63.97 0.00 0.00 0 0
## 2 0.00 0 46.98 0.00 5.02 0 0
## 3 32.62 0 139.31 0.00 0.00 0 0
## 4 26.18 0 121.55 0.00 0.00 0 0
## 5 2.98 0 18.47 29.13 0.00 0 0
## 6 0.00 0 0.00 0.00 0.00 0 0
## 7 6.99 0 3.97 0.00 0.00 0 0
## 8 0.00 0 78.91 322.13 0.00 0 0
## 9 6.04 0 41.87 0.00 0.00 0 0
## 10 16.02 0 25.12 0.00 0.00 0 0
## DOLELHTBHEAT DOLELNEC CUFEETNG CUFEETNGSPH CUFEETNGWTH CUFEETNGCOK
## 1 0 94.09 299.946 120.689 169.719 9.538
## 2 0 104.88 0.000 0.000 0.000 0.000
## 3 0 128.64 294.420 110.238 184.182 0.000
## 4 0 74.42 0.000 0.000 0.000 0.000
## 5 0 140.57 252.370 51.928 168.538 22.034
## 6 0 184.73 0.000 0.000 0.000 0.000
## 7 0 35.86 432.740 133.594 100.652 0.000
## 8 0 634.30 824.741 653.950 170.792 0.000
## 9 0 131.27 0.000 0.000 0.000 0.000
## 10 0 83.82 0.000 0.000 0.000 0.000
## CUFEETNGCDR CUFEETNGPLHEAT CUFEETNGHTBHEAT CUFEETNGNEC BTUNG BTUNGSPH
## 1 0 0 0 0.000 30990.80 12469.727
## 2 0 0 0 0.000 0.00 0.000
## 3 0 0 0 0.000 29483.96 11039.514
## 4 0 0 0 0.000 0.00 0.000
## 5 0 0 0 9.869 25951.53 5339.841
## 6 0 0 0 0.000 0.00 0.000
## 7 0 0 0 198.495 44480.57 13731.855
## 8 0 0 0 0.000 83739.34 66398.170
## 9 0 0 0 0.000 0.00 0.000
## 10 0 0 0 0.000 0.00 0.000
## BTUNGWTH BTUNGCOK BTUNGCDR BTUNGPLHEAT BTUNGHTBHEAT BTUNGNEC DOLLARNG
## 1 17535.62 985.448 0 0 0 0.000 438.87
## 2 0.00 0.000 0 0 0 0.000 0.00
## 3 18444.44 0.000 0 0 0 0.000 400.76
## 4 0.00 0.000 0 0 0 0.000 0.00
## 5 17331.01 2265.816 0 0 0 1014.863 329.82
## 6 0.00 0.000 0 0 0 0.000 0.00
## 7 10345.80 0.000 0 0 0 20402.920 643.57
## 8 17341.17 0.000 0 0 0 0.000 646.91
## 9 0.00 0.000 0 0 0 0.000 0.00
## 10 0.00 0.000 0 0 0 0.000 0.00
## DOLNGSPH DOLNGWTH DOLNGCOK DOLNGCDR DOLNGPLHEAT DOLNGHTBHEAT DOLNGNEC
## 1 176.59 248.33 13.96 0 0 0 0.0
## 2 0.00 0.00 0.00 0 0 0 0.0
## 3 150.06 250.71 0.00 0 0 0 0.0
## 4 0.00 0.00 0.00 0 0 0 0.0
## 5 67.87 220.26 28.80 0 0 0 12.9
## 6 0.00 0.00 0.00 0 0 0 0.0
## 7 198.68 149.69 0.00 0 0 0 295.2
## 8 512.95 133.97 0.00 0 0 0 0.0
## 9 0.00 0.00 0.00 0 0 0 0.0
## 10 0.00 0.00 0.00 0 0 0 0.0
## GALLONLP GALLONLPSPH GALLONLPWTH GALLONLPCOK GALLONLPCDR GALLONLPNEC
## 1 0.000 0.000 0.000 0 0 0
## 2 0.000 0.000 0.000 0 0 0
## 3 0.000 0.000 0.000 0 0 0
## 4 609.498 521.055 88.443 0 0 0
## 5 0.000 0.000 0.000 0 0 0
## 6 227.947 111.345 116.602 0 0 0
## 7 0.000 0.000 0.000 0 0 0
## 8 0.000 0.000 0.000 0 0 0
## 9 0.000 0.000 0.000 0 0 0
## 10 0.000 0.000 0.000 0 0 0
## BTULP BTULPSPH BTULPWTH BTULPCOK BTULPCDR BTULPNEC DOLLARLP DOLLPSPH
## 1 0.00 0.00 0.000 0 0 0 0.00 0.00
## 2 0.00 0.00 0.000 0 0 0 0.00 0.00
## 3 0.00 0.00 0.000 0 0 0 0.00 0.00
## 4 55667.49 47589.65 8077.839 0 0 0 789.86 675.25
## 5 0.00 0.00 0.000 0 0 0 0.00 0.00
## 6 20819.15 10169.51 10649.641 0 0 0 545.99 266.70
## 7 0.00 0.00 0.000 0 0 0 0.00 0.00
## 8 0.00 0.00 0.000 0 0 0 0.00 0.00
## 9 0.00 0.00 0.000 0 0 0 0.00 0.00
## 10 0.00 0.00 0.000 0 0 0 0.00 0.00
## DOLLPWTH DOLLPCOK DOLLPCDR DOLLPNEC GALLONFO GALLONFOSPH GALLONFOWTH
## 1 0.00 0 0 0 0.000 0.000 0
## 2 0.00 0 0 0 0.000 0.000 0
## 3 0.00 0 0 0 0.000 0.000 0
## 4 114.62 0 0 0 0.000 0.000 0
## 5 0.00 0 0 0 0.000 0.000 0
## 6 279.29 0 0 0 0.000 0.000 0
## 7 0.00 0 0 0 0.000 0.000 0
## 8 0.00 0 0 0 0.000 0.000 0
## 9 0.00 0 0 0 422.853 422.853 0
## 10 0.00 0 0 0 0.000 0.000 0
## GALLONFONEC BTUFO BTUFOSPH BTUFOWTH BTUFONEC DOLLARFO DOLFOSPH DOLFOWTH
## 1 0 0.00 0.00 0 0 0.00 0.00 0
## 2 0 0.00 0.00 0 0 0.00 0.00 0
## 3 0 0.00 0.00 0 0 0.00 0.00 0
## 4 0 0.00 0.00 0 0 0.00 0.00 0
## 5 0 0.00 0.00 0 0 0.00 0.00 0
## 6 0 0.00 0.00 0 0 0.00 0.00 0
## 7 0 0.00 0.00 0 0 0.00 0.00 0
## 8 0 0.00 0.00 0 0 0.00 0.00 0
## 9 0 58122.09 58122.09 0 0 953.05 953.05 0
## 10 0 0.00 0.00 0 0 0.00 0.00 0
## DOLFONEC TOTALBTU TOTALDOL TOTALBTUSPH TOTALDOLSPH TOTALBTUWTH TOTALDOLWTH
## 1 0 48974.57 1406.10 12469.727 176.59 17535.625 248.33
## 2 0 41534.00 1366.00 11570.020 380.52 7129.985 234.49
## 3 0 96548.16 2828.84 23499.517 601.17 18444.442 250.71
## 4 0 89284.35 2102.98 52408.189 863.46 8077.839 114.62
## 5 0 36582.15 910.89 5339.841 67.87 17331.011 220.26
## 6 0 30294.15 1039.99 10169.506 266.70 10649.641 279.29
## 7 0 52661.72 1015.17 13731.855 198.68 10345.797 149.69
## 8 0 131135.09 2384.08 66398.170 512.95 17341.172 133.97
## 9 0 93683.40 2484.96 58122.088 953.05 11380.048 490.23
## 10 0 63141.80 1973.72 8769.670 274.13 10797.754 337.52
## TOTALBTUCOK TOTALDOLCOK TOTALBTUCDR TOTALDOLCDR TOTALBTUPL TOTALDOLPL
## 1 985.448 13.96 1727.078 92.89 0 0
## 2 1006.820 33.11 0.000 0.00 0 0
## 3 4650.068 168.36 1819.709 65.88 0 0
## 4 384.600 15.02 1702.112 66.49 0 0
## 5 2265.816 28.80 1002.376 54.79 0 0
## 6 1084.156 56.52 0.000 0.00 0 0
## 7 401.253 18.23 0.000 0.00 0 0
## 8 1800.581 66.00 2520.619 92.39 0 0
## 9 787.067 33.91 1070.033 46.09 0 0
## 10 1036.644 32.40 10224.429 319.60 0 0
## TOTALBTUHTB TOTALDOLHTB TOTALBTUNEC TOTALDOLNEC WOODAMT ZWOODAMT WOODBTU
## 1 0 0 1749.457 94.09 -2 -2 0
## 2 0 0 3188.852 104.88 -2 -2 0
## 3 0 0 3553.130 128.64 -2 -2 0
## 4 0 0 1905.175 74.42 -2 -2 0
## 5 0 0 3586.574 153.47 -2 -2 0
## 6 0 0 3543.161 184.73 -2 -2 0
## 7 0 0 21192.459 331.06 -2 -2 0
## 8 0 0 17305.718 634.30 -2 -2 0
## 9 0 0 3047.186 131.27 -2 -2 0
## 10 0 0 2681.434 83.82 -2 -2 0
## PELLETAMT ZPELLETAMT PELLETBTU ELXBTU PERIODEL ZELAMOUNT NGXBTU PERIODNG
## 1 -2 -2 0 3.412 1 0 103.32 1
## 2 -2 -2 0 3.412 5 1 NA -2
## 3 -2 -2 0 3.412 1 0 100.14 1
## 4 -2 -2 0 3.412 1 0 NA -2
## 5 -2 -2 0 3.412 1 0 102.83 1
## 6 -2 -2 0 3.412 5 1 NA -2
## 7 -2 -2 0 3.412 1 0 102.79 1
## 8 -2 -2 0 3.412 1 0 101.53 1
## 9 -2 -2 0 3.412 1 0 NA -2
## 10 -2 -2 0 3.412 1 0 NA -2
## ZNGAMOUNT FOXBTU PERIODFO ZFOAMOUNT LPXBTU PERIODLP ZLPAMOUNT
## 1 0 137.45 -2 -2 91.33 -2 -2
## 2 -2 137.45 -2 -2 91.33 -2 -2
## 3 0 137.45 -2 -2 91.33 -2 -2
## 4 -2 137.45 -2 -2 91.33 2 0
## 5 0 137.45 -2 -2 91.33 -2 -2
## 6 -2 137.45 -2 -2 91.33 5 1
## 7 0 137.45 -2 -2 91.33 -2 -2
## 8 0 137.45 -2 -2 91.33 -2 -2
## 9 -2 137.45 1 0 91.33 -2 -2
## 10 -2 137.45 -2 -2 91.33 -2 -2colnames(energy, 10)## [1] "DOEID" "REGIONC" "DIVISION"
## [4] "METROMICRO" "UATYP10" "TYPEHUQ"
## [7] "ZTYPEHUQ" "CELLAR" "ZCELLAR"
## [10] "BASEFIN" "ZBASEFIN" "ATTIC"
## [13] "ZATTIC" "ATTICFIN" "ZATTICFIN"
## [16] "STORIES" "ZSTORIES" "PRKGPLC1"
## [19] "ZPRKGPLC1" "SIZEOFGARAGE" "ZSIZEOFGARAGE"
## [22] "KOWNRENT" "ZKOWNRENT" "YEARMADERANGE"
## [25] "ZYEARMADERANGE" "OCCUPYYRANGE" "ZOCCUPYYRANGE"
## [28] "STUDIO" "ZSTUDIO" "BEDROOMS"
## [31] "ZBEDROOMS" "NCOMBATH" "ZNCOMBATH"
## [34] "NHAFBATH" "ZNHAFBATH" "OTHROOMS"
## [37] "ZOTHROOMS" "TOTROOMS" "ZTOTROOMS"
## [40] "WALLTYPE" "ZWALLTYPE" "ROOFTYPE"
## [43] "ZROOFTYPE" "HIGHCEIL" "ZHIGHCEIL"
## [46] "DOOR1SUM" "ZDOOR1SUM" "WINDOWS"
## [49] "ZWINDOWS" "TYPEGLASS" "ZTYPEGLASS"
## [52] "WINFRAME" "ZWINFRAME" "ADQINSUL"
## [55] "ZADQINSUL" "DRAFTY" "ZDRAFTY"
## [58] "UGASHERE" "ZUGASHERE" "SWIMPOOL"
## [61] "ZSWIMPOOL" "MONPOOL" "ZMONPOOL"
## [64] "POOL" "ZPOOL" "FUELPOOL"
## [67] "ZFUELPOOL" "RECBATH" "ZRECBATH"
## [70] "MONTUB" "ZMONTUB" "FUELTUB"
## [73] "ZFUELTUB" "OUTLET" "ZOUTLET"
## [76] "ALTFUELPEV" "ZALTFUELPEV" "BACKUP"
## [79] "ZBACKUP" "SOLAR" "NUMFRIG"
## [82] "ZNUMFRIG" "SIZRFRI1" "ZSIZRFRI1"
## [85] "TYPERFR1" "ZTYPERFR1" "AGERFRI1"
## [88] "ZAGERFRI1" "ICE" "ZICE"
## [91] "SIZRFRI2" "ZSIZRFRI2" "TYPERFR2"
## [94] "ZTYPERFR2" "AGERFRI2" "ZAGERFRI2"
## [97] "LOCRFRI2" "ZLOCRFRI2" "NUMFREEZ"
## [100] "ZNUMFREEZ" "UPRTFRZR" "ZUPRTFRZR"
## [103] "SIZFREEZ" "ZSIZFREEZ" "AGEFRZR"
## [106] "ZAGEFRZR" "STOVEN" "ZSTOVEN"
## [109] "STOVENFUEL" "ZSTOVENFUEL" "DUALCOOKTFUEL"
## [112] "ZDUALCOOKTFUEL" "DUALOVENFUEL" "ZDUALOVENFUEL"
## [115] "COOKTUSE" "ZCOOKTUSE" "OVENUSE"
## [118] "ZOVENUSE" "STOVE" "ZSTOVE"
## [121] "STOVEFUEL" "ZSTOVEFUEL" "SEPCOOKTUSE"
## [124] "ZSEPCOOKTUSE" "OVEN" "ZOVEN"
## [127] "OVENFUEL" "ZOVENFUEL" "SEPOVENUSE"
## [130] "ZSEPOVENUSE" "MICRO" "ZMICRO"
## [133] "AMTMICRO" "ZAMTMICRO" "OUTGRILL"
## [136] "ZOUTGRILL" "OUTGRILLFUEL" "ZOUTGRILLFUEL"
## [139] "NUMMEAL" "ZNUMMEAL" "TOAST"
## [142] "ZTOAST" "TOASTOVN" "ZTOASTOVN"
## [145] "COFFEE" "ZCOFFEE" "CROCKPOT"
## [148] "ZCROCKPOT" "FOODPROC" "ZFOODPROC"
## [151] "RICECOOK" "ZRICECOOK" "BLENDER"
## [154] "ZBLENDER" "APPOTHER" "ZAPPOTHER"
## [157] "DISHWASH" "ZDISHWASH" "DWASHUSE"
## [160] "ZDWASHUSE" "DWCYCLE" "ZDWCYCLE"
## [163] "AGEDW" "ZAGEDW" "CWASHER"
## [166] "ZCWASHER" "TOPFRONT" "ZTOPFRONT"
## [169] "WASHLOAD" "ZWASHLOAD" "WASHTEMP"
## [172] "ZWASHTEMP" "RNSETEMP" "ZRNSETEMP"
## [175] "AGECWASH" "ZAGECWASH" "DRYER"
## [178] "ZDRYER" "DRYRFUEL" "ZDRYRFUEL"
## [181] "DRYRUSE" "ZDRYRUSE" "AGECDRYER"
## [184] "ZAGECDRYER" "TVCOLOR" "ZTVCOLOR"
## [187] "TVSIZE1" "ZTVSIZE1" "TVTYPE1"
## [190] "ZTVTYPE1" "TVONWD1" "ZTVONWD1"
## [193] "TVONWE1" "ZTVONWE1" "TVSIZE2"
## [196] "ZTVSIZE2" "TVTYPE2" "ZTVTYPE2"
## [199] "TVONWD2" "ZTVONWD2" "TVONWE2"
## [202] "ZTVONWE2" "CABLESAT" "ZCABLESAT"
## [205] "COMBODVR" "ZCOMBODVR" "SEPDVR"
## [208] "ZSEPDVR" "PLAYSTA" "ZPLAYSTA"
## [211] "DVD" "ZDVD" "VCR"
## [214] "ZVCR" "INTSTREAM" "ZINTSTREAM"
## [217] "TVAUDIOSYS" "ZTVAUDIOSYS" "DESKTOP"
## [220] "ZDESKTOP" "NUMLAPTOP" "ZNUMLAPTOP"
## [223] "NUMTABLET" "ZNUMTABLET" "ELPERIPH"
## [226] "ZELPERIPH" "NUMSMPHONE" "ZNUMSMPHONE"
## [229] "CELLPHONE" "ZCELLPHONE" "INTERNET"
## [232] "ZINTERNET" "INWIRELESS" "ZINWIRELESS"
## [235] "HEATHOME" "ZHEATHOME" "DNTHEAT"
## [238] "ZDNTHEAT" "EQUIPM" "ZEQUIPM"
## [241] "FUELHEAT" "ZFUELHEAT" "EQUIPAGE"
## [244] "ZEQUIPAGE" "THERMAIN" "ZTHERMAIN"
## [247] "PROTHERM" "ZPROTHERM" "EQUIPMUSE"
## [250] "ZEQUIPMUSE" "TEMPHOME" "ZTEMPHOME"
## [253] "TEMPGONE" "ZTEMPGONE" "TEMPNITE"
## [256] "ZTEMPNITE" "EQUIPAUX" "ZEQUIPAUX"
## [259] "EQUIPAUXTYPE" "ZEQUIPAUXTYPE" "FUELAUX"
## [262] "ZFUELAUX" "BASEHEAT" "ZBASEHEAT"
## [265] "ATTCHEAT" "ZATTCHEAT" "GARGHEAT"
## [268] "ZGARGHEAT" "MOISTURE" "ZMOISTURE"
## [271] "USEMOISTURE" "ZUSEMOISTURE" "AIRCOND"
## [274] "ZAIRCOND" "COOLTYPE" "ZCOOLTYPE"
## [277] "CENACHP" "ZCENACHP" "AGECENAC"
## [280] "ZAGECENAC" "THERMAINAC" "ZTHERMAINAC"
## [283] "PROTHERMAC" "ZPROTHERMAC" "USECENAC"
## [286] "ZUSECENAC" "NUMBERAC" "ZNUMBERAC"
## [289] "WWACAGE" "ZWWACAGE" "USEWWAC"
## [292] "ZUSEWWAC" "TEMPHOMEAC" "ZTEMPHOMEAC"
## [295] "TEMPGONEAC" "ZTEMPGONEAC" "TEMPNITEAC"
## [298] "ZTEMPNITEAC" "BASECOOL" "ZBASECOOL"
## [301] "ATTCCOOL" "ZATTCCOOL" "GARGCOOL"
## [304] "ZGARGCOOL" "SWAMPCOL" "ZSWAMPCOL"
## [307] "NUMCFAN" "ZNUMCFAN" "NUMFLOORFAN"
## [310] "ZNUMFLOORFAN" "NUMWHOLEFAN" "ZNUMWHOLEFAN"
## [313] "NUMATTICFAN" "ZNUMATTICFAN" "NOTMOIST"
## [316] "ZNOTMOIST" "USENOTMOIST" "ZUSENOTMOIST"
## [319] "FUELH2O" "ZFUELH2O" "H2OHEATAPT"
## [322] "ZH2OHEATAPT" "WHEATAGE" "ZWHEATAGE"
## [325] "WHEATSIZ" "ZWHEATSIZ" "MORETHAN1H2O"
## [328] "ZMORETHAN1H2O" "FUELH2O2" "ZFUELH2O2"
## [331] "LGTINNUM" "ZLGTINNUM" "LGTIN4"
## [334] "ZLGTIN4" "LGTINCAN" "ZLGTINCAN"
## [337] "LGTINCFL" "ZLGTINCFL" "LGTINLED"
## [340] "ZLGTINLED" "LGTINCNTL" "ZLGTINCNTL"
## [343] "LGTOUTNUM" "ZLGTOUTNUM" "LGTOUTCNTL"
## [346] "ZLGTOUTCNTL" "AUDIT" "AUDITCHG"
## [349] "EELIGHTS" "FREEAUDIT" "REBATEAPP"
## [352] "RECYCAPP" "TAXCREDITAPP" "BENOTHER"
## [355] "ESCWASH" "ESDISHW" "ESDRYER"
## [358] "ESFREEZE" "ESFRIG" "ESLIGHT"
## [361] "ESWATER" "ESWIN" "SMARTTHERM"
## [364] "ELPAY" "ZELPAY" "NGPAY"
## [367] "ZNGPAY" "LPGPAY" "ZLPGPAY"
## [370] "FOPAY" "ZFOPAY" "SMARTMETER"
## [373] "INTDATA" "INTDATAACC" "HHSEX"
## [376] "ZHHSEX" "HHAGE" "ZHHAGE"
## [379] "EMPLOYHH" "ZEMPLOYHH" "SDESCENT"
## [382] "ZSDESCENT" "HOUSEHOLDER_RACE" "ZHOUSEHOLDER_RACE"
## [385] "EDUCATION" "ZEDUCATION" "NHSLDMEM"
## [388] "ZNHSLDMEM" "NUMADULT" "ZNUMADULT"
## [391] "NUMCHILD" "ZNUMCHILD" "ATHOME"
## [394] "ZATHOME" "MONEYPY" "ZMONEYPY"
## [397] "ENERGYASST" "ZENERGYASST" "ENERGYASST11"
## [400] "ZENERGYASST11" "ENERGYASST12" "ZENERGYASST12"
## [403] "ENERGYASST13" "ZENERGYASST13" "ENERGYASST14"
## [406] "ZENERGYASST14" "ENERGYASST15" "ZENERGYASST15"
## [409] "ENERGYASSTOTH" "ZENERGYASSTOTH" "SCALEB"
## [412] "ZSCALEB" "SCALEG" "ZSCALEG"
## [415] "SCALEE" "ZSCALEE" "PAYHELP"
## [418] "ZPAYHELP" "NOHEATBROKE" "ZNOHEATBROKE"
## [421] "NOHEATEL" "ZNOHEATEL" "NOHEATNG"
## [424] "ZNOHEATNG" "NOHEATBULK" "ZNOHEATBULK"
## [427] "NOHEATDAYS" "ZNOHEATDAYS" "NOHEATHELP"
## [430] "ZNOHEATHELP" "COLDMA" "ZCOLDMA"
## [433] "NOACBROKE" "ZNOACBROKE" "NOACEL"
## [436] "ZNOACEL" "NOACDAYS" "ZNOACDAYS"
## [439] "NOACHELP" "ZNOACHELP" "HOTMA"
## [442] "ZHOTMA" "USEEL" "ELWARM"
## [445] "ELCOOL" "ELWATER" "ELFOOD"
## [448] "ELOTHER" "USENG" "UGWARM"
## [451] "UGWATER" "UGCOOK" "UGOTH"
## [454] "USELP" "LPWARM" "LPWATER"
## [457] "LPCOOK" "LPOTHER" "USEFO"
## [460] "FOWARM" "FOWATER" "FOOTHER"
## [463] "USEWOOD" "WOODLOGS" "ZWOODLOGS"
## [466] "WDPELLET" "ZWDPELLET" "WDOTHER"
## [469] "WDWARM" "WDWATER" "USESOLAR"
## [472] "SOLWATER" "SOLOTHER" "TOTCSQFT"
## [475] "TOTHSQFT" "TOTSQFT_EN" "ZTOTSQFT_EN"
## [478] "TOTUCSQFT" "TOTUSQFT" "NWEIGHT"
## [481] "BRRWT1" "BRRWT2" "BRRWT3"
## [484] "BRRWT4" "BRRWT5" "BRRWT6"
## [487] "BRRWT7" "BRRWT8" "BRRWT9"
## [490] "BRRWT10" "BRRWT11" "BRRWT12"
## [493] "BRRWT13" "BRRWT14" "BRRWT15"
## [496] "BRRWT16" "BRRWT17" "BRRWT18"
## [499] "BRRWT19" "BRRWT20" "BRRWT21"
## [502] "BRRWT22" "BRRWT23" "BRRWT24"
## [505] "BRRWT25" "BRRWT26" "BRRWT27"
## [508] "BRRWT28" "BRRWT29" "BRRWT30"
## [511] "BRRWT31" "BRRWT32" "BRRWT33"
## [514] "BRRWT34" "BRRWT35" "BRRWT36"
## [517] "BRRWT37" "BRRWT38" "BRRWT39"
## [520] "BRRWT40" "BRRWT41" "BRRWT42"
## [523] "BRRWT43" "BRRWT44" "BRRWT45"
## [526] "BRRWT46" "BRRWT47" "BRRWT48"
## [529] "BRRWT49" "BRRWT50" "BRRWT51"
## [532] "BRRWT52" "BRRWT53" "BRRWT54"
## [535] "BRRWT55" "BRRWT56" "BRRWT57"
## [538] "BRRWT58" "BRRWT59" "BRRWT60"
## [541] "BRRWT61" "BRRWT62" "BRRWT63"
## [544] "BRRWT64" "BRRWT65" "BRRWT66"
## [547] "BRRWT67" "BRRWT68" "BRRWT69"
## [550] "BRRWT70" "BRRWT71" "BRRWT72"
## [553] "BRRWT73" "BRRWT74" "BRRWT75"
## [556] "BRRWT76" "BRRWT77" "BRRWT78"
## [559] "BRRWT79" "BRRWT80" "BRRWT81"
## [562] "BRRWT82" "BRRWT83" "BRRWT84"
## [565] "BRRWT85" "BRRWT86" "BRRWT87"
## [568] "BRRWT88" "BRRWT89" "BRRWT90"
## [571] "BRRWT91" "BRRWT92" "BRRWT93"
## [574] "BRRWT94" "BRRWT95" "BRRWT96"
## [577] "CDD30YR" "CDD65" "CDD80"
## [580] "CLIMATE_REGION_PUB" "IECC_CLIMATE_PUB" "HDD30YR"
## [583] "HDD65" "HDD50" "GNDHDD65"
## [586] "WSF" "OA_LAT" "GWT"
## [589] "DBT1" "DBT99" "KWH"
## [592] "KWHSPH" "KWHCOL" "KWHWTH"
## [595] "KWHRFG" "KWHRFG1" "KWHRFG2"
## [598] "KWHFRZ" "KWHCOK" "KWHMICRO"
## [601] "KWHCW" "KWHCDR" "KWHDWH"
## [604] "KWHLGT" "KWHTVREL" "KWHTV1"
## [607] "KWHTV2" "KWHAHUHEAT" "KWHAHUCOL"
## [610] "KWHEVAPCOL" "KWHCFAN" "KWHDHUM"
## [613] "KWHHUM" "KWHPLPMP" "KWHHTBPMP"
## [616] "KWHHTBHEAT" "KWHNEC" "BTUEL"
## [619] "BTUELSPH" "BTUELCOL" "BTUELWTH"
## [622] "BTUELRFG" "BTUELRFG1" "BTUELRFG2"
## [625] "BTUELFRZ" "BTUELCOK" "BTUELMICRO"
## [628] "BTUELCW" "BTUELCDR" "BTUELDWH"
## [631] "BTUELLGT" "BTUELTVREL" "BTUELTV1"
## [634] "BTUELTV2" "BTUELAHUHEAT" "BTUELAHUCOL"
## [637] "BTUELEVAPCOL" "BTUELCFAN" "BTUELDHUM"
## [640] "BTUELHUM" "BTUELPLPMP" "BTUELHTBPMP"
## [643] "BTUELHTBHEAT" "BTUELNEC" "DOLLAREL"
## [646] "DOLELSPH" "DOLELCOL" "DOLELWTH"
## [649] "DOLELRFG" "DOLELRFG1" "DOLELRFG2"
## [652] "DOLELFRZ" "DOLELCOK" "DOLELMICRO"
## [655] "DOLELCW" "DOLELCDR" "DOLELDWH"
## [658] "DOLELLGT" "DOLELTVREL" "DOLELTV1"
## [661] "DOLELTV2" "DOLELAHUHEAT" "DOLELAHUCOL"
## [664] "DOLELEVAPCOL" "DOLELCFAN" "DOLELDHUM"
## [667] "DOLELHUM" "DOLELPLPMP" "DOLELHTBPMP"
## [670] "DOLELHTBHEAT" "DOLELNEC" "CUFEETNG"
## [673] "CUFEETNGSPH" "CUFEETNGWTH" "CUFEETNGCOK"
## [676] "CUFEETNGCDR" "CUFEETNGPLHEAT" "CUFEETNGHTBHEAT"
## [679] "CUFEETNGNEC" "BTUNG" "BTUNGSPH"
## [682] "BTUNGWTH" "BTUNGCOK" "BTUNGCDR"
## [685] "BTUNGPLHEAT" "BTUNGHTBHEAT" "BTUNGNEC"
## [688] "DOLLARNG" "DOLNGSPH" "DOLNGWTH"
## [691] "DOLNGCOK" "DOLNGCDR" "DOLNGPLHEAT"
## [694] "DOLNGHTBHEAT" "DOLNGNEC" "GALLONLP"
## [697] "GALLONLPSPH" "GALLONLPWTH" "GALLONLPCOK"
## [700] "GALLONLPCDR" "GALLONLPNEC" "BTULP"
## [703] "BTULPSPH" "BTULPWTH" "BTULPCOK"
## [706] "BTULPCDR" "BTULPNEC" "DOLLARLP"
## [709] "DOLLPSPH" "DOLLPWTH" "DOLLPCOK"
## [712] "DOLLPCDR" "DOLLPNEC" "GALLONFO"
## [715] "GALLONFOSPH" "GALLONFOWTH" "GALLONFONEC"
## [718] "BTUFO" "BTUFOSPH" "BTUFOWTH"
## [721] "BTUFONEC" "DOLLARFO" "DOLFOSPH"
## [724] "DOLFOWTH" "DOLFONEC" "TOTALBTU"
## [727] "TOTALDOL" "TOTALBTUSPH" "TOTALDOLSPH"
## [730] "TOTALBTUWTH" "TOTALDOLWTH" "TOTALBTUCOK"
## [733] "TOTALDOLCOK" "TOTALBTUCDR" "TOTALDOLCDR"
## [736] "TOTALBTUPL" "TOTALDOLPL" "TOTALBTUHTB"
## [739] "TOTALDOLHTB" "TOTALBTUNEC" "TOTALDOLNEC"
## [742] "WOODAMT" "ZWOODAMT" "WOODBTU"
## [745] "PELLETAMT" "ZPELLETAMT" "PELLETBTU"
## [748] "ELXBTU" "PERIODEL" "ZELAMOUNT"
## [751] "NGXBTU" "PERIODNG" "ZNGAMOUNT"
## [754] "FOXBTU" "PERIODFO" "ZFOAMOUNT"
## [757] "LPXBTU" "PERIODLP" "ZLPAMOUNT"colnames(energy)=tolower(colnames(energy)) #changing columns from capital letters to lowercase as easier to work with
kwh_tot <- ggplot(energy, aes(x=kwh, fill=as.factor(regionc), alpha=0.5))+geom_density() #total amount of electricity used by houses at each region in kwh
kwh_tot
ggplot(energy, aes(x = kwh, fill=as.factor(atticfin), alpha=0.5))+geom_density()+
scale_fill_discrete(name="Finished attic present",
breaks=c("-2","0","1"),
labels=c("Not Applicable", "No", "Yes"))#graph shows houses with an attic use more electricity which makes sense as it is another room in the house requiring heat, light and other electrically intense appliances 
ggplot(energy, aes(x = kwh, fill=as.factor(division), alpha=0.5))+geom_density()+
scale_fill_discrete(name="Division",
breaks=c("1","2","3","4","5","6","7","8","9","10"),
labels=c("New England", "Middle Atlantic", "East North Central", "West North Central", "South Atlantic", "East South Central", "West South Central", "Mountain North", "Mountain South", "Pacific"),) #shows kwh usage for each area division, indicates East is a comparatively large electricity user
ggplot(energy, aes(x = kwh, fill=as.factor(typeglass), alpha=0.5))+geom_density()+
scale_fill_discrete(name="type of glass in window",
breaks=c("1","2","3"),
labels=c("Single-paned", "Double-paned", "Triple-paned")) #shows triple-paned glass had the highest electricity usage ehich is strange as it is the best heat insulator, could be to do with higher wealth to afford the windows so ability to buy other electrically intensive appliances
ggplot(energy, aes(y=kwh, x=sizeofgarage))+geom_point()+geom_smooth(method="lm") #shows a slight upwards slope which tells us houses with larger garages use more electricity, most likely due to lighting and electrical appliances, as well as general wealth associated with larger garages meaning higher likelihood of more electronics## `geom_smooth()` using formula = 'y ~ x'
Bootstrapping
Testing means between groups
t.test(kwh ~ outgrill, data = energy)##
## Welch Two Sample t-test
##
## data: kwh by outgrill
## t = -22.965, df = 5362.1, p-value < 2.2e-16
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
## -4372.503 -3684.713
## sample estimates:
## mean in group 0 mean in group 1
## 8552.68 12581.29og.t.test <- t.test(kwh ~ outgrill, data = energy)
names(og.t.test)## [1] "statistic" "parameter" "p.value" "conf.int" "estimate"
## [6] "null.value" "stderr" "alternative" "method" "data.name"og.t.test$p.value #p-value## [1] 2.101207e-111og.t.test$estimate #group means## mean in group 0 mean in group 1
## 8552.68 12581.29og.t.test$conf.int #our study shows a confidence interval of [-4372.503, -3684.713]## [1] -4372.503 -3684.713
## attr(,"conf.level")
## [1] 0.95get_resample_mean <- function(energy, paired = FALSE) {
if (paired) {
diff <- energy$kwh - energy$outgrill
boot_sample <- sample(diff, length(diff), replace = TRUE)
mean_og<- mean(boot_sample)
} else {
outgrill <- sample(energy$outgrill, nrow(energy), replace = TRUE)
kwh <- sample(energy$kwh, nrow(energy), replace = TRUE)
mean_og <- mean(kwh) - mean(outgrill)
}
return(mean_og)
} #creating a function to get our sample mean of kwh used
get_bootstrap_mean <- function(energy, N = 1000, paired = FALSE) {
for (i in 1:N) {
if (i == 1) {
boot_means <- get_resample_mean(energy, paired)
} else {
boot_means <- c(boot_means, get_resample_mean(energy))
}
}
return(boot_means)
} #using our previous function to get a bootstrap mean function
get_bootstrap_mean(energy, 10)## [1] 11151.58 11079.05 11096.34 10907.59 11105.72 10973.03 10991.82 11012.85
## [9] 10904.84 10841.27get_resample_mean(energy, paired = TRUE)## [1] 11236.15unpaired_means <- get_bootstrap_mean(energy, N = 1000, paired = FALSE) #unpaired data
ci_unpaired <- quantile(unpaired_means,c(0.025, 0.975))
ci_unpaired## 2.5% 97.5%
## 10844.11 11228.10ggplot() + geom_histogram(aes(unpaired_means)) +
geom_vline(data = data.frame(CI=ci_unpaired),
aes(xintercept=CI), color = "blue", linetype = "dashed")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Using our get_bootstrap_mean function we made, we were able to find and
plot our unpaired data at a 95% confidence level with N=1000. This
confidence interval tells us that our mean kwh data has a 95% chance of
being between 10,849.16 and 11,220.55 when paired with the outgrill
data. ## Linear regressions
Reporting on the regression
statistical signifigance
gwt.lm=lm(kwh~gwt, energy) #running the regression
summary(gwt.lm)##
## Call:
## lm(formula = kwh ~ gwt, data = energy)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13338 -4946 -1332 3444 50395
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3092.732 558.617 5.536 3.23e-08 ***
## gwt 138.155 9.592 14.403 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6925 on 5684 degrees of freedom
## Multiple R-squared: 0.03521, Adjusted R-squared: 0.03504
## F-statistic: 207.4 on 1 and 5684 DF, p-value: < 2.2e-16gwt.lm$coefs## NULLattributes(gwt.lm)## $names
## [1] "coefficients" "residuals" "effects" "rank"
## [5] "fitted.values" "assign" "qr" "df.residual"
## [9] "xlevels" "call" "terms" "model"
##
## $class
## [1] "lm"gwt.lm.coef <- round(summary(gwt.lm)$coef, 3) #getting the coefficient table
class(gwt.lm.coef)## [1] "matrix" "array"attributes(gwt.lm.coef)## $dim
## [1] 2 4
##
## $dimnames
## $dimnames[[1]]
## [1] "(Intercept)" "gwt"
##
## $dimnames[[2]]
## [1] "Estimate" "Std. Error" "t value" "Pr(>|t|)"gwt.lm.coef["gwt", "Pr(>|t|)"] #gives p-value of intercept on gwt## [1] 0gwt.rsq = round(summary(gwt.lm)$r.squared, 3)
round(coef(gwt.lm)["gwt"],3)## gwt
## 138.155practical signifigance
energy %>% group_by(regionc) %>% summarise(avg_gwt=mean(gwt), avg_kwh=mean(kwh)) #Shows how the ground water temperature varies with region (Region 1: Northeast, 2: Midwest, 3:South, 4:West). Large variation## # A tibble: 4 × 3
## regionc avg_gwt avg_kwh
## <int> <dbl> <dbl>
## 1 1 48.6 8806.
## 2 2 49.5 9797.
## 3 3 65.3 14381.
## 4 4 58.6 8883.Plotting the lm() object
ggplot(energy, aes(y=kwh, x=gwt))+geom_point()+geom_smooth(method="lm") #plotting the graph with method=lm## `geom_smooth()` using formula = 'y ~ x'
Using lm() on categorical data
lm(kwh~as.factor(dryrfuel), energy) #using as.factor to treat our categorical data as a factor##
## Call:
## lm(formula = kwh ~ as.factor(dryrfuel), data = energy)
##
## Coefficients:
## (Intercept) as.factor(dryrfuel)1 as.factor(dryrfuel)2
## 5998 2893 5651
## as.factor(dryrfuel)5
## 6762lm(kwh~as.factor(walltype), energy)##
## Call:
## lm(formula = kwh ~ as.factor(walltype), data = energy)
##
## Coefficients:
## (Intercept) as.factor(walltype)2 as.factor(walltype)3
## 11403.9 -465.9 202.5
## as.factor(walltype)4 as.factor(walltype)5 as.factor(walltype)6
## -2119.3 -1279.5 2794.1
## as.factor(walltype)7 as.factor(walltype)9
## -864.5 -667.3Visualising the regression
ggplot(energy, aes(y=kwh, x = as.factor(dryrfuel)))+geom_point()+geom_smooth(method="lm")## `geom_smooth()` using formula = 'y ~ x'
ggplot(energy, aes(y=kwh, x = as.factor(walltype)))+geom_point()+geom_smooth(method="lm")## `geom_smooth()` using formula = 'y ~ x'
Summary of results
Using our get_bootstrap_mean function we made, we were able to find and plot our unpaired data at a 95% confidence level with N=1000. This confidence interval tells us that our mean kwh data has a 95% chance of being between 10,849.16 and 11,220.55 when paired with the out-grill data. In 2015, a unit increase in ground water temperature is associated with 138.155 kWh increase in annual electricity usage. At a 99% significance level, this effect is statistically different from 0. The R^2 value of 0.035 tells us that the increase in groundwater temperature alone does not explain the variation in electricity consumption for 2015. This could warrant further research to find out what else is contributing to variation in electricity consumption. A 138.55 effect corresponds to a 2,308.243 kWh average difference in a house in the southern (highest) and north-eastern (lowest). On average a house in the south consumed over 14,000 kWh of electricity while the north consumed 9,000 kWh of electricity. This shows major variation between different parts of the country with the south consuming the most electricity by far and the north consuming the least. When we look at our confidence interval, our high end suggests an average consumption of 11,220.55 kWh over the entire area. When compared with the over 14,000 kWh in the south we see that the average in the south lies outside of 95% of houses. This could be due to large, typically un-affordable, wealthy houses with out grills or due to farms which require large plots of land and a high amount of electricity for maintenance and equipment such as machinery that are likely to own an out-grill to cook products they grow.
Project Work
Data search
Excel sheet of data:https://ucd-my.sharepoint.com/:x:/g/personal/matthew_kirwan_ucdconnect_ie/EflXT1Q_wBxPuR95rTPJz7QBzefbmnJceOlSuyJjzC5Wqg?e=ZvBOqV (a) The variables I am going to use are access to basic clean water and sanitation in rural and urban areas and access between ethnical groups. These will help me measure the construct of health by determining if clean water access is better in rural or urban parts and also measure access by wealth by determining whether foreign ethnicities have better access to clean water. (b) Data on the finances of the sampled group would have helped as well as the accurate measurement of the water components such as pH, temperature, etc. (c) They change the research question by discluding some of the water parameters which I have replaced by studying the rural and urban differences.
Data description
df.Ph <- read.csv("water_Phillipines.csv")
access_ph <- as_tibble(df.Ph)
access_ph <- na.omit(access_ph) #removing rows with NA observations
str(access_ph)## tibble [436 × 64] (S3: tbl_df/tbl/data.frame)
## $ Access.to.improved.drinking.water : num [1:436] 97 97.2 97.4 97.6 97.8 ...
## $ Access.to.basic.drinking.water : num [1:436] 91.6 91.8 92.1 92.3 92.5 ...
## $ Access.to.limited.drinking.water : num [1:436] 5.39 5.37 5.34 5.32 5.3 5.26 5.23 5.19 5.16 5.12 ...
## $ Access.to.unimproved.drinking.water : num [1:436] 2.7 2.51 2.32 2.14 1.96 1.78 1.61 1.44 1.28 1.11 ...
## $ No.access.to.drinking.water : num [1:436] 0.31 0.29 0.27 0.25 0.23 0.21 0.19 0.17 0.16 0.14 ...
## $ Access.to.safely.managed.drinking.water : num [1:436] 73.7 74.2 74.6 75.1 75.5 ...
## $ Number.with.access.to.improved.drinking.water : num [1:436] 33140777 33761082 34420698 35120525 35860866 ...
## $ Number.with.access.to.basic.drinking.water : num [1:436] 31300104 31897736 32532626 33205737 33917327 ...
## $ Number.with.access.to.limited.drinking.water : int [1:436] 1840673 1863346 1888072 1914788 1943539 1968254 1994333 2021381 2049084 2077308 ...
## $ Number.with.access.to.unimproved.drinking.water : int [1:436] 921524 870375 819450 768514 717412 665915 613787 560779 506717 451496 ...
## $ Number.with.no.access.to.drinking.water : int [1:436] 104676 99148 93735 88410 83160 77962 72794 67628 62450 57248 ...
## $ Number.with.access.to.safely.managed.drinking.water: num [1:436] 25188141 25764143 26368860 27003525 27668358 ...
## $ Rural.access : num [1:436] 94.2 94.5 94.9 95.2 95.6 ...
## $ Rural.access.1 : num [1:436] 85.7 86 86.3 86.7 87 ...
## $ Rural.access.2 : num [1:436] 8.47 8.5 8.53 8.56 8.6 8.62 8.64 8.66 8.69 8.71 ...
## $ Rural.access.3 : num [1:436] 5.12 4.8 4.48 4.17 3.85 3.53 3.21 2.9 2.58 2.26 ...
## $ Rural.access.4 : num [1:436] 0.72 0.68 0.63 0.59 0.55 0.51 0.47 0.42 0.38 0.34 ...
## $ Rural.access.5 : num [1:436] 58.4 59.3 60.2 61.1 62.1 ...
## $ Rural.access..number.of.people. : int [1:436] 11148725 11129974 11121924 11122704 11132965 11151420 11176753 11206180 11238522 11272581 ...
## $ Rural.access..number.of.people..1 : int [1:436] 10146330 10129265 10121938 10122648 10131987 10149906 10174089 10202004 10232580 10264726 ...
## $ Rural.access..number.of.people..2 : int [1:436] 1002395 1000709 999986 1000056 1000978 1001515 1002664 1004175 1005942 1007855 ...
## $ Rural.access..number.of.people..3 : int [1:436] 605919 565256 525532 486548 448232 410438 373033 335863 298853 261945 ...
## $ Rural.access..number.of.people..4 : int [1:436] 84897 79487 74207 69028 63942 58928 53969 49042 44138 39248 ...
## $ Rural.access..number.of.people..5 : int [1:436] 6907980 6979491 7057511 7141081 7230820 7326095 7426216 7529467 7635137 7742470 ...
## $ Urban.access : num [1:436] 98.5 98.6 98.7 98.8 98.8 ...
## $ Urban.access.1 : num [1:436] 94.7 94.8 94.9 95 95.1 ...
## $ Urban.access.2 : num [1:436] 3.75 3.76 3.76 3.76 3.77 3.75 3.74 3.72 3.71 3.69 ...
## $ Urban.access.3 : num [1:436] 1.41 1.33 1.24 1.16 1.08 0.99 0.91 0.82 0.74 0.65 ...
## $ Urban.access.4 : num [1:436] 0.09 0.09 0.08 0.08 0.08 0.07 0.07 0.07 0.07 0.06 ...
## $ Urban.access.5 : num [1:436] 81.9 81.8 81.8 81.7 81.7 ...
## $ Urban.access..number.of.people. : int [1:436] 21992052 22631107 23298773 23997821 24727900 25488601 26276803 27089101 27920331 28770073 ...
## $ Urban.access..number.of.people..1 : int [1:436] 21153774 21768471 22410687 23083089 23785340 24521861 25285133 26071895 26877189 27700620 ...
## $ Urban.access..number.of.people..2 : int [1:436] 838278 862637 888086 914732 942561 966740 991669 1017206 1043143 1069453 ...
## $ Urban.access..number.of.people..3 : int [1:436] 315605 305118 293919 281967 269180 255478 240755 224917 207865 189552 ...
## $ Urban.access..number.of.people..4 : int [1:436] 19779 19661 19529 19382 19218 19034 18825 18586 18312 18000 ...
## $ Urban.access..number.of.people..5 : int [1:436] 18280160 18784652 19311349 19862445 20437538 21036181 21655693 22041555 22373173 22698870 ...
## $ Entity : chr [1:436] "Algeria" "Algeria" "Algeria" "Algeria" ...
## $ Year : int [1:436] 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 ...
## $ wat_bas_minus_sm : num [1:436] 17.9 17.7 17.4 17.2 17.1 ...
## $ wat_bas_minus_sm_number : int [1:436] 6111963 6133593 6163765 6202212 6248969 6309491 6377313 6702878 7101459 7524006 ...
## $ san_bas_minus_sm : num [1:436] 65.9 66.3 66.7 67.1 67.5 ...
## $ san_bas_minus_sm_number : int [1:436] 22531279 23043034 23582933 24152146 24750925 25289508 25848600 26423927 27010839 27608208 ...
## $ wat_bas_minus_sm_rural : num [1:436] 27.4 26.8 26.1 25.5 24.9 ...
## $ wat_bas_minus_sm_number_rural : int [1:436] 3238349 3149774 3064427 2981567 2901167 2823810 2747872 2672538 2597443 2522256 ...
## $ san_bas_minus_sm_rural : num [1:436] 52.2 52.6 53 53.5 53.9 ...
## $ san_bas_minus_sm_number_rural : int [1:436] 6179167 6195167 6216860 6243274 6274840 6301311 6331463 6363744 6397502 6432066 ...
## $ wat_bas_minus_sm_urban : num [1:436] 12.9 13 13.1 13.2 13.4 ...
## $ wat_bas_minus_sm_number_urban : int [1:436] 2873614 2983819 3099338 3220645 3347802 3485681 3629440 4030340 4504016 5001750 ...
## $ san_bas_minus_sm_urban : num [1:436] 73.2 73.4 73.5 73.7 73.9 ...
## $ san_bas_minus_sm_number_urban : int [1:436] 16352111 16847867 17366073 17908872 18476085 18988197 19517137 20060182 20613337 21176141 ...
## $ wat_imp_number_without : int [1:436] 1026200 969524 913185 856924 800572 743877 686581 628407 569166 508745 ...
## $ wat_bas_number_without : int [1:436] 2866873 2832870 2801257 2771712 2744111 2712131 2680915 2649788 2618251 2586053 ...
## $ wat_sm_number_without : num [1:436] 8978836 8966463 8965022 8973924 8993080 ...
## $ wat_imp_without : num [1:436] 3 2.79 2.58 2.38 2.18 1.99 1.8 1.61 1.43 1.25 ...
## $ wat_bas_without : num [1:436] 8.39 8.16 7.93 7.7 7.49 7.25 7.03 6.81 6.59 6.38 ...
## $ wat_sm_without : num [1:436] 26.3 25.8 25.4 24.9 24.5 ...
## $ san_imp_number_without : num [1:436] 2007958 1963488 1921540 1881764 1844105 ...
## $ san_bas_number_without : num [1:436] 4681068 4676975 4678387 4684935 4696608 ...
## $ san_sm_number_without : num [1:436] 27212347 27720009 28261320 28837081 29447533 ...
## $ san_imp_without : num [1:436] 5.88 5.65 5.44 5.23 5.03 4.84 4.65 4.47 4.3 4.13 ...
## $ san_bas_without : num [1:436] 13.7 13.5 13.2 13 12.8 ...
## $ san_sm_without : num [1:436] 79.7 79.8 80 80.2 80.3 ...
## $ hyg_bas_number_without : num [1:436] 5837840 5894013 5956653 6025518 6100708 ...
## $ hyg_bas_without : num [1:436] 17.1 17 16.9 16.8 16.6 ...
## - attr(*, "na.action")= 'omit' Named int [1:4682] 1 2 3 4 5 6 7 8 9 10 ...
## ..- attr(*, "names")= chr [1:4682] "1" "2" "3" "4" ...class(access_ph$Access.to.basic.drinking.water) #data is numeric## [1] "numeric"class(access_ph$Entity) #data is a character## [1] "character"grouped_eth = access_ph %>% group_by(Year, Entity) %>% summarise(total_access = mean(Access.to.basic.drinking.water))## `summarise()` has grouped output by 'Year'. You can override using the
## `.groups` argument.view(grouped_eth)
no_wat_eth = access_ph %>% group_by(Entity, Year) %>% summarise(num_no_access = sum(Number.with.no.access.to.drinking.water))## `summarise()` has grouped output by 'Entity'. You can override using the
## `.groups` argument.view(no_wat_eth)
rural_access <- access_ph %>% group_by(Year) %>% summarise(rural_acc = mean(Rural.access.1),
urban_acc = mean(Urban.access.1))
view(rural_access)
#(a)Data has 436 observations of 64 variables. Ethnicity data is collected at 34 levels and yearly data is based between 2000 and 2020.
#(b)Originally the data had 5118 observations of 64 variables however, using the na.omit function we removed the rows with NA data present which gave us 436 observations of 64 variables.Plotting relevant data
grouped_eth %>% ggplot(aes(x=Year, y=total_access, group = Entity)) +
geom_point() + facet_wrap(~Entity) + geom_line()#graph of percent access to basic clean drinking water by ethnicity (entity) from 2000-2020 in the Phillipines
no_wat_eth %>% ggplot(aes(x=Year, y=num_no_access, group = Entity)) +
geom_point() + facet_wrap(~Entity) + geom_line()#graph of the number of people for different ethnicities that have access to no clean water from 2000-2020
data_ggp <- data.frame(x = rural_access$Year, # Reshape data frame
y = c(rural_access$rural_acc, rural_access$urban_acc),
group = c(rep("rural_acc", nrow(rural_access)),
rep("urban_acc", nrow(rural_access))))
head(data_ggp)## x y group
## 1 2000 60.82000 rural_acc
## 2 2001 61.13000 rural_acc
## 3 2002 61.44000 rural_acc
## 4 2003 61.75500 rural_acc
## 5 2004 46.98444 rural_acc
## 6 2005 58.41000 rural_accggplot(data_ggp, aes(x, y, col = group)) + labs(x = "Year", y = "Percentage access to basic clean water") + geom_line()
#graph of percentage access of people in the rural vs urban areas with access to basic clean water between 2000 and 2020