Project 3
Jenny
February 26, 2018
install.packages(‘ggplot2’)
Queions 1
After a few building collapses, the City of New York is going to begin investigating older buildings for safety. The city is particularly worried about buildings that were unusually tall when they were built, since best-practices for safety hadn’t yet been determined. Create a graph that shows how many buildings of a certain number of floors were built in each year (note: you may want to use a log scale for the number of buildings). Find a strategy to bin buildings (It should be clear 20-29-story buildings, 30-39-story buildings, and 40-49-story buildings were first built in large numbers, but does it make sense to continue in this way as you get taller?)
library(ggplot2)
# read file locally due to large file size
bk <- read.csv("~/Project 2 Dataset/PLUTO17v1.1/BK2017V11.csv", header = TRUE)
br <- read.csv("~/Project 2 Dataset/PLUTO17v1.1/BX2017V11.csv", header = TRUE)
mn <- read.csv("~/Project 2 Dataset/PLUTO17v1.1/MN2017V11.csv", header = TRUE)
qn <- read.csv("~/Project 2 Dataset/PLUTO17v1.1/QN2017V11.csv", header = TRUE)
si <- read.csv("~/Project 2 Dataset/PLUTO17v1.1/SI2017V11.csv", header = TRUE)
# Check if the dataset
head(bk)## Borough Block Lot CD CT2010 CB2010 SchoolDist Council ZipCode FireComp
## 1 BK 1 1 302 21 NA 13 33 11201 L118
## 2 BK 1 50 302 21 2000 13 33 11201 L118
## 3 BK 1 7501 302 21 2000 13 33 11201 L118
## 4 BK 3 1 302 21 3002 13 33 11201 L118
## 5 BK 3 5 302 21 NA 13 33 11201 L118
## 6 BK 3 35 302 21 NA 13 33 11201 L118
## PolicePrct HealthCenterDistrict HealthArea SanitBoro SanitDistrict
## 1 84 36 1000 3 2
## 2 84 36 1000 3 2
## 3 84 36 1000 1 2
## 4 84 36 1000 3 2
## 5 84 36 1000 3 2
## 6 84 36 1000 3 2
## SanitSub Address ZoneDist1 ZoneDist2 ZoneDist3 ZoneDist4 Overlay1
## 1 1B JOHN STREET M3-1 M1-4/R8A
## 2 1B 10 JAY STREET M1-4/R8A M3-1
## 3 1 JOHN STREET M3-1
## 4 1B JAY STREET M3-1
## 5 1B JAY STREET M3-1
## 6 1B GOLD STREET M3-1
## Overlay2 SPDist1 SPDist2 SPDist3 LtdHeight SplitZone BldgClass LandUse
## 1 MX-2 Y V1 11
## 2 MX-2 Y O6 5
## 3 N RM 4
## 4 N U4 7
## 5 N T2 7
## 6 N T2 7
## Easements OwnerType OwnerName LotArea BldgArea ComArea
## 1 1 P BROOKLYN BRIDGE PARK 151930 0 0
## 2 0 SAFDI PLAZA REALTY IN 19682 163894 163894
## 3 1 0 102534 4686
## 4 1 CONSOLIDED EDISON CO/ 387060 0 0
## 5 0 C NYC DSBS 6384 0 0
## 6 0 C NYC DSBS 0 0 0
## ResArea OfficeArea RetailArea GarageArea StrgeArea FactryArea OtherArea
## 1 0 0 0 0 0 0 0
## 2 0 147505 16389 0 0 0 0
## 3 97848 0 4686 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
## AreaSource NumBldgs NumFloors UnitsRes UnitsTotal LotFront LotDepth
## 1 4 0 0 0 0 206.25 337.42
## 2 2 1 10 0 2 109.08 207.25
## 3 7 1 12 42 44 0.00 0.00
## 4 7 15 0 0 0 1051.00 469.00
## 5 7 0 0 0 0 0.00 0.00
## 6 7 0 0 0 0 0.00 0.00
## BldgFront BldgDepth Ext ProxCode IrrLotCode LotType BsmtCode AssessLand
## 1 0 0 0 Y 5 5 1371105
## 2 88 195 1 Y 3 0 834300
## 3 0 0 0 N 0 5 389694
## 4 0 0 0 Y 5 5 0
## 5 0 0 0 N 8 5 21600
## 6 0 0 0 N 5 5 1854
## AssessTot ExemptLand ExemptTot YearBuilt YearAlter1 YearAlter2
## 1 1371105 0 0 0 0 0
## 2 10156950 0 0 1920 1994 2015
## 3 6603514 0 0 0 0 0
## 4 0 0 0 0 0 0
## 5 21600 21600 21600 0 0 0
## 6 1854 1854 1854 0 0 0
## HistDist Landmark BuiltFAR ResidFAR CommFAR FacilFAR
## 1 0.00 0.0 2 0.0
## 2 DUMBO Historic District 8.33 5.4 2 6.5
## 3 0.00 0.0 2 0.0
## 4 0.00 0.0 2 0.0
## 5 0.00 0.0 2 0.0
## 6 0.00 0.0 2 0.0
## BoroCode BBL CondoNo Tract2010 XCoord YCoord ZoneMap ZMCode
## 1 3 3000010001 0 21 NA NA 12d
## 2 3 3000010050 0 21 987838 195989 12d
## 3 3 3000017501 3819 21 987624 195992 12d
## 4 3 3000030001 0 21 988568 196151 12d
## 5 3 3000030005 0 21 NA NA 12d
## 6 3 3000030035 0 21 NA NA
## Sanborn TaxMap EDesigNum APPBBL APPDate PLUTOMapID FIRM07_FLAG
## 1 302 007 30101 3000010001 11/26/2013 1 1
## 2 302 007 30101 E-231 0 1 1
## 3 302 007 30101 3000010002 3/4/2016 1 1
## 4 302 007 30101 0 1 1
## 5 302 007 30101 0 4 1
## 6 302 007 30101 0 2 NA
## PFIRM15_FLAG Version
## 1 1 17v1.1
## 2 1 17v1.1
## 3 1 17v1.1
## 4 1 17v1.1
## 5 1 17v1.1
## 6 NA 17v1.1# Since the question is only about number of floors, so we can subset the column "borogh" and "number of floors"
sub_bk <- bk[c("Borough", "NumFloors")]
sub_br <- br[c("Borough", "NumFloors")]
sub_mn <- mn[c("Borough", "NumFloors")]
sub_qn <- qn[c("Borough", "NumFloors")]
sub_si <- si[c("Borough", "NumFloors")]
# Combine the 5 borough dataset vertically using rbind
nyc <- rbind(sub_bk, sub_br, sub_mn, sub_qn, sub_si)
head(nyc)## Borough NumFloors
## 1 BK 0
## 2 BK 10
## 3 BK 12
## 4 BK 0
## 5 BK 0
## 6 BK 0#View(nyc)
# Remove the rows with 0 for number of floors.
#complete.cases(nyc$NumFloors)
range(nyc$NumFloors)## [1] 0 119ggplot(nyc, aes(nyc$NumFloors)) +
geom_histogram(bins = 20)