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NEW YORK CITY’S
ELECTRICITY CONSUMPTION 2010
New Yorkers consume more energy inside than
Americans on average. In New York...
We take a closer look on New York City’s
electricity consumption to figure out what is
actually happening within NYC build...
ELECTRICITY CONSUMPTION IN NEW YORK CITY 2010
Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija Drobn...
LARGE RESIDENTIAL BUILDINGS ELECTRICITY CONSUMPTION
Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija...
INSTITUTIONAL BUILDINGS ELECTRICITY CONSUMPTION
Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija Dro...
SMALL RESIDENTIAL BUILDINGS ELECTRICITY CONSUMPTION
Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija...
COMMERCIAL BUILDINGS ELECTRICITY CONSUMPTION
Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija Drobnj...
The City of New York has recently released a
report benchmarking commercial building
consumption in NYC. This is the first...
require(ggplot2)
# shape file, download from: http://www.census.gov/cgi-bin/geo/shapefiles2010/main
shape_fp <- " xx "
sha...
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Data visualization of NYC's electricity consumption in 2010 per building type

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A data visualization of New York City's electricity consumption per building type in 2010.

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Transcript of "Data visualization of NYC's electricity consumption in 2010 per building type "

  1. 1. NEW YORK CITY’S ELECTRICITY CONSUMPTION 2010 New Yorkers consume more energy inside than Americans on average. In New York around 75% of the greenhouse gas emissions come from activities such as lighting, heating, cooling and appliances, while on a national level that figure is 39%. Source: http://www.nycedc.com/blog-entry/energy-consumption-new-york-city
  2. 2. We take a closer look on New York City’s electricity consumption to figure out what is actually happening within NYC buildings.
  3. 3. ELECTRICITY CONSUMPTION IN NEW YORK CITY 2010 Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija Drobnjak and Lise White, Dec. 2013 Commercial buildings use 55% Institutional buildings consume of the city’s entire electricity consumption 12% Large residential Small residential buildings consume 7% buildings consume 26% high low
  4. 4. LARGE RESIDENTIAL BUILDINGS ELECTRICITY CONSUMPTION Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija Drobnjak and Lise White, Dec. 2013 Large residential buildings use 7 % of New York City’s entire electricity consumption Max consumption per year = kWh per zip code area 100 million The areas with highest large residential consumption are predominately zip codes containing public housing high low
  5. 5. INSTITUTIONAL BUILDINGS ELECTRICITY CONSUMPTION Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija Drobnjak and Lise White, Dec. 2013 Institutional buildings use 12 % of New York City’s entire electricity consumption Max consumption per year = 467 million kWh per zip code area South Ozone park has the highest consumption within institutional buildings, here lies JFK Airport high low
  6. 6. SMALL RESIDENTIAL BUILDINGS ELECTRICITY CONSUMPTION Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija Drobnjak and Lise White, Dec. 2013 Small residential buildings use 26 % of New York City’s entire electricity consumption Max consumption per year = 224 million kWh per zip code area Staten Island and The Upper East and Upper West Side have the highest small residential energy consumption Staten Island has 2.7 people per household where Manhattan has 1.7 high low
  7. 7. COMMERCIAL BUILDINGS ELECTRICITY CONSUMPTION Data source: NYC Open Data (www.nyc.gov). Data visualization by Marija Drobnjak and Lise White, Dec. 2013 Commercial buildings use 55 % of New York City’s entire electricity consumption Max consumption per year = 1.4 billion kWh per zip code area 4 zip codes between 42nd and 57th street use 20 % of the total commercial consumption. They range between 1.2 and 1.4 billion kWh use high low
  8. 8. The City of New York has recently released a report benchmarking commercial building consumption in NYC. This is the first time a city in the nation releases private sector building data. The objective is to make the general public aware of the current consumption patterns and thereby stimulate an interest in changing these. Our data analysis fully supports the city’s initiative. We therefore hope our data visualization can function as a supporting tool to encourage change. Source: http://www.nyc.gov/html/gbee/html/plan/ll84_scores.shtml
  9. 9. require(ggplot2) # shape file, download from: http://www.census.gov/cgi-bin/geo/shapefiles2010/main shape_fp <- " xx " shape_fn <- "tl_2010_36_zcta510.shp" electricity_fp <- " xx " electricity_fn <- "Electric_Consumption.csv" library(ggplot2) library(maptools) library(rgdal) library(rgeos) setwd(shape_fp) ogrListLayers(shape_fn) nyc_shp <- readOGR(shape_fn, layer="tl_2010_36_zcta510") nycs <- fortify(nyc_shp, region= "ZCTA5CE10") setwd(electricity_fp) electric <- read.csv(electricity_fn, header=TRUE) electric$loc1 electric$loc2 electric$loc3 electric$loc4 <<<<- regexpr("n", as.character(electric$Zip.Code)) regexpr(",", as.character(electric$Zip.Code)) regexpr("-", as.character(electric$Zip.Code)) regexpr(")", as.character(electric$Zip.Code)) electric$Zip <- substr(as.character(electric$Zip.Code), 1, 5) electric$Lat <- as.numeric(substr(as.character(electric$Zip.Code), electric$loc1 + 2, electric$loc2 - 1)) electric$Long <- as.numeric(substr(as.character(electric$Zip.Code), electric$loc3, electric$loc4 - 1)) electric$loc1 electric$loc2 electric$loc3 electric$loc4 <<<<- NULL NULL NULL NULL electric$Building.type..service.class. <- gsub('Small residential', 'Small Residential', electric$Building.type..service.class.) electric$Building.type..service.class. <- as.factor(electric$Building.type..service.class.) electric$kwdecN <- as.numeric(cut(electric$Consumption..kWh.,quantile(electric$Consumption..kWh.,(0:10)/ 10),include.lowest=TRUE,lable=TRUE)) summary(electric) attach(electric) elec.summ <- aggregate(electric, by=list(Zip, Building.type..service.class.), FUN = mean, na.rm=TRUE) elec.summ.largeres <- elec.summ[elec.summ$Group.2=="Large Residential",] elec.summ.largeres$id <- elec.summ.largeres$Group.1 elec.summ.largeres$Group.1 <- NULL head(elec.summ.largeres) summary(elec.summ.largeres) head(nycs) head(elec.summ.largeres) formap <- merge(nycs, elec.summ.largeres, by="id", all.x = TRUE) head(formap) summary(formap) nrow(nycs) nrow(formap) formap <- formap[order(formap$order), ] rm(nycs) ggplot(formap, aes(x = long, y = lat, group=group)) + geom_polygon(aes(fill= kwdecN), color="grey") + coord_cartesian(xlim=c(-74.3, -73.7), ylim=c(40.41, 40.92)) + theme(plot.background = element_rect(fill='black', colour='black')) + theme(panel.background = element_rect(fill="black")) + theme(line = element_blank()) + theme(text = element_blank()) + theme(title = element_blank()) + labs(x=NULL, y=NULL) + scale_x_continuous(expand=c(0,0)) + scale_fill_gradientn(colours = c("yellow" , "red")) table(cut(electric$Consumption..kWh.,quantile(electric$Consumption..kWh.,(0:10)/10),include.lowest=TRUE,lable=TRUE)) getwd() ggsave("elec.svg", width = 7, height = 7) ggsave("elec.png", width= 7, height=7)
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