Foodmile Bar Chart
4+8
FdConsumer_emission= {
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Apples"){
foodData[i].Total_Emissions_Financial_District= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Financial_District_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Financial_District_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Milk_products"){
foodData[i].Total_Emissions_Financial_District= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Financial_District_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Financial_District_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Meat_All_Red"){
foodData[i].Total_Emissions_Financial_District= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Financial_District_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Financial_District_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Bread"){
foodData[i].Total_Emissions_Financial_District= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Financial_District_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Financial_District_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Broccoli"){
foodData[i].Total_Emissions_Financial_District= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Financial_District_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Financial_District_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Lettuce"){
foodData[i].Total_Emissions_Financial_District= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Financial_District_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Financial_District_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Tomatoes"){
foodData[i].Total_Emissions_Financial_District= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Financial_District_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Financial_District_Food_Miles)
}}
return foodData}
Financial_District_Total_CO2_Emission_Chart2=Plot.plot({
marginBottom: 50,
x: {
tickRotate: -30,
},
y: {
transform: (d) => d / 1,
label: "Total Co2 Metric Ton",
grid: 10
},
marks: [
Plot.ruleY([0]),
Plot.barY(FdConsumer_emission, {
x: "Products",
y: "Total_Emissions_Financial_District",
sort: { x: "y", reverse: true, },
fill: "green",
channels: { Conv_Total_Food_Pound: "Conv_Total_Food_Pound", Local_Total_Food_Pound:"Local_Total_Food_Pound", Average_food_lb_per_year:"Average_food_lb_per_year"},
tip:"x"
}),
]
})
CobbleHillConsumer= {
// do some claculations and returen their values
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Apples"){
foodData[i].Total_Emissions_Cobble_Hill= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Cobble_Hill_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Cobble_Hill_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Milk_products"){
foodData[i].Total_Emissions_Cobble_Hill= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Cobble_Hill_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Cobble_Hill_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Meat_All_Red"){
foodData[i].Total_Emissions_Cobble_Hill= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Cobble_Hill_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Cobble_Hill_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Bread"){
foodData[i].Total_Emissions_Cobble_Hill= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Cobble_Hill_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Cobble_Hill_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Broccoli"){
foodData[i].Total_Emissions_Cobble_Hill= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Cobble_Hill_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Cobble_Hill_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Lettuce"){
foodData[i].Total_Emissions_Cobble_Hill= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Cobble_Hill_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Cobble_Hill_Food_Miles)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Tomatoes"){
foodData[i].Total_Emissions_Cobble_Hill= (foodmile[i].Local_Total_Food_Pound*foodmile[i].Local_Cobble_Hill_Food_Miles) + (foodmile[i].Conv_Total_Food_Pound* foodmile[i].Conv_Cobble_Hill_Food_Miles)
}}
return foodData}
Cobble_Hill_Total_CO2_Emission_Chart2= Plot.plot({
marginBottom: 50,
x: {
tickRotate: -30,
},
y: {
transform: (d) => d / 1,
label: "Total Co2 Metric Ton ",
grid: 5
},
marks: [
Plot.ruleY([0]),
Plot.barY(CobbleHillConsumer, {
x: "Products",
y: "Total_Emissions_Cobble_Hill",
sort: { x: "y", reverse: true, },
fill: "blue",
channels: { Conv_Total_Food_Pound: "Conv_Total_Food_Pound", Local_Total_Food_Pound:"Local_Total_Food_Pound", Average_food_lb_per_year:"Average_food_lb_per_year"},
tip:"x"
}),
]
})
foodmile= {
// do some claculations and returen their values
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Apples"){
var localPercent = Apple
var conPercent = 1 - Apple
foodData[i].Local_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(Apple)
foodData[i].Conv_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(1- Apple)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products){
foodData[i].Local_Financial_District_Food_Miles= Math.round(foodData[i].Financial_District_Localmiles*Tons_Local*Co2g)/1000000
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products){
foodData[i].Local_Cobble_Hill_Food_Miles = Math.round(foodData[i].Cobble_Hill_Localmiles*Tons_Local*Co2g)/1000000
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products){
foodData[i].Conv_Financial_District_Food_Miles = Math.round(foodData[i].Financial_District_Cmiles*TonsConventional*Co2g)/1000000
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products){
foodData[i].Conv_Cobble_Hill_Food_Miles = Math.round(foodData[i].Cobble_Hill_Cmiles*TonsConventional*Co2g)/1000000
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Milk_products"){
var localPercent = Milk_products
var conPercent = 1 - Milk_products
foodData[i].Local_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(Milk_products)
foodData[i].Conv_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(1- Milk_products)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Meat_All_Red"){
var localPercent = Meat_All_Red
var conPercent = 1 - Meat_All_Red
foodData[i].Local_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(Meat_All_Red)
foodData[i].Conv_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(1- Meat_All_Red)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Bread"){
var localPercent = Bread
var conPercent = 1 - Bread
foodData[i].Local_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(Bread)
foodData[i].Conv_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(1- Bread)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Broccoli"){
var localPercent = Broccoli
var conPercent = 1 - Broccoli
foodData[i].Local_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(Broccoli)
foodData[i].Conv_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(1- Broccoli)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Lettuce"){
var localPercent = Lettuce
var conPercent = 1 - Lettuce
foodData[i].Local_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(Lettuce)
foodData[i].Conv_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(1- Lettuce)
}}
for (let i= 0; i < foodData.length; ++i) {
if(foodData[i].Products=="Tomatoes"){
var localPercent = Tomatoes
var conPercent = 1 - Tomatoes
foodData[i].Local_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(Tomatoes)
foodData[i].Conv_Total_Food_Pound = foodData[i].Average_food_lb_per_year*(1- Tomatoes)
}}
return foodData}
Co2g=161.8
TonsConventional=22
Tons_Local=1.5
Milk_products
viewof Milk_products = Inputs.range([0, 1], {value: .5, step: .01, label: "Milk_product"})
Meat_All_Red
viewof Meat_All_Red = Inputs.range([0, 1], {value: .5, step: .01, label: "Meat_All_Red"})
Bread
viewof Bread = Inputs.range([0, 1], {value: .5, step: .01, label: "Bread"})
Broccoli
viewof Broccoli = Inputs.range([0, 1], {value: .5, step: .01, label: "Broccoli"})
Lettuce
viewof Lettuce = Inputs.range([0, 1], {value: .5, step: .01, label: "Lettuce"})
Tomatoes
viewof Tomatoes = Inputs.range([0, 1], {value: .5, step: .01, label: "Tomatoes"})
Apple
viewof Apple = Inputs.range([0, 1], {value: .5, step: .001, label: "Apple"})
st3 = FileAttachment("square_test3.txt").tsv({array:true})
buildingList_link = "https://docs.google.com/spreadsheets/d/e/2PACX-1vQJi6qcVeQdmk5SVWmCvSYHnz7tynk64zCRfYYax4JgT3DVpa1692_rT1I0jf0ylIGhdEwAUVr7rsv7/pub?gid=1476053808&single=true&output=csv"
foodData = d3.csv(buildingList_link,d3.autoType)
foodbarchartlink = "https://docs.google.com/spreadsheets/d/e/2PACX-1vQJi6qcVeQdmk5SVWmCvSYHnz7tynk64zCRfYYax4JgT3DVpa1692_rT1I0jf0ylIGhdEwAUVr7rsv7/pub?gid=504406909&single=true&output=csv"
foodbarchart = d3.csv(foodbarchartlink,d3.autoType)
foodbarchart[0].Co2 = foodmile[0].Local_Cobble_Hill_Food_Miles;
foodbarchart[1].Co2 = foodmile[0].Conv_Cobble_Hill_Food_Miles;
foodbarchart[2].Co2 = foodmile[1].Local_Cobble_Hill_Food_Miles;
foodbarchart[3].Co2 = foodmile[1].Conv_Cobble_Hill_Food_Miles;
foodbarchart[4].Co2 = foodmile[2].Local_Cobble_Hill_Food_Miles;
foodbarchart[5].Co2 = foodmile[2].Conv_Cobble_Hill_Food_Miles;
foodbarchart[6].Co2 = foodmile[3].Local_Cobble_Hill_Food_Miles;
foodbarchart[7].Co2 = foodmile[3].Conv_Cobble_Hill_Food_Miles;
foodbarchart[8].Co2 = foodmile[4].Local_Cobble_Hill_Food_Miles;
foodbarchart[9].Co2 = foodmile[4].Conv_Cobble_Hill_Food_Miles;
foodbarchart[10].Co2 = foodmile[5].Local_Cobble_Hill_Food_Miles;
foodbarchart[11].Co2 = foodmile[5].Conv_Cobble_Hill_Food_Miles;
foodbarchart[12].Co2 = foodmile[6].Local_Cobble_Hill_Food_Miles;
foodbarchart[13].Co2 = foodmile[6].Conv_Cobble_Hill_Food_Miles;
foodbarchart
X
Local_VS_Conv
Y
Co2
Color
Local_VS_Conv
Size
Co2
Facet X
Products
Facet Y
—
Mark
bar
Type Chart, then Shift-Enter. Ctrl-space for more options.
FDfoodbarchart = d3.csv(FDfoodbarchartlink,d3.autoType)
FDfoodbarchart[0].Co2 = foodmile[0].Local_Financial_District_Food_Miles;
FDfoodbarchart[1].Co2 = foodmile[0].Conv_Financial_District_Food_Miles;
FDfoodbarchart[2].Co2 = foodmile[1].Local_Financial_District_Food_Miles;
FDfoodbarchart[3].Co2 = foodmile[1].Conv_Financial_District_Food_Miles;
FDfoodbarchart[4].Co2 = foodmile[2].Local_Financial_District_Food_Miles;
FDfoodbarchart[5].Co2 = foodmile[2].Conv_Financial_District_Food_Miles;
FDfoodbarchart[6].Co2 = foodmile[3].Local_Financial_District_Food_Miles;
FDfoodbarchart[7].Co2 = foodmile[3].Conv_Financial_District_Food_Miles;
FDfoodbarchart[8].Co2 = foodmile[4].Local_Financial_District_Food_Miles;
FDfoodbarchart[9].Co2 = foodmile[4].Conv_Financial_District_Food_Miles;
FDfoodbarchart[10].Co2 = foodmile[5].Local_Financial_District_Food_Miles;
FDfoodbarchart[11].Co2 = foodmile[5].Conv_Financial_District_Food_Miles;
FDfoodbarchart[12].Co2 = foodmile[6].Local_Financial_District_Food_Miles;
FDfoodbarchart[13].Co2 = foodmile[6].Conv_Financial_District_Food_Miles;
FDfoodbarchartlink = "https://docs.google.com/spreadsheets/d/e/2PACX-1vQJi6qcVeQdmk5SVWmCvSYHnz7tynk64zCRfYYax4JgT3DVpa1692_rT1I0jf0ylIGhdEwAUVr7rsv7/pub?gid=154398284&single=true&output=csv"
FDfoodbarchart
X
Local_VS_Conv
Y
Co2
Color
Local_VS_Conv
Size
—
Facet X
Products
Facet Y
—
Mark
bar
Type Chart, then Shift-Enter. Ctrl-space for more options.
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