MTA_Daily_Ridership_Data__Beginning_2020-9.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
mta
X
Date
Y
Subways: Total Estimated Ridership
Color
—
Size
—
Facet X
—
Facet Y
—
Mark
Auto
Type Chart, then Shift-Enter. Ctrl-space for more options.
myValue = {
const a = 10;
const b = 20;
return a + b;
}
myValue * 20
myOtherValue = 200 + myValue
mta
myNewDatabase = DuckDBClient.of({mta})
myEndpointData = d3.json("https://data.ny.gov/resource/vxuj-8kew.json")
mta
X
Date
Y
Subways: Total Estimated Ridership
Color
Date
Size
—
Facet X
—
Facet Y
—
Mark
dot
Type Chart, then Shift-Enter. Ctrl-space for more options.
pizza
Type Table, then Shift-Enter. Ctrl-space for more options.
viewof selectCategory = Inputs.select(["Classic", "Specialty","Vegetarian"], {label: "Select one"})
MyPizzaData
Plot.plot({
marks: [
Plot.rectY(myFilteredData, {
x: "order_date",
y: "orders",
interval: d3.utcDay}),
Plot.ruleY([0])
]
})
MyPizzaData
X
order_date
Y
sum
orders
Color
—
Size
—
Facet X
category
Facet Y
day_of_week
Mark
Auto
Type Chart, then Shift-Enter. Ctrl-space for more options.
Plot.plot({
marginLeft: 100,
marginRight: 200,
marks: [
Plot.frame({ strokeOpacity: 0.1 }),
Plot.rectY(
MyPizzaData,
Plot.binX(
{ y: "sum" },
{
fx: "category",
fy: "day_of_week",
x: "order_date",
y: "orders",
fill: "category",
tip: true
}
)
),
Plot.ruleY([0])
]
})
myChart = Plot.plot({
marks: [
Plot.areaY(aapl, {x: "Date", y: "Close"}),
Plot.ruleY([0])
]
})
import {data} from "@pstuffa/density-contour-matrix-with-brushing"
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
