ETH-USD@3.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
viewof bollingerMultiplier_slider=Inputs.range([1,4], {
label:"Bollinger Standard Deviations",
step:1,
value:2
})
viewof EMA_Slider=Inputs.range([1,100],{
label:'EMA Period',
step:1,
value:9
})
Etherum_price=d3.json("https://www.binance.com/api/v3/ticker/price?symbol=ETHUSDT")
Etherum_price.price = +Etherum_price.price
Etherum_price
// Uncomment to activate
data_forAroundOneYear = aq.from(data_initial)
.filter( aq.escape(d => d["Date"].getFullYear() > 2022 ) )
.objects()
// Uncomment to enable
data_filtered = aq.from(data_initial)
.filter(aq.escape((d) => d["Date"].getFullYear() === year_slider))
.objects()
import {toc} from "@nebrius/indented-toc"
import {Wrangler, op} from "@observablehq/data-wrangler"
import {howTo} from "@clokman/howto"
import {imageToDo} from "@clokman/student-blocks"
imageToDo
viewof year_slider = Inputs.range([2017, 2023], {label: "Amount", step: 1, value: 2023})
numberOfDaysInFilteredData=data_filtered.length
import {Plot} from "@mkfreeman/plot-tooltip"
createTooltipContent = (d) =>
`${ d["Date"].toLocaleString('default', { month: 'long' }) } ${d["Date"].getDate()}
Close: ${ d3.format('.3s')(d["Close"]) }
High: ${ d3.format('.3s')(d["High"]) }
Open: ${ d3.format('.3s')(d["Open"]) }
Low: ${ d3.format('.3s')(d["Low"]) }`
// createTooltipContent = function (d) {
// `${ d["Date"].toLocaleString('default', { month: 'long' }) } ${d["Date"].getDate()}
// Close: ${ d3.format('.3s')(d["Close"]) }
// High: ${ d3.format('.3s')(d["High"]) }
// Open: ${ d3.format('.3s')(d["Open"]) }
// Low: ${ d3.format('.3s')(d["Low"]) }`
// }
fc = require('d3fc')
// Uncoment to enable
emaColumn = fc.indicatorExponentialMovingAverage()
.period( 9 )
.value(d => d["Close"])
( data_filtered )
// Uncoment to enable
bollingerColumn = fc.indicatorBollingerBands()
.value( d => d["Close"] )
.period( bollingerPeriod_slider )
.multiplier( 2 )
( data_filtered )
viewof bollingerPeriod_slider = Inputs.range([0, 100], {
label: "Bollinger Period",
step: 1,
value: 7
})
// Uncoment to enable
macdColumn = fc.indicatorMacd()
.value( d => d["Close"] )
.signalPeriod( 9 )
.fastPeriod( 12 )
.slowPeriod( 26 )
( data_filtered )
// Uncoment to enable
data_filtered_withIndicators = data_filtered.map( (d, i) => ({
ema: emaColumn[i],
macd: macdColumn[i].macd,
macdSignal: macdColumn[i].signal,
macdDivergence: macdColumn[i].divergence,
bollingerUpper: bollingerColumn[i].upper,
bollingerAverage: bollingerColumn[i].average,
bollingerLower: bollingerColumn[i].lower,
...d
}))
// Complete the code
data_fearGreedIndex_raw = d3.json("https://api.alternative.me/fng/?limit=0&format=json")
// Uncomment to activate
data_fearGreedIndex = aq.from(data_fearGreedIndex_raw.data)
.derive({ date: aq.escape(d => new Date(+d["timestamp"] * 1000)) })
.derive({ valueAsNumber: d => +d["value"] })
.select('value_classification','date','valueAsNumber')
.rename({valueAsNumber: "FearGreedValue"})
.rename({value_classification: "FearGreedClass"})
.rename({date: "FearGreedDate"})
.objects()
// Uncomment to activate
data_filtered_withIndicators_withFearGreedIndex = aq.from(data_filtered_withIndicators)
.join(aq.from(data_fearGreedIndex), ["Date", "FearGreedDate"])
.objects()
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.
