input_data = tpx_table.sheet(0,{headers: true})
tpx_table = FileAttachment("tpx_table.xlsx").xlsx()
getLabelPart = (label, partIndex) => label.split(": ")[partIndex]
substractObjects = (r1, r2) => {
return Object.keys(r1).reduce((a, k) => {
a[k] = typeof r1[k] == "string"? r1[k]: (typeof r1[k] != "undefined") && (typeof r2[k] != "undefined")? r1[k] - r2[k]: NaN;
return a;
}, {});
}
input_data_mapped = input_data.map(o => {
return {
touchpoint: getLabelPart(o["Touchpoint Experience"],2),
...o,
quadrant: getLabelPart(o["Touchpoint Experience"],1),
period: getLabelPart(o["Touchpoint Experience"],0)
}
})
input_data_indexed = d3.index(input_data_mapped, o => o.period, o => o.quadrant, o => o.touchpoint)
quadrantsFilterOptions = Array.from ( new Set( input_data_mapped.map(o => o.quadrant) ) )
periods = Array.from ( new Set ( input_data_mapped.map(o => o.period) ) )
periodsFilterOptions = [periods[0], `${periods[0]} vs ${periods[1]}`]
touchpoints = Array.from ( new Set ( input_data_mapped.map(o => o.touchpoint) ) )
forTable = period == periods[0]? touchpoints.map( o => input_data_indexed.get(period).get(quadrant).get(o) ) : touchpoints.map( o => substractObjects( input_data_indexed.get(periods[0]).get(quadrant).get(o), input_data_indexed.get(periods[1]).get(quadrant).get(o) ) )
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.
