Published
Edited
Sep 27, 2021
1 fork
majorsData
vl.markBar()
.data(majorsData)
.encode(
//Code here -- be careful with aggregating the data across the years
)
.render()
vl.markBar()
.data(majorsData)
.encode(
//Code here
)
.render()
vl.markPoint({filled: true}) // What happens if filled is false? What is the default?
.data(majorsData)
.encode(
// Code here
)
.render()
vl.markPoint({filled: true})
.data(majorsData)
.encode(
// Code here
)
.render()
vl.markBar()
.data(majorsData)
.encode(
//Code Here
)
.render()
vl.markBar()
.data(majorsData)
.encode(
//Code here -- After making the bar chart as above, try normalizing the bars to cover the full range of the y-axis
)
.render()
vl.markArea()
.data(majorsData)
.encode(
// Code here -- again try normalizing the data on the y-axis.
vl.tooltip(['Subject', 'Number of Students'])
)
.render()
vl.markLine()
.data(majorsData)
.encode(
// Code here
vl.tooltip(['Subject', 'Number of Students'])
)
.render()
vl.markRect()
.data(majorsData)
.encode(
//Code here
)
.render()
vl.markCircle()
.data(majorsData)
.encode(
//Code here
)
.render()
vl.markBar()
.data(majorsData)
.encode(
//Code here
)
// .width(130)
.render()
vl.markArc({"stroke": "#fff"}) //What does setting this stroke property do? Try removing it here.
.data(majorsData)
.encode(
//Code here
vl.tooltip(['Year', 'Number of Students'])
)
.render()
vl.markArc({"stroke": "#fff"})
.data(majorsData)
.encode(
//Code here
vl.tooltip(['Subject', 'Number of Students'])
)
.render()
viewof test = vl.markPoint()
.data(majorsData)
.transform(
//Code the pivot here
vl.pivot(/* data field */).value(/* data field*/).groupby([/*data field*/])
)
.encode(
//Code here
vl.tooltip("StartYear")
)
.render()
//Use this to visualize the data before and after the pivot. source_0 is the source data, data_0 is the pivoted data
vegaDataViewer(test, {dataset: "source_0"})
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