Public
Edited
Apr 4, 2022
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yearly_count_subject = FileAttachment("count_subjects.csv").csv()
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tot_weekly_commit = extract_weekly_commit()
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range_date = d3.extent(contrib_python[0]['weeks'].map(d => d.w))
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contrib_python = FileAttachment("contrib_python.json").json()
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total_yearly_contrib = FileAttachment("total_count.csv").csv({typed:true})
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summary_all = FileAttachment("text_summary_all@3.csv").csv({typed:true})
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import { tidy, mutate, arrange, desc, count, sliceMax } from '@pbeshai/tidyjs'
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import { swatches } from "@d3/color-legend"
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import {addLegend, addColorLegend, colorLegend} from "@ambassadors/plot-color-legend"
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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.
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