The avatar for @ammanyusuf
Amman Yusuf
Undergraduate Computer Science student at the University of Calgary.
Published unlisted
Edited
Apr 19, 2022
24
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From above, one can see how certain cancer ASIR rates seem to have a linear relationship with the health indicators. For example, take the positive linear relationship between "Current smoker, daily or occasional" and lung and bronchus cancer. What about "High boold pressure" and melanoma. To better visualize this correlation, I computed the following heat map of the correlation coefficient.
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md`${await FileAttachment("pca-variance-final@1.png").image()}${await FileAttachment("pca-final@1.png").image()}`
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color_mortality = d3.scaleThreshold()
.domain([color_selection_mortality[9][1], color_selection_mortality[5][1], color_selection_mortality[2][1], color_selection_mortality[1][1]])
.range(d3.schemeReds[4])
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color_selection_mortality = Array.from(new Map([...map_data_mortality.entries()].sort((a,b) => a[1] < b[1])));
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mapHeight = 300
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mapWidth = 550
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// Edit the iso code to the origina data for mortality
fig_2_4_2_5_data_provinces.map(function(d) {
d.iso_id = "CA-" + d["Location"];
return d;
});
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map_data_mortality = Object.assign(new Map(fig_2_4_2_5_data_provinces.filter(d => d["Cancer Type"] == cancer_select_mortality_map && d["Sex"] == sex_select_mortality_map).map(d => {
return [d.iso_id, d[selected_value_mortality_map]];
})), {title: selected_value_mortality_map}).set('CA-NU', -1).set('CA-NT', -1).set('CA-YT', -1);
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topojson.feature(canada_provinces_geo_json_2, canada_provinces_geo_json_2.objects.canadaprov).features
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canada_provinces_geojson = FileAttachment("canada_provinces.geojson").json()
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indicators_data.map(function(item) {
if (item["REF_DATE"] instanceof Date) {
return item;
} else {
item["REF_DATE"] = new Date(Date.UTC(item["REF_DATE"], 0, 1));
return item;
}
});
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fig_1_4_1_5_data_provinces = FileAttachment("fig_1_5_1_4_combined-by-province.csv").csv()
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fig_1_4_1_5_data_provinces.map(function(item) {
item["Projected Cases"] = parseInt(item["Projected Cases"]);
return item;
});
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fig_1_4_1_5_data_provinces.map(function(item) {
item["ASIR (Cases per 100,000) "] = parseFloat(item["ASIR (Cases per 100,000) "]);
return item;
});
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viewof summary_fig_1_4_1_5_data = SummaryTable(fig_1_4_1_5_data_provinces,
{label: html`<b>Projected cases and ASIR (cases per 100,000) of cancer types by province and sex</b>`})
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fig_2_4_2_5_data_provinces = FileAttachment("fig-2.4-2.5-combined-by-province.csv").csv()
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fig_2_4_2_5_data_provinces.map(function(item) {
item["Projected Cases"] = parseInt(item["Projected Cases"]);
return item;
});
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fig_2_4_2_5_data_provinces.map(function(item) {
item["ASMR (per 100,000)"] = parseFloat(item["ASMR (per 100,000)"]);
return item;
});
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viewof summary_fig_2_4_2_5_data = SummaryTable(fig_2_4_2_5_data_provinces,
{label: html`<b>Projected mortality and ASMR (cases per 100,000) of cancer types by province and sex</b>`})
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fig_1_3_data = FileAttachment("fig-1.3-tidy-asir-percentage-sex-age.csv").csv({typed: true})
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fig_1_6_data = FileAttachment("fig-1.6-tidy-asir-cases-sex-year.csv").csv({typed: true})
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fig_1_6_data.map(function(item) {
if (item["Year"] instanceof Date) {
return item;
} else {
item["Year"] = new Date(Date.UTC(item["Year"], 0, 1));
return item;
}
});
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fig_2_3_data = FileAttachment("fig-2.3-tidy-asmr-percentage-sex-age.csv").csv({typed: true})
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fig_2_6_data = FileAttachment("fig-2.6-tidy-asmr-cases-sex-year.csv").csv()
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fig_2_6_data.map(function(item) {
item["ASMR (per 100,000)"] = parseFloat(item["ASMR (per 100,000)"]);
item["Deaths (in thousands)"] = parseFloat(item["Deaths (in thousands)"]);
if (item["Year"] instanceof Date) {
return item;
} else {
item["Year"] = new Date(Date.UTC(item["Year"], 0, 1));
return item;
}
});
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fig_S1_1_projected_cases_2021 = FileAttachment("fig-S1.1-TIDY-projected-cases-2021-2.csv").csv()
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fig_S1_1_projected_cases_2021.map(function(d) {
d["Projected new cases"] = parseInt(d["Projected new cases"]);
return d;
})
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fig_S1_2_projected_asir_2021 = FileAttachment("fig-S1.2-tidy-projected-asir-rates-2021.csv").csv()
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fig_S1_3_data = FileAttachment("fig-S1.3-1.3-1.5-tidy-asir-by-year-sex-cancer-type-TIDY.csv").csv()
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// Convert date of figS1_3 into date format
fig_S1_3_data.map(function(item) {
if (item["Year"] instanceof Date) {
return item;
} else {
item["Year"] = new Date(Date.UTC(item["Year"], 0, 1));
return item;
}
});
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fig_S2_1_projected_deaths_2022 = FileAttachment("fig-S2.1-tidy-projected-deaths-2021-2.csv").csv()
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fig_S2_1_projected_deaths_2022.map(function(d) {
d["Projected deaths"] = parseInt(d["Projected deaths"]);
return d;
})
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viewof summary_data_S2_1 = SummaryTable(fig_S2_1_projected_deaths_2022.map(function(item) {
delete item["Table Name"];
delete item["* Note"];
delete item["Analysis By"];
delete item["Note"];
delete item["Data Sources"];
return item;
}), {label: html`<b>Data summary Table S2.1 - Projected deaths by cancer type, age, and sex</b>`})
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fig_S2_2_projected_asmr_2021 = FileAttachment("fig-S2.2-tidy-asmr-deadliest-cancers.csv").csv()
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fig_S2_3_data = FileAttachment("fig-S2.3-2.4-2.5-asmr-by-year-sex-cancer-type-TIDY.csv").csv()
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// Convert date of figS1_3 into date format
fig_S2_3_data.map(function(item) {
item["Age-standardized mortality rate (ASMR)"] = parseFloat(item["Age-standardized mortality rate (ASMR)"]);
if (item["Year"] instanceof Date) {
return item;
} else {
item["Year"] = new Date(Date.UTC(item["Year"], 0, 1));
return item;
}
});
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viewof summary_data_S2_3 = SummaryTable(fig_S2_3_data.map(function(item) {
delete item["Table Name"];
delete item["* Note"];
delete item["Analysis By"];
delete item["Note"];
delete item["Data Sources"];
delete item["Liver Note"];
return item;
}), {label: html`<b>Data summary Table S2.1 - Projected deaths by cancer type, age, and sex</b>`})
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import { SummaryTable } from "@observablehq/summary-table"
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import {Plot} from "@mkfreeman/plot-tooltip"
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import {addTooltips} from "@mkfreeman/plot-tooltip"
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import {PieChart} from "@ammanyusuf/pie-chart"
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import {GroupedBarChart} from "@d3/grouped-bar-chart"
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import {StackedBarChart} from "@d3/stacked-normalized-horizontal-bar"
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import {Legend, Swatches} from "@d3/color-legend"
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import {StackedAreaChart} from "@d3/stacked-area-chart"
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import { autoSelect, select, number, checkbox, slider } from "@jashkenas/inputs"
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import {legend} from "@d3/color-legend"
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import {searchCheckbox} from "@ammanyusuf/search-checkbox"
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import {ScatterplotMatrix} from "@d3/splom"
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d3 = require("d3@6")
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