Data Scientist, Author, DataVis, Educator, Speaker, Public Service @ClintonBrownley
https://cbrownley.github.io
Public
Edited
Feb 13
7 forks
stackedData = d3.stack().keys()(tableData)
// <-- Add the variable "age_buckets" here (i.e. the list of age bucket strings)
tableData = groupToStack(df, //attr1 , //attr2 ) // <-- Add the two relevant attributes from the dataset `df` to group by (i.e. "nationality" and "age_bucket") as strings here
.map((d, i) => ({
...d,
total: total_players_by_nationality.get(d.nationality)
}))
.sort((a, b) => b.total - a.total)
df = {
const bucketize = (val) => {
let result = "";
if (val <= 20) result = "age_lte_20";
else if (val > 20 && val <= 25) result = "age_21_25";
else if (val > 25 && val <= 30) result = "age_26_30";
else if (val > 30 && val <= 35) result = "age_31_35";
else if (val > 35 && val <= 40) result = "age_36_40";
else if (val > 40) result = "age_gt_40";
return result;
};
const mutate = (df) =>
df_imported.map((df) => ({
age_bucket: bucketize(df["age"]),
...df
}));
return mutate(df_imported);
}
total_players_by_nationality = d3.rollup(
df,
(v) => v.length,
(d) => d.nationality
)
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