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* revert all commits to before Typescript migration * update compat workflow to match latest deps (#2335) * update compat workflow to match latest deps * attempt to debug * attempt to debug * remove debugging code * typo * update deps to match desktop (#2340) * fix: don't run lint with `--fix` on push tests (#2273) * fix: don't run lint with `--fix` on push tests * npx Co-authored-by: maniarathi <mani.arathi@gmail.com> Co-authored-by: Madison Dunitz <madison.dunitz@chanzuckerberg.com> * rename X_approx_distribution to X_approximate_distribution (#2337) * Correctly handle non-finite numbers in heuristic determination of X distribution (#2342) * handle non-finites explicitly * improve and test edge case handling for distribution estimation * revert debugging changes * code readability * clean up type inferencing (#2332) * unit tests for 64 bit conversion * clean up type handling * type inference tests * more type inference fixes * use schema to determine user intent for data typing * stop using deprecated API * fbs type encoding test * add missing test * add more tests * correctly infer X type for CXG adaptor * lint * fix typo * ts migration * cleanup from PR review * lint * PR review changes * remove unused packages from client (#2359) * remove unused packages from client * add missing peer dep * fix: disable FE auth testing on compatibility tests (#2377) * update: release process (#2277) Co-authored-by: maniarathi <mani.arathi@gmail.com> * fix: remove spaces in param setup (#2380) * delete deploy workflow (#2396) * undo reformatting which now does not pass lint * fix snapshots which changed due to npm dep changes * add missing quoting to snapshot * another snapshot typo fix * TS Revert (2) - replay PR #2347 and #2354 (#2403) * replay edits from PR 2347 * TS Revert (3) - replay edits in PR #2327 (#2404) * replay edits in PR 2327 * TS Revert (4) - replay PR #2355 (#2405) * replay edits in PR 2355 * add additional babel config * reformat with new prettier config Co-authored-by: Severiano Badajoz <sbadajoz@chanzuckerberg.com> Co-authored-by: maniarathi <mani.arathi@gmail.com> Co-authored-by: Madison Dunitz <madison.dunitz@chanzuckerberg.com>
282 lines
6.5 KiB
JavaScript
282 lines
6.5 KiB
JavaScript
import * as Dataframe from "../../../src/util/dataframe";
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function float32Conversion(f) {
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return new Float32Array([f])[0];
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}
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describe("Dataframe column summary", () => {
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test("empty column test", () => {
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const df = Dataframe.Dataframe.create([0, 1], [[]]);
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const summary = df.icol(0).summarize();
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expect(summary).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: [],
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categoryCounts: new Map(),
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numCategories: 0,
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})
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);
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});
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test("simple test", () => {
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const df = new Dataframe.Dataframe(
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[1, 6],
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[
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["n1"],
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["hi"],
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[true],
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new Float32Array([39.3]),
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new Int32Array([99]),
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[1],
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],
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null,
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new Dataframe.KeyIndex([
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"name",
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"nameString",
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"nameBoolean",
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"nameFloat32",
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"nameInt32",
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"nameCategorical",
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])
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);
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expect(df.icol(0).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: ["n1"],
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categoryCounts: new Map([["n1", 1]]),
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numCategories: 1,
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})
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);
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expect(df.icol(1).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: ["hi"],
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categoryCounts: new Map([["hi", 1]]),
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numCategories: 1,
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})
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);
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expect(df.icol(2).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: [true],
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categoryCounts: new Map([[true, 1]]),
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numCategories: 1,
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})
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);
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expect(df.icol(3).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: float32Conversion(39.3),
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max: float32Conversion(39.3),
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nan: 0,
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ninf: 0,
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pinf: 0,
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})
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);
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expect(df.icol(4).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: 99,
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max: 99,
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nan: 0,
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ninf: 0,
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pinf: 0,
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})
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);
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expect(df.icol(5).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: [1],
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categoryCounts: new Map([[1, 1]]),
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numCategories: 1,
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})
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);
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});
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test("multi test", () => {
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const df = new Dataframe.Dataframe(
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[3, 6],
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[
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["n0", "n1", "n2"],
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["hi", "hi", "bye"],
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[false, true, true],
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new Float32Array([39.3, 39.3, 0]),
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new Int32Array([99, 99, 99]),
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[1, false, "0"],
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],
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null,
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new Dataframe.KeyIndex([
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"name",
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"nameString",
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"nameBoolean",
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"nameFloat32",
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"nameInt32",
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"nameCategorical",
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])
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);
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expect(df.icol(0).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining(["n0", "n1", "n2"]),
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categoryCounts: new Map([
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["n0", 1],
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["n1", 1],
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["n2", 1],
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]),
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numCategories: 3,
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})
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);
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expect(df.icol(1).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining(["hi", "bye"]),
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categoryCounts: new Map([
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["hi", 2],
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["bye", 1],
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]),
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numCategories: 2,
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})
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);
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expect(df.icol(2).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining([true, false]),
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categoryCounts: new Map([
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[true, 2],
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[false, 1],
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]),
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numCategories: 2,
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})
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);
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expect(df.icol(3).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: 0,
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max: float32Conversion(39.3),
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nan: 0,
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ninf: 0,
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pinf: 0,
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})
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);
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expect(df.icol(4).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: 99,
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max: 99,
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nan: 0,
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ninf: 0,
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pinf: 0,
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})
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);
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expect(df.icol(5).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining([1, false, "0"]),
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categoryCounts: new Map([
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[1, 1],
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[false, 1],
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["0", 1],
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]),
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numCategories: 3,
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})
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);
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});
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test("non-finite numbers", () => {
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const df = new Dataframe.Dataframe(
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[4, 6],
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[
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["n0", "n1", "n2", "n2"],
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["hi", "hi", "bye", "bye"],
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[false, true, true, true],
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new Float32Array([
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39.3,
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Number.NEGATIVE_INFINITY,
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Number.NaN,
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Number.POSITIVE_INFINITY,
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]),
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new Int32Array([99, 99, 99, 99]),
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[1, false, "0", "0"],
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],
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null,
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new Dataframe.KeyIndex([
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"name",
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"nameString",
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"nameBoolean",
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"nameFloat32",
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"nameInt32",
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"nameCategorical",
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])
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);
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expect(df.icol(0).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining(["n0", "n1", "n2"]),
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categoryCounts: new Map([
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["n0", 1],
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["n1", 1],
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["n2", 2],
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]),
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numCategories: 3,
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})
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);
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expect(df.icol(1).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining(["hi", "bye"]),
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categoryCounts: new Map([
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["hi", 2],
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["bye", 1],
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]),
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numCategories: 2,
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})
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);
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expect(df.icol(2).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining([true, false]),
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categoryCounts: new Map([
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[true, 2],
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[false, 1],
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]),
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numCategories: 2,
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})
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);
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expect(df.icol(3).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: float32Conversion(39.3),
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max: float32Conversion(39.3),
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nan: 1,
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ninf: 1,
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pinf: 1,
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})
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);
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expect(df.icol(4).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: 99,
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max: 99,
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nan: 0,
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ninf: 0,
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pinf: 0,
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})
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);
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expect(df.icol(5).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining([1, false, "0"]),
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categoryCounts: new Map([
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[1, 1],
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[false, 1],
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["0", 1],
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]),
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numCategories: 3,
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})
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);
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});
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});
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