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risenWrisenW
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Merge pull request #418 from NeonSpork/pct_change-port
feat: Added `pctChange()` to DataFrame and `divNoNan()` to `$MathOps` in DataFrame
2 parents b712f70 + a6d0372 commit f49f16c

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‎src/danfojs-base/core/frame.ts‎

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Original file line numberDiff line numberDiff line change
@@ -329,6 +329,9 @@ export default class DataFrame extends NDframe implements DataFrameInterface {
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case 'div':
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tensorResult = tensors[0].div(tensors[1])
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break;
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case 'divNoNan':
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tensorResult = tensors[0].divNoNan(tensors[1])
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break;
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case 'mul':
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tensorResult = tensors[0].mul(tensors[1])
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break;
@@ -726,6 +729,36 @@ export default class DataFrame extends NDframe implements DataFrameInterface {
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return this.$MathOps(tensors, "div", inplace)
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}
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/**
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* Return division of DataFrame with other, returns 0 if denominator is 0.
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* @param other DataFrame, Series, Array or Scalar number to divide with.
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* @param options.axis 0 or 1. If 0, compute the division column-wise, if 1, row-wise
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* @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false
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* @example
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* ```
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* const df = new DataFrame([[1, 2], [3, 4]], { columns: ['A', 'B'] })
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* const df2 = df.divNoNan(2)
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* df2.print()
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* ```
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*/
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divNoNan(other: DataFrame | Series | number[] | number, options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame
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divNoNan(other: DataFrame | Series | number[] | number, options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void {
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const { inplace, axis } = { inplace: false, axis: 1, ...options }
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if (this.$frameIsNotCompactibleForArithmeticOperation()) {
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throw Error("TypeError: div operation is not supported for string dtypes");
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}
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if ([0, 1].indexOf(axis) === -1) {
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throw Error("ParamError: Axis must be 0 or 1");
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}
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const tensors = this.$getTensorsForArithmeticOperationByAxis(other, axis);
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return this.$MathOps(tensors, "divNoNan", inplace)
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}
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/**
@@ -1333,6 +1366,87 @@ export default class DataFrame extends NDframe implements DataFrameInterface {
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}
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/**
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* Return percentage difference of DataFrame with other.
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* @param other DataFrame, Series, Array or Scalar number (positive numbers are preceding rows, negative are following rows) to compare difference with.
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* @param options.axis 0 or 1. If 0, compute the difference column-wise, if 1, row-wise
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* @param options.inplace Boolean indicating whether to perform the operation inplace or not. Defaults to false
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* @example
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* ```
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* const df = new DataFrame([[1, 2, 3, 4, 5, 6], [1, 1, 2, 3, 5, 8], [1, 4, 9, 16, 25, 36]], { columns: ['A', 'B', 'C'] })
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*
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* // Percentage difference with previous row
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* const df0 = df.pctChange(1)
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* console.log(df0)
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*
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* // Percentage difference with previous column
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* const df1 = df.pctChange(1, {axis: 0})
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* console.log(df1)
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*
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* // Percentage difference with previous 3rd previous row
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* const df2 = df.pctChange(3)
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* console.log(df2)
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*
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* // Percentage difference with following row
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* const df3 = df.pctChange(-1)
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* console.log(df3)
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*
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* // Percentage difference with another DataFrame
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* const df4 = df.pctChange(df3)
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* console.log(df4)
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* ```
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*/
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pctChange(other: DataFrame | Series | number[] | number, options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame
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pctChange(other: DataFrame | Series | number[] | number, options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void {
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const { inplace, axis } = { inplace: false, axis: 1, ...options }
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if (this.$frameIsNotCompactibleForArithmeticOperation()) {
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throw Error("TypeError: pctChange operation is not supported for string dtypes");
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}
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if ([0, 1].indexOf(axis) === -1) {
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throw Error("ParamError: Axis must be 0 or 1");
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}
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if (other === 0) {
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return this;
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}
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if (typeof other === "number") {
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let origDF = this.copy() as DataFrame;
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if (axis === 0) {
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origDF = origDF.T;
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}
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const originalTensor = origDF.tensor.clone();
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const unit = new Array(originalTensor.shape[originalTensor.rank - 1]).fill(NaN);
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let pctArray: any[] = originalTensor.arraySync();
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if (other > 0) {
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for (let i = 0; i < other; i++) {
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pctArray.unshift(unit);
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pctArray.pop();
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}
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}
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else if (other < 0) {
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for (let i = 0; i > other; i--) {
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pctArray.push(unit);
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pctArray.shift();
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}
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}
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const pctTensor = tensorflow.tensor2d(pctArray, originalTensor.shape);
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const pctDF = (this.$MathOps([originalTensor, pctTensor], "divNoNan", inplace) as DataFrame).sub(1);
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if (axis === 0) {
1438+
return pctDF.T;
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}
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return pctDF;
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}
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if (other instanceof DataFrame || other instanceof Series) {
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const tensors = this.$getTensorsForArithmeticOperationByAxis(other, axis);
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const pctDF = (this.$MathOps(tensors, "divNoNan", inplace) as DataFrame).sub(1);
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return pctDF;
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}
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}
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/**
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* Return difference of DataFrame with other.
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* @param other DataFrame, Series, Array or Scalar number (positive numbers are preceding rows, negative are following rows) to compare difference with.

‎src/danfojs-base/shared/types.ts‎

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@@ -216,8 +216,10 @@ export interface DataFrameInterface extends NDframeInterface {
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sub(other: DataFrame | Series | number | number[], options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void
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mul(other: DataFrame | Series | number | number[], options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void
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div(other: DataFrame | Series | number | number[], options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void
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divNoNan(other: DataFrame | Series | number | number[], options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void
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pow(other: DataFrame | Series | number | number[], options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void
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mod(other: DataFrame | Series | number | number[], options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void
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pctChange(other: DataFrame | Series | number[] | number, options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void
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diff(other: DataFrame | Series | number[] | number, options?: { axis?: 0 | 1, inplace?: boolean }): DataFrame | void
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mean(options?: { axis?: 0 | 1 }): Series
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median(options?: { axis?: 0 | 1 }): Series

‎src/danfojs-browser/tests/core/frame.test.js‎

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@@ -1018,6 +1018,51 @@ describe("DataFrame", function () {
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});
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describe("pctChange", function () {
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it("Return same DataFrame if other === 0", function () {
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const data = [ [ 0, 2, 4 ], [ 10, 10, 10 ], [ 1, 2, 3 ] ];
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const df = new dfd.DataFrame(data);
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assert.deepEqual((df.pctChange(0)).values, [ [ 0, 2, 4 ], [ 10, 10, 10 ], [ 1, 2, 3 ] ]);
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});
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it("Return difference in percentage of DataFrame with previous row", function () {
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const data = [ [ 90 ], [ 900 ], [ 900 ] ];
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const df = new dfd.DataFrame(data);
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assert.deepEqual((df.pctChange(1)).values, [ [ NaN ], [ 9 ], [ 0 ] ]);
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});
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it("Return difference in percentage of DataFrame with following row", function () {
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const data = [ [ 0, 5, 15 ], [ 10, 10, 10 ], [ 1, 2, 5 ] ];
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const df = new dfd.DataFrame(data);
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assert.deepEqual((df.pctChange(-1)).values, [ [ -1, -0.5, 0.5 ], [ 9, 4, 1 ], [ NaN, NaN, NaN ] ]);
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});
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it("Return difference in percentage of a DataFrame with a Series along default axis 1", function () {
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const data = [ [ 0, 2, 4 ], [ 10, 10, 10 ], [ 1, 2, 3 ] ];
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const sf = new dfd.Series([ 1, 2, 1 ]);
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const df = new dfd.DataFrame(data);
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assert.deepEqual((df.pctChange(sf)).values, [ [ -1, 0, 3 ], [ 9, 4, 9 ], [ 0, 0, 2 ] ]);
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});
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it("Return difference in percentage of a DataFrame with along axis 0 (column-wise), previous column", function () {
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const data = [ [ 0, 2, 4 ], [ 10, 10, 10 ], [ 1, 2, 3 ] ];
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const df = new dfd.DataFrame(data);
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assert.deepEqual((df.pctChange(1, { axis: 0 })).values, [ [ NaN, -1, 1 ], [ NaN, 0, 0 ], [ NaN, 1, 0.5 ] ]);
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});
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it("Return difference in percentage of a DataFrame with along axis 0 (column-wise), following column", function () {
1049+
const data = [ [ 0, 2, 4 ], [ 10, 10, 10 ], [ 1, 2, 8 ] ];
1050+
const df = new dfd.DataFrame(data);
1051+
assert.deepEqual((df.pctChange(-1, { axis: 0 })).values, [ [ -1, -0.5, NaN ], [ 0, 0, NaN ], [ -0.5, -0.75, NaN ] ]);
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});
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it("Return difference in percentage of a DataFrame with another DataFrame along default axis 1", function () {
1054+
const df1 = new dfd.DataFrame([ [ 0, 2, 4 ], [ 3, 10, 4 ] ]);
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const df2 = new dfd.DataFrame([ [ -1, -2, 4 ], [ 6, 5, 0 ] ]);
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assert.deepEqual((df1.pctChange(df2)).values, [ [ -1, -2, 0 ], [ -0.5, 1, -1 ] ]);
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});
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it("Throw error if DataFrame for pctChange contains string", function () {
1059+
const df = new dfd.DataFrame([ [ "words", "words", "words" ], [ "words", "words", "words" ] ]);
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assert.throws(() => {
1061+
df.pctChange(1);
1062+
}, Error, "TypeError: pctChange operation is not supported for string dtypes");
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});
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});
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10211066
describe("diff", function () {
10221067
it("Return same DataFrame if other === 0", function () {
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const data = [ [ 0, 2, 4 ], [ 10, 10, 10 ], [ 1, 2, 3 ] ];

‎src/danfojs-node/test/core/frame.test.ts‎

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Original file line numberDiff line numberDiff line change
@@ -1037,6 +1037,51 @@ describe("DataFrame", function () {
10371037
});
10381038
});
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1040+
describe("pctChange", function () {
1041+
it("Return same DataFrame if other === 0", function () {
1042+
const data = [[0, 2, 4], [10, 10, 10], [1, 2, 3]];
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const df = new DataFrame(data);
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assert.deepEqual((df.pctChange(0) as DataFrame).values, [[0, 2, 4], [10, 10, 10], [1, 2, 3]]);
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});
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it("Return difference in percentage of DataFrame with previous row", function () {
1047+
const data = [[90], [900], [900]];
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const df = new DataFrame(data);
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assert.deepEqual((df.pctChange(1) as DataFrame).values, [[NaN], [9], [0]]);
1050+
});
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it("Return difference in percentage of DataFrame with following row", function () {
1052+
const data = [[0, 5, 15], [10, 10, 10], [1, 2, 5]];
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const df = new DataFrame(data);
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assert.deepEqual((df.pctChange(-1) as DataFrame).values, [[-1, -0.5, 0.5], [9, 4, 1], [NaN, NaN, NaN]]);
1055+
});
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it("Return difference in percentage of a DataFrame with a Series along default axis 1", function () {
1057+
const data = [[0, 2, 4], [10, 10, 10], [1, 2, 3]];
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const sf = new Series([1, 2, 1]);
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const df = new DataFrame(data);
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assert.deepEqual((df.pctChange(sf) as DataFrame).values, [[-1, 0, 3], [9, 4, 9], [0, 0, 2]]);
1061+
});
1062+
it("Return difference in percentage of a DataFrame with along axis 0 (column-wise), previous column", function () {
1063+
const data = [[0, 2, 4], [10, 10, 10], [1, 2, 3]];
1064+
const df = new DataFrame(data);
1065+
assert.deepEqual((df.pctChange(1, { axis: 0 }) as DataFrame).values, [[NaN, -1, 1], [NaN, 0, 0], [NaN, 1, 0.5]]);
1066+
});
1067+
it("Return difference in percentage of a DataFrame with along axis 0 (column-wise), following column", function () {
1068+
const data = [[0, 2, 4], [10, 10, 10], [1, 2, 8]];
1069+
const df = new DataFrame(data);
1070+
assert.deepEqual((df.pctChange(-1, { axis: 0 }) as DataFrame).values, [[-1, -0.5, NaN], [0, 0, NaN], [-0.5, -0.75, NaN]]);
1071+
});
1072+
it("Return difference in percentage of a DataFrame with another DataFrame along default axis 1", function () {
1073+
const df1 = new DataFrame([[0, 2, 4], [3, 10, 4]]);
1074+
const df2 = new DataFrame([[-1, -2, 4], [6, 5, 0]]);
1075+
assert.deepEqual((df1.pctChange(df2) as DataFrame).values, [[-1, -2, 0], [-0.5, 1, -1]]);
1076+
});
1077+
it("Throw error if DataFrame for pctChange contains string", function () {
1078+
const df = new DataFrame([["words", "words", "words"], ["words", "words", "words"]]);
1079+
assert.throws(() => {
1080+
df.pctChange(1);
1081+
}, Error, "TypeError: pctChange operation is not supported for string dtypes");
1082+
});
1083+
});
1084+
10401085
describe("mod", function () {
10411086
it("Return modulus of DataFrame with a single Number", function () {
10421087
const data = [[0, 2, 4], [360, 180, 360]];

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