danfojs

/** * @license * Copyright 2022 JsData. All rights reserved. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ========================================================================== */ import Configs from "../shared/config"; import { NDframeInterface, NdframeInputDataType, AxisType, ArrayType1D, ArrayType2D } from '../shared/types'; /** * N-Dimension data structure. Stores multi-dimensional * data in a size-mutable, labeled data structure. Analogous to the Python Pandas DataFrame. * * @param Object * * data: 1D or 2D Array, JSON, Tensor, Block of data. * * index: Array of numeric or string names for subseting array. If not specified, indexes are auto generated. * * columns: Array of column names. If not specified, column names are auto generated. * * dtypes: Array of data types for each the column. If not specified, dtypes inferred. * * config: General configuration object for NDframe * * @returns NDframe */ export default class NDframe implements NDframeInterface { $isSeries: boolean; protected $data: any; protected $dataIncolumnFormat: ArrayType1D | ArrayType2D; protected $index: Array<string | number>; protected $columns: string[]; protected $dtypes: Array<string>; protected $config: Configs; constructor({ data, index, columns, dtypes, config, isSeries }: NdframeInputDataType); /** * Internal function to load array of data into NDFrame * @param data The array of data to load into NDFrame * @param index Array of numeric or string names for subsetting array. * @param columns Array of column names. * @param dtypes Array of data types for each the column. */ private loadArrayIntoNdframe; /** * Internal function to format and load a Javascript object or object of arrays into NDFrame. * @param data Object or object of arrays. * @param type The type of the object. There are two recognized types: * * - type 1 object are in JSON format `[{a: 1, b: 2}, {a: 30, b: 20}]`. * * - type 2 object are of the form `{a: [1,2,3,4], b: [30,20, 30, 20}]}` * @param index Array of numeric or string names for subsetting array. * @param columns Array of column names. * @param dtypes Array of data types for each the column. */ private loadObjectIntoNdframe; /** * Converts and returns the data in the NDframe as a Tensorflow.js Tensor. */ get tensor(): any; /** * Returns the dtypes of the columns */ get dtypes(): Array<string>; /** * Internal function to set the Dtypes of the NDFrame from an array. This function * performs the necessary checks. */ $setDtypes(dtypes: Array<string> | undefined): void; /** * Returns the dimension of the data. Series have a dimension of 1, * while DataFrames have a dimension of 2. */ get ndim(): number; /** * Returns the axis labels of the NDFrame. */ get axis(): AxisType; /** * Returns the configuration object of the NDFrame. */ get config(): Configs; /** * Internal function to set the configuration of the ndframe */ $setConfig(config: Configs): void; /** * Returns the indices of the NDFrame */ get index(): Array<string | number>; /** * Internal function to set the index of the NDFrame with the specified * array of indices. Performs all necessary checks to ensure that the * index is valid. */ $setIndex(index: Array<string | number> | undefined): void; /** * Internal function to reset the index of the NDFrame using a range of indices. */ $resetIndex(): void; /** * Returns the column names of the NDFrame */ get columns(): string[]; /** * Internal function to set the column names for the NDFrame. This function * performs a check to ensure that the column names are unique, and same length as the * number of columns in the data. */ $setColumnNames(columns?: string[]): void; /** * Returns the shape of the NDFrame. Shape is determined by [row length, column length] */ get shape(): Array<number>; /** * Returns the underlying data in Array format. */ get values(): ArrayType1D | ArrayType2D; /** * Updates the internal $data property to the specified value * @param values An array of values to set * @param checkLength Whether to check the length of the new values and the existing row length * @param checkColumnLength Whether to check the length of the new values and the existing column length * */ $setValues(values: ArrayType1D | ArrayType2D, checkLength?: boolean, checkColumnLength?: boolean): void; /** * Returns the underlying data in Array column format. * Similar to this.values, but in column format. */ get getColumnData(): ArrayType1D | ArrayType2D; /** * Returns the size of the NDFrame object * */ get size(): number; /** * Converts a DataFrame or Series to CSV. * @deprecated Use `toCSV` function directly instead. * @example * ``` * import * as dfd from "danfojs" * const df = new dfd.DataFrame([[1, 2, 3], [4, 5, 6]]) * const csv = dfd.toCSV(df) * ``` * @example * ``` * import { toCSV } from "danfojs-node" * const df = new DataFrame([[1, 2, 3], [4, 5, 6]]) * toCSV(df, { * filePath: "./data/sample.csv", * header: true, * sep: "+" * }) */ toCSV(options?: any): string; /** * Converts a DataFrame or Series to JSON. * @deprecated Use `toJSON` function directly instead. * @example * ``` * import * as dfd from "danfojs-node" * const df = new dfd.DataFrame([[1, 2, 3], [4, 5, 6]]) * const json = dfd.toJSON(df) * ``` * @example * ``` * import { toJSON } from "danfojs-node" * const df = new DataFrame([[1, 2, 3], [4, 5, 6]]) * toJSON(df, { * filePath: "./data/sample.json", * format: "row" * }) * ``` */ toJSON(options?: any): object; /** * Converts a DataFrame or Series to Excel. * @deprecated Use `toExcel` function directly instead. * @example * ``` * import * as dfd from "danfojs" * const df = new dfd.DataFrame([[1, 2, 3], [4, 5, 6]]) * dfd.toExcel(df, { * filePath: "./data/sample.xlsx", * sheetName: "MySheet", * }) * ``` * * @example * ``` * import { toExcel } from "danfojs-node" * const df = new DataFrame([[1, 2, 3], [4, 5, 6]]) * toExcel(df, { * filePath: "./data/sample.xlsx", * sheetName: "MySheet", * }) * ``` */ toExcel(options?: any): void; /** * Pretty prints a DataFrame or Series to the console */ print(): void; }