Add/Update Typescript types for new features in browser

Author: risenW

danfojs-browser/src/core/generic.js

@@ -414,7 +414,7 @@ export default class NDframe {
   /**
      * Converts a DataFrame or Series to JSON.
      * @param options Configuration object. Supported options:
-     * - `filePath`: The file path to write the JSON to. If not specified, the JSON object is returned.
+     * - `fileName`: The file path to write the JSON to. If not specified, the JSON object is returned.
      * - `format`: The format of the JSON. Defaults to `'column'`. E.g for using `column` format:
      * ```
      * [{ "a": 1, "b": 2, "c": 3, "d": 4 },

danfojs-browser/src/io/io.csv.js

@@ -44,10 +44,10 @@ import { DataFrame } from '../index';
  * const df = await readCSV("./data/sample.csv")
  * ```
  */
-const $readCSV = async (file, options) => {
+const $readCSV = async (filePath, options) => {
   options = { header: true, dynamicTyping: true, ...options };
   return new Promise((resolve) => {
-    Papa.parse(file, {
+    Papa.parse(filePath, {
       ...options,
       download: true,
       complete: (results) => {

danfojs-browser/types/config/config.d.ts

@@ -0,0 +1,188 @@
+/**
+*  @license
+* Copyright 2021, 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 Series from "./series";
+import { ArrayType1D, DateTime } from "../shared/types";
+/**
+ * Format and handle all datetime operations on Series or Array of date strings
+ * @param data Series or Array of date strings
+ */
+export default class TimeSeries implements DateTime {
+   private $dateObjectArray;
+   constructor(data: Series | ArrayType1D);
+   /**
+    * Processed the data values into internal structure for easy access
+    * @param dateArray An array of date strings
+   */
+   private processData;
+   /**
+    *  Returns the month, in local time.
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-01",
+    * "2019-03-01",
+    * "2019-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const dfNew = df.dt.month()
+    * console.log(dfNew.values)
+    * // [1, 2, 3, 4]
+    * ```
+   */
+   month(): Series;
+   /**
+    * Returns the day of the week, in local time
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-01",
+    * "2019-03-01",
+    * "2019-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const dayOfWeek = df.dt.day()
+    * console.log(day.values)
+    * ```
+   */
+   day(): Series;
+   /**
+    * Returns the year, in local time
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-01",
+    * "2021-03-01",
+    * "2020-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const year = df.dt.year()
+    * console.log(year.values)
+    * // [2019, 2019, 2021, 2020]
+    * ```
+   */
+   year(): Series;
+   /**
+    *  Returns the name of the month, in local time
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-01",
+    * "2021-03-01",
+    * "2020-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const monthName = df.dt.month_name().values
+    * console.log(monthName)
+    * // ["January", "February", "March", "April"]
+    * ```
+   */
+   month_name(): Series;
+   /**
+    * Returns the name of the day, of the week, in local time
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-01",
+    * "2021-03-01",
+    * "2020-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const dayOfWeekName = df.dt.weekdays().values
+    * console.log(dayOfWeekName)
+    * ```
+   */
+   weekdays(): Series;
+   /**
+    * Returns the day of the month, in local time
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-05",
+    * "2021-03-02",
+    * "2020-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const dayOfMonth = df.dt.monthday().values
+    * console.log(dayOfMonth)
+    * // [1, 5, 2, 1]
+    * ```
+   */
+   monthday(): Series;
+   /**
+    * Returns the hour of the day, in local time
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-05",
+    * "2021-03-02",
+    * "2020-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const hour = df.dt.hour().values
+    * console.log(hour)
+    * // [0, 0, 0, 0]
+    * ```
+   */
+   hours(): Series;
+   /**
+    * Returns the second of the day, in local time
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-05",
+    * "2021-03-02",
+    * "2020-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const second = df.dt.second().values
+    * console.log(second)
+    * ```
+   */
+   seconds(): Series;
+   /**
+    * Returns the minute of the day, in local time
+    * @example
+    * ```
+    * import { Dataframe } from "danfojs-node"
+    * const data = [
+    * "2019-01-01",
+    * "2019-02-05",
+    * "2021-03-02",
+    * "2020-04-01",
+    * ]
+    * const df = new Dataframe(data)
+    * const minute = df.dt.minute().values
+    * console.log(minute)
+    * ```
+   */
+   minutes(): Series;
+}
+export declare const toDateTime: (data: Series | ArrayType1D) => TimeSeries;