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Add prebuild script and update readme
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‎src/danfojs-base/shared/tensorflowlib.ts‎

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const tf = require("@tensorflow/tfjs")
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export default tf
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// This file is auto-generated by prebuild.js. Do not edit!
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const tf = require("@tensorflow/tfjs")
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export default tf
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‎src/danfojs-browser/README.md‎

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```html
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<script src="https://cdn.jsdelivr.net/npm/danfojs@0.2.7/lib/bundle.min.js"></script>
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```
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### Example Usage in the Client Side Frameworks like React, Angular, Vue.js, etc.
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> If you want to use Danfo in frontend frameworks like React/Vue, read this [guide](https://danfo.jsdata.org/examples/using-danfojs-in-react)
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TODO:
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### Example Usage in the Browser
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Danfo.js is hosted on NPM, and can installed via package managers like npm and yarn
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```sh
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npm install danfojs-node
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```
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### Example usage in Nodejs
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```javascript
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const dfd = require("danfojs-node")
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dfd.read_csv("https://web.stanford.edu/class/archive/cs/cs109/cs109.1166/stuff/titanic.csv")
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.then(df => {
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//prints the first five columns
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df.head().print()
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//Calculate descriptive statistics for all numerical columns
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df.describe().print()
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//prints the shape of the data
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console.log(df.shape);
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//prints all column names
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console.log(df.column_names);
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//prints the inferred dtypes of each column
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df.ctypes.print()
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//selecting a column by subsetting
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df['Name'].print()
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//drop columns by names
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cols_2_remove = ['Age', 'Pclass']
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df_drop = df.drop({ columns: cols_2_remove, axis: 1 })
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df_drop.print()
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//select columns by dtypes
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let str_cols = df_drop.select_dtypes(["string"])
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let num_cols = df_drop.select_dtypes(["int32", "float32"])
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str_cols.print()
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num_cols.print()
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//add new column to Dataframe
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let new_vals = df['Fare'].round().values
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df_drop.addColumn({ column: "fare_round", value: new_vals})
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df_drop.print()
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df_drop['fare_round'].print(5)
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//prints the number of occurence each value in the column
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df_drop['Survived'].value_counts().print()
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//print the last ten elementa of a DataFrame
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df_drop.tail(10).print()
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//prints the number of missing values in a DataFrame
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df_drop.isna().sum().print()
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}).catch(err => {
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console.log(err);
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})
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npm install danfojs
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```
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Output in Node Console:
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![](assets/node-rec.gif)
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> If you want to use Danfo in frontend frameworks like React/Vue, read this [guide](https://danfo.jsdata.org/examples/using-danfojs-in-react)
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### Danfo-js in Node.js
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To use Danfo.js in Node.js, you need to install the nodejs version (danfojs-node) via NPM/Yarn. See more information here.
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#### You can play with Danfo.js on Dnotebooks playground [here](https://playnotebook.jsdata.org/demo)
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#### [See the Official Getting Started Guide](https://danfo.jsdata.org/getting-started)

‎src/danfojs-browser/package.json‎

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"scripts": {
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"test": "karma start --single-run --browsers ChromeHeadless karma.conf.js",
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"test:clean": "yarn build:clean && yarn run test",
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"build": "tsc && yarn run bundle",
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"build:clean": "rimraf ./dist && rimraf ./lib && yarn run build",
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"build": "node ./scripts/prebuild.js && tsc && yarn run bundle",
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"build:clean": "rimraf ./dist && rimraf ./lib && node ./scripts/prebuild.js && yarn run build",
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"dev": "nodemon",
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"lint": "eslint ./src",
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"bundle": "webpack --mode development",

‎src/danfojs-browser/scripts/prebuild.js‎

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/**
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* @license
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* Copyright 2021, JsData. All rights reserved.
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*
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* This source code is licensed under the MIT license found in the
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* LICENSE file in the root directory of this source tree.
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* ==========================================================================
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*/
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/**
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* Danfojs-node version uses Tensorflowjs-node package. Hence on bundling, we set the tensorflow lib
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* to use the Tensorflowjs-node package.
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* */
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/* eslint-disable no-undef */
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const fs = require('fs');
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function updateTensorflowLib(tensorflowLibPath) {
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const importStatement = `
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// This file is auto-generated by prebuild.js. Do not edit!
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const tf = require("@tensorflow/tfjs")\nexport default tf
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`;
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fs.writeFileSync(tensorflowLibPath, importStatement);
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}
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updateTensorflowLib('../danfojs-base/shared/tensorflowlib.ts');

‎src/danfojs-node/README.md‎

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- Robust data preprocessing functions like [OneHotEncoders](https://danfo.jsdata.org/api-reference/general-functions/danfo.onehotencoder), [LabelEncoders](https://danfo.jsdata.org/api-reference/general-functions/danfo.labelencoder), and scalers like [StandardScaler](https://danfo.jsdata.org/api-reference/general-functions/danfo.standardscaler) and [MinMaxScaler](https://danfo.jsdata.org/api-reference/general-functions/danfo.minmaxscaler) are supported on DataFrame and Series
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To use Danfo.js via script tags, copy and paste the CDN below to the body of your HTML file
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```html
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<script src="https://cdn.jsdelivr.net/npm/danfojs@0.2.7/lib/bundle.min.js"></script>
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```
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### Example Usage in the Browser
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> See the example below in [Code Sandbox](https://codepen.io/risingodegua/pen/bGwPGMG)
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```html
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<script src="https://cdn.plot.ly/plotly-1.2.0.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@0.2.7/lib/bundle.min.js"></script>
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<title>Document</title>
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</head>
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<body>
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<div id="div1"></div>
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<div id="div2"></div>
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<div id="div3"></div>
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<script>
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dfd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
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.then(df => {
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df['AAPL.Open'].plot("div1").box() //makes a box plot
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df.plot("div2").table() //display csv as table
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new_df = df.set_index({ key: "Date" }) //resets the index to Date column
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new_df.plot("div3").line({ columns: ["AAPL.Open", "AAPL.High"] }) //makes a timeseries plot
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}).catch(err => {
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console.log(err);
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})
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</script>
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</body>
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</html>
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```
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Output in Browser:
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![](assets/browser-out.gif)
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## How to install
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Danfo.js is hosted on NPM, and can installed via package managers like npm and yarn
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‎src/danfojs-node/package.json‎

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"test:clean": "yarn build:clean && yarn test",
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"dev": "nodemon",
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"build": "tsc",
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"build:clean": "rimraf ./build && tsc",
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"build:clean": "rimraf ./build && node ./scripts/prebuild.js && tsc",
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"lint": "eslint ./src",
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"coveralls": "cat ./coverage/lcov.info | ./node_modules/.bin/coveralls",
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"coverage": "nyc report --reporter=text-lcov | coveralls && nyc report --reporter=lcov",

‎src/danfojs-node/scripts/prebuild.js‎

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/**
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* @license
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* Copyright 2021, JsData. All rights reserved.
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*
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* This source code is licensed under the MIT license found in the
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* LICENSE file in the root directory of this source tree.
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* ==========================================================================
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*/
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/**
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* Danfojs-node version uses Tensorflowjs-node package. Hence on bundling, we set the tensorflow lib
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* to use the Tensorflowjs-node package.
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* */
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/* eslint-disable no-undef */
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const fs = require('fs');
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function updateTensorflowLib(tensorflowLibPath) {
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const importStatement = `const tf = require("@tensorflow/tfjs-node")\nexport default tf`;
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fs.writeFileSync(tensorflowLibPath, importStatement);
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}
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updateTensorflowLib('../danfojs-base/shared/tensorflowlib.ts');

‎src/danfojs-node/test/samples/sampleOut.xlsx‎

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‎src/danfojs-node/test/samples/test.xlsx‎

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‎src/danfojs-node/test/samples/testSeries.xlsx‎

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