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Merge branch 'dev' into build-esm-bundle
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‎README.md‎

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For use directly in HTML files, you can add the latest script tag from [JsDelivr](https://www.jsdelivr.com/package/npm/danfojs) to your HTML file:
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```html
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.0/lib/bundle.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.1/lib/bundle.js"></script>
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```
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See all available versions [here](https://www.jsdelivr.com/package/npm/danfojs)
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### Quick Examples
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* [Danfojs with HTML and vanilla JavaScript on CodePen](https://codepen.io/risingodegua/pen/bGpwyYW)
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* [Danfojs with React on Code Sandbox](https://codesandbox.io/s/using-danfojs-in-react-dwpv54?file=/src/App.js)
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* [Danfojs on ObservableHq](https://observablehq.com/@risingodegua/using-danfojs-on-observablehq)
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* [Danfojs in Nodejs on Replit](https://replit.com/@RisingOdegua/Danfojs-in-Nodejs)
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### Example Usage in the Browser
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```html
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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.jsdelivr.net/npm/danfojs@1.1.0/lib/bundle.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.1/lib/bundle.js"></script>
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<title>Document</title>
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</head>
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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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const dfd = require("danfojs-node")
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const file_url =
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"https://web.stanford.edu/class/archive/cs/cs109/cs109.1166/stuff/titanic.csv";
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dfd
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.readCSV(file_url)
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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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const file_url = "https://web.stanford.edu/class/archive/cs/cs109/cs109.1166/stuff/titanic.csv"
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dfd.readCSV(file_url)
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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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// 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 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.columns);
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//prints all column names
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console.log(df.columns);
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// //prints the inferred dtypes of each column
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df.ctypes.print();
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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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//selecting a column by subsetting
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df['Name'].print()
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//drop columns by names
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let cols_2_remove = ["Age", "Pclass"];
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let df_drop = df.drop({ columns: cols_2_remove, axis: 1 });
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df_drop.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.selectDtypes(["string"]);
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let num_cols = df_drop.selectDtypes(["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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//select columns by dtypes
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let str_cols = df_drop.selectDtypes(["string"])
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let num_cols = df_drop.selectDtypes(["int32", "float32"])
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str_cols.print()
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num_cols.print()
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let new_vals = df["Fare"].round(1);
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df_drop.addColumn("fare_round", new_vals, { inplace: true });
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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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df_drop["fare_round"].round(2).print(5);
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//add new column to Dataframe
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//prints the number of occurence each value in the column
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df_drop["Survived"].valueCounts().print();
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let new_vals = df['Fare'].round(1)
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df_drop.addColumn("fare_round", new_vals, { inplace: true })
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df_drop.print()
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df_drop['fare_round'].round(2).print(5)
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//prints the number of occurence each value in the column
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df_drop['Survived'].valueCounts().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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//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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})
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.catch((err) => {
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console.log(err);
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});
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```
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Output in Node Console:

‎src/danfojs-base/core/frame.ts‎

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): DataFrame | void {
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let { columns, inplace } = { inplace: false, ...options }
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if (!values && typeof values !== "boolean" && typeof values !== "number") {
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if (!values && typeof values !== "boolean" && typeof values !== "number" && typeof values !== "string") {
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throw Error('ParamError: value must be specified');
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}
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‎src/danfojs-base/index.ts‎

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import dateRange from "./core/daterange"
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import tensorflow from "./shared/tensorflowlib"
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const __version = "1.1.0";
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const __version = "1.1.1";
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export {
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NDframe,

‎src/danfojs-base/io/browser/io.csv.ts‎

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Papa.parse(file, {
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header: true,
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dynamicTyping: true,
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skipEmptyLines: 'greedy',
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...options,
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download: true,
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complete: results => {

‎src/danfojs-base/io/node/io.csv.ts‎

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const optionsWithDefaults = {
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header: true,
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dynamicTyping: true,
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skipEmptyLines: 'greedy',
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...options,
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}
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const dataStream = request.get(filePath);
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const parseStream: any = Papa.parse(Papa.NODE_STREAM_INPUT, optionsWithDefaults);
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const parseStream: any = Papa.parse(Papa.NODE_STREAM_INPUT, optionsWithDefaults as any);
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dataStream.pipe(parseStream);
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const data: any = [];

‎src/danfojs-base/package.json‎

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{
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"name": "danfojs-base",
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"version": "1.1.0",
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"version": "1.1.1",
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"description": "Base package used in danfojs-node and danfojs-browser",
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"main": "index.ts",
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"scripts": {

‎src/danfojs-browser/README.md‎

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For use directly in HTML files, you can add the latest script tag from [JsDelivr](https://www.jsdelivr.com/package/npm/danfojs) to your HTML file:
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```html
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.0/lib/bundle.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.1/lib/bundle.js"></script>
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```
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See all available versions [here](https://www.jsdelivr.com/package/npm/danfojs)
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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.jsdelivr.net/npm/danfojs@1.1.0/lib/bundle.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.1/lib/bundle.js"></script>
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<title>Document</title>
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</head>

‎src/danfojs-browser/package.json‎

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{
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"name": "danfojs",
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"version": "1.1.0",
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"version": "1.1.1",
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"description": "JavaScript library providing high performance, intuitive, and easy to use data structures for manipulating and processing structured data.",
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"main": "dist/danfojs-browser/src/index.js",
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"types": "dist/danfojs-browser/src/index.d.ts",

‎src/danfojs-browser/tsconfig.json‎

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{
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"compilerOptions": {
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"target": "es5", /* Specify ECMAScript target version: 'ES3' (default), 'ES5', 'ES2015', 'ES2016', 'ES2017', 'ES2018', 'ES2019', 'ES2020', or 'ESNEXT'. */
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"module": "es2015", /* Specify module code generation: 'none', 'commonjs', 'amd', 'system', 'umd', 'es2015', 'es2020', or 'ESNext'. */
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"module": "CommonJS", /* Specify module code generation: 'none', 'commonjs', 'amd', 'system', 'umd', 'es2015', 'es2020', or 'ESNext'. */
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"moduleResolution": "node",
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"lib": ["es6", "dom"], /* Specify library files to be included in the compilation. */
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"allowJs": true, /* Allow javascript files to be compiled. */

‎src/danfojs-node/README.md‎

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For use directly in HTML files, you can add the latest script tag from [JsDelivr](https://www.jsdelivr.com/package/npm/danfojs) to your HTML file:
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```html
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.0/lib/bundle.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.1/lib/bundle.js"></script>
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```
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See all available versions [here](https://www.jsdelivr.com/package/npm/danfojs)
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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.jsdelivr.net/npm/danfojs@1.1.0/lib/bundle.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@1.1.1/lib/bundle.js"></script>
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<title>Document</title>
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</head>

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