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risenWrisenW
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add travis config
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‎.travis.yml‎

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language: node_js
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node_js:
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- node
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- 8
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- 10
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- 12
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script:
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- export NODE_ENV=test
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- npm run build
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- npm run test
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- npm run lint
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- nyc --silent npm run test
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- nyc report --reporter=text-lcov | coveralls
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- nyc check-coverage --lines 70
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after_success:
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-
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notifications:
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email: false
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sudo: false

‎README.md‎

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<div align="center">
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<img src="logo.png"><br>
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<img src="assets/logo.png"><br>
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</div>
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-----------------
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sets
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- Robust IO tools for loading data from [flat-files](https://jsdata.gitbook.io/danfojs/api-reference/input-output)
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(CSV and delimited) and JSON data format.
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- Powerful, flexible and intutive API for [plotting](https://app.gitbook.com/@jsdata/s/danfojs/~/drafts/-MESZnq3_VBU0EW71MxS/api-reference/plotting) DataFrames and Series interactively.
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- [Timeseries](https://jsdata.gitbook.io/danfojs/api-reference/series#accessors)-specific functionality: date range
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generation and date and time properties.
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To use danfo.js via script tags, copy and paste the CDN below to your HTML file
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```html
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<script src="https://cdn.jsdelivr.net/npm/danfojs@0.0.13/dist/index.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@0.0.14/dist/index.min.js"></script>
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```
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### Example Usage in the Browser
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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@0.0.13/dist/index.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/danfojs@0.0.14/dist/index.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="some_div"></div>
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<div id="alldiv"></div>
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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/risenW/medium_tutorial_notebooks/master/train.csv")
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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.describe().print()
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//prints in console
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// Shape: (5,5)
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// ╔════════╤═══════════════════╤═══════════════════╤═══════════════════╤═══════════════════╤═══════════════════╗
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// ║ │ Product_Weight │ Product_Shelf... │ Product_Price │ Product_Super... │ Supermarket_O... ║
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// ╟────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
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// ║ count │ 4188 │ 4990 │ 4990 │ 4990 │ 4990 ║
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// ╟────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
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// ║ mean │ 12.908838 │ 0.066916 │ 391.803772 │ 6103.52002 │ 2004.783447 ║
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// ╟────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
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// ║ std │ NaN │ 0.053058 │ 119.378259 │ 4447.333835 │ 8.283151 ║
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// ╟────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
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// ║ min │ 4.555 │ 0 │ 78.730003 │ 83.230003 │ 1992 ║
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// ╟────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
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// ║ median │ NaN │ 0.053564 │ 393.86 │ 5374.675 │ 2006 ║
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// ╚════════╧═══════════════════╧═══════════════════╧═══════════════════╧═══════════════════╧═══════════════════╝
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var layout = {
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title: 'A sample plot',
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xaxis: {
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title: 'X',
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},
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yaxis: {
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title: 'Y',
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}
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};
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//Displays plot in the specified div
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df['Product_Weight'].plot("some_div", { kind: "histogram" })
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df.plot("alldiv", { x: "Product_Price", y: "Product_Shelf_Visibility", kind: "scatter", mode: 'markers' })
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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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## Installation from sources
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To install danfo in [development mode], clone the repo:
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Output:
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![](danfo-sample.gif)
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```sh
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git clone https://github.com/opensource9ja/danfojs
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```
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cd into danfojs folder and run:
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```sh
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npm install
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```
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## Documentation
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The official documentation can be found [here](https://jsdata.gitbook.io/danfojs/)
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## Discussion and Development
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Most development discussions take place on github in this repo. Feel free to use the issues tab.
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Most development discussions take place on our [issues](https://github.com/opensource9ja/danfojs/issues) tab.
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## Contributing to Danfo
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All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. A detailed overview on how to contribute can be found in the [contributing guide](https://jsdata.gitbook.io/danfojs/contributing-guide). As contributors and maintainers to this project, you are expected to abide by danfo' code of conduct. More information can be found at: [Contributor Code of Conduct](https://github.com/pandas-dev/pandas/blob/master/.github/CODE_OF_CONDUCT.md) Javascript version of Pandas
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All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. A detailed overview on how to contribute can be found in the [contributing guide](https://jsdata.gitbook.io/danfojs/contributing-guide).
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#### Licence [MIT](https://github.com/opensource9ja/danfojs/blob/master/LICENCE)
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#### Created by [Rising Odegua](https://github.com/risenW) and [Stephen Oni](https://github.com/steveoni)
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#### Logo Design By [Seyi Oniyitan](https://twitter.com/seyioniyitan)

‎assets/logo-gif.gif‎

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‎assets/logo.png‎

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‎danfojs/src/core/frame.js‎

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*/
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describe() {
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let numeric_df = this.select_dtypes(['float32', 'int32'])
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let col_names = numeric_df.columns
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let col_names = numeric_df.column_names
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let index = ['count', 'mean', 'std', 'min', 'median', 'max', 'variance']
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let stats_arr = []
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col_names.forEach(name => {
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let col_series = numeric_df.column(name)
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let col_series = numeric_df[name]
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let count = col_series.count()
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let mean = col_series.mean()
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let std = col_series.std()

‎logo.png‎

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