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‎README.md

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* Danfo.js is fast and supports[ Tensorflow.js](https://js.tensorflow.org)'s tensors out of the box. This means you can [convert Danfo.js ](api-reference/dataframe/)DataFrames to Tensors, and vice versa.
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* Easy handling of missing data (represented as `NaN, undefined, or null`) in data
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* Size mutability: columns can be inserted/deleted from DataFrame
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* Size mutability: columns can be inserted/deleted from DataFrames
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* Automatic and explicit alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let [`Series`](api-reference/series/), [`DataFrame`](api-reference/dataframe/), etc. automatically align the data for you in computations
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* Powerful, flexible, [groupby](api-reference/groupby/) functionality to perform split-apply-combine operations on data sets, for both aggregating and transforming data
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* Make it easy to convert Arrays, JSONs, List or Objects, Tensors, and differently-indexed data structures into DataFrame objects

‎api-reference/dataframe/danfo.dataframe.mod.md

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╚════════════╧═══════════════════╧═══════════════════╝
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```
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{% endtab %}
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{% endtabs %}
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```
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```
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╟────────────┼───────────────────┼───────────────────╢
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```
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╚════════════╧═══════════════════╧═══════════════════╝
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```
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{% endtab %}
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{% endtabs %}

‎api-reference/dataframe/danfo.dataframe.mul.md

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# DataFrame.mul
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danfo.DataFrame.mul(other, option) 
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danfo.DataFrame.mul(other, option)
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| Parameters | Type | Description | Default |
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| ---------- | ---------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------- |
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```
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```
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‎api-reference/dataframe/danfo.dataframe.pow.md

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# DataFrame.pow
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danfo.DataFrame.pow(other, option) 
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danfo.DataFrame.pow(other, option)
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| Parameters | Type | Description | Default |
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| ---------- | ---------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------- |
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```
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```
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‎api-reference/groupby/groupby.col.md

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# Groupby.col
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> danfo.Groupby.col\(col\_names\) \[[source](https://github.com/opensource9ja/danfojs/blob/master/danfojs/src/core/groupby.js#L104)\]
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> danfo.Groupby.col(col\_names) \[[source](https://github.com/opensource9ja/danfojs/blob/master/danfojs/src/core/groupby.js#L104)]
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| Parameters | Type | Description | Default |
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| :--- | :--- | :--- | :--- |
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| col\_names | Array | List of column | |
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| Parameters | Type | Description | Default |
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| ---------- | ----- | -------------- | ------- |
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| col\_names | Array | List of column | |
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Returns: Groupby Data structure
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Note: This is similar to pandas `df.groupby(["column"])["colNames"]`
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Note: This is similar to pandas `df.groupby(["column"])["colNames"]`
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**Examples**
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Apparently the output are not that useful unless you perform some operations like max\(\), count\(\) and the likes.
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Apparently the output are not that useful unless you perform some operations like max(), count() and the likes.
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```text
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```
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```
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‎api-reference/plotting/box-plots.md

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export default App;
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```
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![](../../.gitbook/assets/newplot-23-.png)
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![](<../../.gitbook/assets/screen-shot-2020-08-11-at-1.20.42-am (1) (1).png>)
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To customize your plots, see the [Configuring your plot page](configuring-your-plots.md)

‎api-reference/plotting/configuring-your-plots.md

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| **columns** | Array of column names to plot. | All columns in the DataFrame when applicable |
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| **values** | Used to configure a `pie` chart. A column name containing values for the pie. Maps 1-1 with labels. | |
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| **labels** | Used to configure a `pie` chart. A column name containing labels for the pie. Maps 1-1 with values. | |
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| **rowPositions** | Used to configure a `pie` chart. Pie chart domain row. See [https://plotly.com/javascript/reference/pie/#pie-domain-row](https://plotly.com/javascript/reference/pie/#pie-domain-row) | Range of `0 - DataFrame column length` |
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| **rowPositions** | Used to configure a `pie` chart. Pie chart domain row. See [https://plotly.com/javascript/reference/pie/#pie-domain-row](https://plotly.com/javascript/reference/pie/#pie-domain-row) | Range of `0 - DataFrame column length` |
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| **columnPositions** | Used to configure a `pie` chart. Pie chart domain column. See [https://plotly.com/javascript/reference/pie/#pie-domain-column](https://plotly.com/javascript/reference/pie/#pie-domain-column) | Range of `0 - DataFrame column length` |
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| **tableHeaderStyle** | Table properties used for configuring table header. See [full list](https://plotly.com/javascript/reference/table/#table-header) of supported arguments. | |
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##

‎api-reference/plotting/line-charts.md

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‎api-reference/plotting/tables.md

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![](../../.gitbook/assets/screen-shot-2020-08-11-at-12.34.08-am.png)
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![](../../.gitbook/assets/screen-shot-2020-08-11-at-12.38.30-am.png)

‎api-reference/plotting/timeseries-plots.md

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‎building-data-driven-applications-with-danfo.js-book.md

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By the end of this app development book, you'll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.
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![Danfo.js book cover](.gitbook/assets/b17076\_cover.jpg)
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## **What you will learn**
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‎examples/using-danfojs-in-react.md

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On running the app, we get the following output in the console:
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Note that you can also import specific modules. For instance, in the code below we import only the DataFrame module:
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