> For the complete documentation index, see [llms.txt](https://danfo.jsdata.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://danfo.jsdata.org/readme.md).

# Danfo.js Documentation

D**anfo.js** is heavily inspired by the [Pandas](https://pandas.pydata.org/pandas-docs/stable/index.html) library and provides a similar interface and API. This means users familiar with the [Pandas ](https://pandas.pydata.org/pandas-docs/stable/index.html)API can easily use D**anfo.js.**

## Main Features

* 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.md)DataFrames to Tensors, and vice versa.
* Easy handling of missing data (represented as `NaN, undefined, or null`) in data
* Size mutability: columns can be inserted/deleted from DataFrames
* 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.md), [`DataFrame`](/api-reference/dataframe.md), etc. automatically align the data for you in computations
* Powerful, flexible, [groupby](/api-reference/groupby.md) functionality to perform split-apply-combine operations on data sets, for both aggregating and transforming data
* Make it easy to convert Arrays, JSONs, List or Objects, Tensors, and differently-indexed data structures into DataFrame objects
* Intelligent label-based slicing, fancy indexing, and querying of large data sets
* Intuitive [merging](/api-reference/general-functions/danfo.merge.md) and [joining](/api-reference/general-functions/danfo.concat.md) data sets
* Robust IO tools for loading data from [flat-files](/api-reference/input-output/danfo.read_csv.md) (CSV and delimited), Excel, and JSON data format.
* Powerful, flexible, and intiutive API for [plotting](https://app.gitbook.com/@jsdata/s/danfojs/~/drafts/-MESZnq3_VBU0EW71MxS/api-reference/plotting) DataFrames and Series interactively.
* Timeseries-specific functionality: date range generation and date and time properties.
* Robust data preprocessing functions like [OneHotEncoders](/api-reference/general-functions/danfo.onehotencoder.md), [LabelEncoders](/api-reference/general-functions/danfo.labelencoder.md), and scalers like [StandardScaler](/api-reference/general-functions/danfo.standardscaler.md) and [MinMaxScaler](/api-reference/general-functions/danfo.minmaxscaler.md) are supported on DataFrame and Series

## Getting Started

New to Danfo? Check out the getting started guides. It contains a quick introduction to D\_anfo's\_ main concepts and links to additional content.

{% content-ref url="/pages/-MDu9wFmXxB4IoYAO6R\_" %}
[Getting Started](/getting-started.md)
{% endcontent-ref %}

## **API Reference**

The reference guide contains a detailed description of the **danfo** API. The reference describes how each function works and which parameters can be used.

{% content-ref url="/pages/-MB6W-03\_cNQ3LxfB2\_S" %}
[API reference](/api-reference.md)
{% endcontent-ref %}

## User Guides/Tutorials

{% content-ref url="/pages/-MEi4CrRaNqLzqrANwdU" %}
[User Guides](/examples.md)
{% endcontent-ref %}

## Building Data Driven Applications with Danfo.js - Book

{% content-ref url="/pages/-MjTMTRb0z4eG\_2wVz99" %}
[Building Data Driven Applications with Danfo.js - Book](/building-data-driven-applications-with-danfo.js-book.md)
{% endcontent-ref %}

## Contributing Guide

Want to help improve our documentation and existing functionalities? The contributing guidelines will guide you through the process.

{% content-ref url="/pages/-MDuLPJpehtmq5YbLLm7" %}
[Contributing Guide](/contributing-guide.md)
{% endcontent-ref %}

## Release Notes

{% content-ref url="/pages/-MEmTsIPGMd\_H6JAOlt9" %}
[Release Notes](/release-notes.md)
{% endcontent-ref %}