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\n\n\n## What is it?\n\n**Danfo.js** is a javascript package that provides fast, flexible, and expressive data\nstructures designed to make working with \"relational\" or \"labeled\" data both\neasy and intuitive. It is heavily inspired by [Pandas](https://pandas.pydata.org/pandas-docs/stable/) library, and provides a similar API. This means that users familiar with [Pandas](https://pandas.pydata.org/pandas-docs/stable/), can easily pick up danfo.js. \n\n## Main Features\n\n - Danfo.js is fast. It is built on Tensorflow.js, and supports tensors out of the box. This means you can [convert Danfo data structure](https://danfo.jsdata.org/api-reference/dataframe/dataframe.tensor) to Tensors.\n - Easy handling of [missing-data](https://danfo.jsdata.org/getting-started#missing-data) (represented as\n `NaN`) in floating point as well as non-floating point data\n - Size mutability: columns can be [inserted/deleted](https://danfo.jsdata.org/api-reference/dataframe#combining-comparing-joining-merging) from DataFrame\n - Automatic and explicit [alignment](https://danfo.jsdata.org/api-reference/dataframe#reindexing-selection-label-manipulation): objects can\n be explicitly aligned to a set of labels, or the user can simply\n ignore the labels and let `Series`, `DataFrame`, etc. automatically\n align the data for you in computations\n - Powerful, flexible [groupby](https://danfo.jsdata.org/api-reference/groupby) functionality to perform\n split-apply-combine operations on data sets, for both aggregating\n and transforming data\n - Make it easy to convert Arrays, JSONs, List or Objects, Tensors and \n differently-indexed data structures\n into DataFrame objects\n - Intelligent label-based [slicing](https://danfo.jsdata.org/api-reference/dataframe/danfo.dataframe.loc), [fancy indexing](https://danfo.jsdata.org/api-reference/dataframe/danfo.dataframe.iloc), and [querying](https://danfo.jsdata.org/api-reference/dataframe/danfo.dataframe.query) of\n large data sets\n - Intuitive [merging](https://danfo.jsdata.org/api-reference/general-functions/danfo.merge) and [joining](https://danfo.jsdata.org/api-reference/general-functions/danfo.concat) data\n sets\n - Robust IO tools for loading data from [flat-files](https://danfo.jsdata.org/api-reference/input-output)\n (CSV, Json, Excel, Data package).\n - Powerful, flexible and intutive API for [plotting](https://danfo.jsdata.org/api-reference/plotting) DataFrames and Series interactively.\n - [Timeseries](https://danfo.jsdata.org/api-reference/series#accessors)-specific functionality: date range\n generation and date and time properties. \n - 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\n\n\n## Installation\nThere are three ways to install and use Danfo.js in your application\n* For Nodejs applications, you can install the [__danfojs-node__]() version via package managers like yarn and/or npm:\n\n```bash\nnpm install danfojs-node\n\nor\n\nyarn add danfojs-node\n```\nFor client-side applications built with frameworks like React, Vue, Next.js, etc, you can install the [__danfojs__]() version:\n\n```bash\nnpm install danfojs\n\nor\n\nyarn add danfojs\n```\n\nFor 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:\n\n```html\n \n```\nSee all available versions [here](https://www.jsdelivr.com/package/npm/danfojs)\n\n### Example Usage in the Browser\n\n> Run in [Code Sandbox](https://codepen.io/risingodegua/pen/bGwPGMG)\n\n```html\n\n\n\n \n \n \n \n\n ![\"Danfo.js](\"https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=233871&theme=light\")
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