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    0.3.3 • Public • Published

    Danfojs: powerful javascript data analysis toolkit

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    What is it?

    Danfo.js is a javascript package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It is heavily inspired by Pandas library, and provides a similar API. This means that users familiar with Pandas, can easily pick up danfo.js.

    Main Features

    • 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 to Tensors.
    • Easy handling of missing-data (represented as NaN) in floating point as well as non-floating point data
    • Size mutability: columns can be inserted/deleted from DataFrame
    • 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, DataFrame, etc. automatically align the data for you in computations
    • Powerful, flexible groupby 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 and joining data sets
    • Robust IO tools for loading data from flat-files (CSV, Json, Excel, Data package).
    • Powerful, flexible and intutive API for plotting DataFrames and Series interactively.
    • Timeseries-specific functionality: date range generation and date and time properties.
    • Robust data preprocessing functions like OneHotEncoders, LabelEncoders, and scalers like StandardScaler and MinMaxScaler are supported on DataFrame and Series

    To use Danfo.js via script tags, copy and paste the CDN below to the body of your HTML file

        <script src="https://cdn.jsdelivr.net/npm/danfojs@0.3.3/lib/bundle.min.js"></script> 

    Example Usage in the Browser

    See the example below in Code Sandbox

    <!DOCTYPE html>
    <html lang="en">
        <meta charset="UTF-8">
        <meta name="viewport" content="width=device-width, initial-scale=1.0">
        <script src="https://cdn.plot.ly/plotly-1.2.0.min.js"></script> 
        <script src="https://cdn.jsdelivr.net/npm/danfojs@0.3.3/lib/bundle.min.js"></script> 
        <div id="div1"></div>
        <div id="div2"></div>
        <div id="div3"></div>
                .then(df => {
                    df['AAPL.Open'].plot("div1").box() //makes a box plot
                    df.plot("div2").table() //display csv as table
                    new_df = df.set_index({ column: "Date" }) //resets the index to Date column
                    new_df.plot("div3").line({ columns: ["AAPL.Open", "AAPL.High"] })  //makes a timeseries plot
                }).catch(err => {

    Output in Browser:

    How to install

    Danfo.js is hosted on NPM, and can installed via package managers like npm and yarn

    npm install danfojs-node

    Example usage in Nodejs

    const dfd = require("danfojs-node")
    const file_url = "https://web.stanford.edu/class/archive/cs/cs109/cs109.1166/stuff/titanic.csv"
        .then(df => {
            //prints the first five columns
            // Calculate descriptive statistics for all numerical columns
            //prints the shape of the data
            //prints all column names
            // //prints the inferred dtypes of each column
            //selecting a column by subsetting
            //drop columns by names
            cols_2_remove = ['Age', 'Pclass']
            df_drop = df.drop({ columns: cols_2_remove, axis: 1 })
            //select columns by dtypes
            let str_cols = df_drop.select_dtypes(["string"])
            let num_cols = df_drop.select_dtypes(["int32", "float32"])
            //add new column to Dataframe
            let new_vals = df['Fare'].round(1)
            df_drop.addColumn({ column: "fare_round", values: new_vals, inplace: true })
            //prints the number of occurence each value in the column
            //print the last ten elementa of a DataFrame
            //prints the number of missing values in a DataFrame
        }).catch(err => {

    Output in Node Console:

    If you want to use Danfo in frontend frameworks like React/Vue, read this guide

    You can play with Danfo.js on Dnotebooks playground here

    See the Official Getting Started Guide


    The official documentation can be found here

    Discussion and Development

    Development discussions take place on our issues tab.

    Contributing to Danfo

    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.

    Licence MIT

    Created by Rising Odegua and Stephen Oni

    Danfo.js - Open Source JavaScript library for manipulating data. | Product Hunt Embed


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