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  1. Stackups
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  5. Chartify vs Highcharts vs Plotly

Chartify vs Highcharts vs Plotly

OverviewDecisionsComparisonAlternatives

Overview

Highcharts
Highcharts
Stacks1.5K
Followers1.1K
Votes92
Plotly.js
Plotly.js
Stacks399
Followers694
Votes69
GitHub Stars17.9K
Forks1.9K
Chartify
Chartify
Stacks0
Followers4
Votes0

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Manual

Advice on Highcharts, Plotly.js, Chartify

Steve
Steve

Lead Software Tools Engineer at Leonardo UK

Oct 30, 2020

Review

I would specifically recommend basing your application on Pandas which will handle the vast majority of the work for you. You will be amazed at what you will be able to get done with only a few lines of code.

Pandas can load the data from either Excel xslx files or csv files (and a lot of other places)

If you structure your code well you can have a cross platform command line program, a GUI desktop program, a Jupyter Notebook and a web service all with the vast majority of the code in common.

A jupyter notebook is a great place to start developing your code and may be all that you need.

Some plug-ins & resources that can help:

  • pandas-summary (for a rapid overview of the data): https://github.com/mouradmourafiq/pandas-summary
  • pandasgui (for exploring what you would like to do): https://github.com/adamerose/pandasgui
  • Pandas-Bokeh (plotting): https://github.com/PatrikHlobil/Pandas-Bokeh
  • plot.ly (plotting): https://plotly.com/python/pandas-backend/
  • wxPython (for a desktop GUI): https://wxpython.org/
8.83k views8.83k
Comments
Shaik
Shaik

Feb 18, 2020

Needs advice

I have used highcharts and it is pretty awesome for my previous project. now as I am about to start my new project I want to use other charting libraries such as recharts, chart js, Nivo, d3 js.... my upcoming project might use react js as front end and laravel as a backend technology. the project would be of hotel management type. please suggest me the best charts to use

247k views247k
Comments

Detailed Comparison

Highcharts
Highcharts
Plotly.js
Plotly.js
Chartify
Chartify

Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.

It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.

Build charts with CSS in React

It works in all modern mobile and desktop browsers including the iPhone/iPad and Internet Explorer from version 6;Free for non-commercial;One of the key features of Highcharts is that under any of the licenses, free or not, you are allowed to download the source code and make your own edits;Pure Javascript - Highcharts is solely based on native browser technologies and doesn't require client side plugins like Flash or Java.
Feature parity with MATLAB/matplotlib graphing; Online chart editor; Fully interactive (hover, zoom, pan); SVG and WebGL backends; Publication-quality image export
-
Statistics
GitHub Stars
-
GitHub Stars
17.9K
GitHub Stars
-
GitHub Forks
-
GitHub Forks
1.9K
GitHub Forks
-
Stacks
1.5K
Stacks
399
Stacks
0
Followers
1.1K
Followers
694
Followers
4
Votes
92
Votes
69
Votes
0
Pros & Cons
Pros
  • 34
    Low learning curve and powerful
  • 17
    Multiple chart types such as pie, bar, line and others
  • 13
    Responsive charts
  • 9
    Handles everything you throw at it
  • 8
    Extremely easy-to-parse documentation
Cons
  • 9
    Expensive
Pros
  • 16
    Bindings to popular languages like Python, Node, R, etc
  • 10
    Integrated zoom and filter-out tools in charts and maps
  • 9
    Great support for complex and multiple axes
  • 8
    Powerful out-of-the-box featureset
  • 6
    Beautiful visualizations
Cons
  • 18
    Terrible document
No community feedback yet
Integrations
No integrations available
Python
Python
React
React
MATLAB
MATLAB
Jupyter
Jupyter
Julia
Julia
React
React

What are some alternatives to Highcharts, Plotly.js, Chartify?

D3.js

D3.js

It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.

Chart.js

Chart.js

Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.

Recharts

Recharts

Quickly build your charts with decoupled, reusable React components. Built on top of SVG elements with a lightweight dependency on D3 submodules.

ECharts

ECharts

It is an open source visualization library implemented in JavaScript, runs smoothly on PCs and mobile devices, and is compatible with most current browsers.

ZingChart

ZingChart

The most feature-rich, fully customizable JavaScript charting library available used by start-ups and the Fortune 100 alike.

amCharts

amCharts

amCharts is an advanced charting library that will suit any data visualization need. Our charting solution include Column, Bar, Line, Area, Step, Step without risers, Smoothed line, Candlestick, OHLC, Pie/Donut, Radar/ Polar, XY/Scatter/Bubble, Bullet, Funnel/Pyramid charts as well as Gauges.

CanvasJS

CanvasJS

Lightweight, Beautiful & Responsive Charts that make your dashboards fly even with millions of data points! Self-Hosted, Secure & Scalable charts that render across devices.

AnyChart

AnyChart

AnyChart is a flexible JavaScript (HTML5) based solution that allows you to create interactive and great looking charts. It is a cross-browser and cross-platform charting solution intended for everybody who deals with creation of dashboard, reporting, analytics, statistical, financial or any other data visualization solutions.

ApexCharts

ApexCharts

A modern JavaScript charting library to build interactive charts and visualizations with simple API.

Bokeh

Bokeh

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.

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