What is Bokeh and what are its top alternatives?
Top Alternatives to Bokeh
Plotly.js
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. ...
Matplotlib
It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits. ...
Dash
Dash is an API Documentation Browser and Code Snippet Manager. Dash stores snippets of code and instantly searches offline documentation sets for 150+ APIs. You can even generate your own docsets or request docsets to be included. ...
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. ...
Tableau
Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click. ...
Shiny
It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge. ...
Chart.js
Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions. ...
Highcharts
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. ...
Bokeh alternatives & related posts
- Bindings to popular languages like Python, Node, R, etc16
- Integrated zoom and filter-out tools in charts and maps10
- Great support for complex and multiple axes9
- Powerful out-of-the-box featureset8
- Beautiful visualizations6
- Active user base4
- Webgl chart types are extremely performant3
- Impressive support for webgl 3D charts3
- Charts are easy to share with a cloud account3
- Interactive charts2
- Publication quality image export2
- Easy to use online editor for creating plotly.js charts2
- Terrible document16
related Plotly.js posts
We use Plotly (just their open source stuff) for Zulip's user-facing and admin-facing statistics graphs because it's a reasonably well-designed JavaScript graphing library.
If you've tried using D3.js, it's a pretty poor developer experience, and that translates to spending a bunch of time getting the graphs one wants even for things that are conceptually pretty basic. Plotly isn't amazing (it's decent), but it's way better than than D3 unless you have very specialized needs.
Here is my stack on #Visualization. @FusionCharts and Highcharts are easy to use but only free for non-commercial. Chart.js and Plotly are two lovely tools for commercial use under the MIT license. And D3.js would be my last choice only if a complex customized plot is needed.
- The standard Swiss Army Knife of plotting7
- Lots of code4
related Matplotlib posts
Hi - I am looking to develop an app accessed by a browser that will display interactive networks (including adding or deleting nodes, edges, labels (or changing labels) based on user input. Look to use Django at the backend. Also need to manage graph versions if one person makes a graph change while another person is looking at it. Mainly tree networks for starters anyway. I probably will use the Networkx package. Not sure what the pros and cons are using Bokeh vs Matplotlib. I would be grateful for any comments or suggestions. Thanks.
- Dozens of API docs and Cheat-Sheets16
- Great for offline use10
- Excellent documentation7
- Works with Alfred7
- Quick API search7
- Fast4
- Good integration with Xcode and AppCode2
- Great for mobile dev work1
related Dash posts
- Beautiful visualizations182
- Svg97
- Data-driven91
- Large set of examples80
- Data-driven documents60
- Visualization components23
- Transitions20
- Dynamic properties18
- Plugins14
- Transformation11
- Makes data interactive6
- Components4
- Enter and Exit4
- Open Source3
- Exhaustive3
- Backed by the new york times3
- Kris2
- Easy and beautiful2
- Angular 41
- Simple elegance1
- Templates, force template1
- Awesome Community Support1
- Beginners cant understand at all6
- Complex syntax5
related D3.js posts
We use Plotly (just their open source stuff) for Zulip's user-facing and admin-facing statistics graphs because it's a reasonably well-designed JavaScript graphing library.
If you've tried using D3.js, it's a pretty poor developer experience, and that translates to spending a bunch of time getting the graphs one wants even for things that are conceptually pretty basic. Plotly isn't amazing (it's decent), but it's way better than than D3 unless you have very specialized needs.
I'm a student, and I have a project to build an application (Visual analytics tool) that takes a Microsoft Excel file, cleans the data, and visualizes it. Also, the app should allow the user to filter and interact with it.
1- should I make it desktop application or web application? : I'm leaning toward (desktop)
2- D3.js OR Python?
3- better excel or CSV?
I'm a beginner Inspiration for interaction and look of the app: eventflow application.
- Capable of visualising billions of rows3
- Responsive1
related Tableau posts
Looking for the best analytics software for a medium-large-sized firm. We currently use a Microsoft SQL Server database that is analyzed in Tableau desktop/published to Tableau online for users to access dashboards. Is it worth the cost savings/time to switch over to using SSRS or Power BI? Does anyone have experience migrating from Tableau to SSRS /or Power BI? Our other option is to consider using Tableau on-premises instead of online. Using custom SQL with over 3 million rows really decreases performances and results in processing times that greatly exceed our typical experience. Thanks.
- R Compatibility6
- Free1
- Highly customizable and extensible1
related Shiny posts
- Offers all types of charts9
- Interactive Charts5
- It's totally free3
- Slow rendering9
- Bitmap quality export2
- Low quality zoom plugin1
- It's totally free0
related Chart.js posts
Here is my stack on #Visualization. @FusionCharts and Highcharts are easy to use but only free for non-commercial. Chart.js and Plotly are two lovely tools for commercial use under the MIT license. And D3.js would be my last choice only if a complex customized plot is needed.
Highcharts
- Low learning curve and powerful32
- Multiple chart types such as pie, bar, line and others15
- Responsive charts11
- Handles everything you throw at it8
- Extremely easy-to-parse documentation7
- Easy to customize color scheme and palettes4
- Built-in export chart as-is to image file4
- Expensive3
related Highcharts posts
Here is my stack on #Visualization. @FusionCharts and Highcharts are easy to use but only free for non-commercial. Chart.js and Plotly are two lovely tools for commercial use under the MIT license. And D3.js would be my last choice only if a complex customized plot is needed.