RStudio is pretty good open-source software for data science but sometimes it’s not working properly. most comment problem of RStudio is ” Cannot install or load packages on R“.
After doing 12 days of comprehensive research we come up with this 15 alternatives for RStudio data science software.
6 data science software similar to RStudio
1. Jupyter Notebook
A Jupyter Notebook is a project and community and a web application that can host code, data, notes, equations, etc. – specifically, an interactive online document. If you’re working on a project with other data scientists, Jupyter Notebooks is the perfect teamwork tool!
Jupyter Notebook – Pros
- They’re great for showcasing your work. You can see both the code and the results. The notebooks at Kaggle are a particularly great example of this.
- It’s easy to use other people’s work as a starting point. You can run cell by cell to better understand what the code does.
- Very easy to host server side, which is helpful for security purposes. A lot of data is sensitive and should be protected, and one of the steps toward that is that no information is stored on local machines. A server-side Jupyter Notebook setup gives you that for free.
Jupyter Notebook – Cons
- It’s hard to collaborate on code with Jupyter — as we’re copying snippets from each other, it’s straightforward to get out of sync
- Hard to maintain one version of the truth. Which notebooks have the one proper solution to the number of Xyz?
2. KNIME
KNIME, also known as Konstanz Information Miner, provides complete end-to-end data analysis, integration and reporting. Its GUI allows users to perform pre-processing, analysis, model building and visualization with minimal programming.
3. TensorFlow.js
TensorFlow.js is the JavaScript library edition of the popular machine learning framework, TensorFlow. You can develop ML models in JavaScript or Node.js and use TensorFlow.js to deploy them over the web on the client browser.
4. MLFlow
MLFlow is a machine learning lifecycle management platform – from building and packaging to deployment of models. It has the following primary components: Tracking: Allows you to track experiments to record and compare parameters and results.
If you’re experimenting with multiple tools or building multiple models, MLFlow helps manage it all from one place. You can integrate a library, language or algorithm with the product.
5. D3.js
D3.js is a javascript library for producing dynamic, interactive data visualizations in web browsers. With D3.js or Data-Driven Documents (D3), you can visualize data on web browsers using HTML, SVG and CSS. It is famous among data scientists for its abilities in animation and interactive visuals.
6. Zeppelin Notebooks
Zeppelin Notebooks is a web-based environment where you can do data analysis using multiple languages like Python, SQL, Scala etc. You can explore, share, analyze and visualize data with Zeppelin Notebooks.
Final Words
These 6 data science software as better to compare RStudio, you can use it for learning and driving better results to your organization.
Thanks for visiting Mapping Returns!
