Let's find the most essential and reliable no-code data science tools to speed up the elaboration of the research results. Thanks to Avi Chawla (source: LinkedIn post), I have some suggestions for you here. Let us know your tips.
Gigasheet
- Browser-based no-code tool to analyze data at scale
- Use AI to conduct data analysis
- It's like a combination of Excel + Pandas with no scale limitations
- Analyze up to 1B rows
Mito
- Create a spreadsheet interface in Jupyter Notebook
- Yse Mito AI to conduct data analysis
- Automatically generates Python code for each analysis
PivotTableJS
- Create Pivot tables, aggregations, and charts using drag-and-drop
- Add heatmaps to tables
- Works within Jupyter notebook
Drawdata
- Draw any 2D scatter dataset by dragging the mouse
- Export the data as DataFrame, CSV, or JSON
- Create a histogram and line plot by dragging the mouse
PyGWalker
- Open a tableau-style interface in Jupyter notebook
- Analyze a DataFrame as you would in Tableau
Visual Python
- A GUI-based Python code generator
- Import libraries, perform data I/O, create plots, and write code for ML models by clicking buttons
Tensorflow Playground
- Provides an elegant UI to build, train, and visualize neural networks
- Browser-based tool
- Change data, model architecture, hyperparameters, etc. by clicking buttons
ydata-profiling
- Generate a standardized EDA report for your dataset
- Works in a Jupyter notebook
- Covers info about missing values, data statistics, correlation, and data interactions
Enlarging your list here with the concurrent block of "data analytics":
https://www.shno.co/no-code-tools-category/no-code-analytics
I've used Orange in the classroom and for one-off personal projects. "Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox."
I can certainly tell you about some popular no-code data science tools that people often use:
1. **Tableau**: It's known for its data visualization capabilities, making it easy to create interactive charts and dashboards.
2. **Google Data Studio**: Great for creating custom, shareable reports and dashboards using data from various sources.
3. **IBM Watson Studio**: Offers a wide range of data science and machine learning tools with a user-friendly interface.
4. **RapidMiner**: Known for its powerful data preparation and machine learning features without the need for coding.
5. **KNIME**: A visual platform for data analytics, reporting, and integration.
6. **DataRobot**: Focuses on automated machine learning, making it easier to build predictive models.
7. **Alteryx**: Combines data preparation, data blending, and analytics into a single platform.
The choice of tool depends on your specific needs and preferences. These tools can be valuable for those who want to perform data science tasks without extensive coding knowledge.
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