They automate many redundant steps in data science projects and help you perform data science tasks without any code.
- 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.
- https://www.gigasheet.com/
- Create a spreadsheet interface in Jupyter notebook.
- Yse Mito AI to conduct data analysis.
- Automatically generates Python code for each analysis
- https://docs.trymito.io/getting-started/installing-mito
- Create Pivot tables, aggregations, and charts using drag-and-drop.
- Add heatmaps to tables.
- Works within Jupyter notebook.
- https://github.com/nicolaskruchten/jupyter_pivottablejs
- 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.
- https://github.com/koaning/drawdata
- Open a tableau-style interface in Jupyter notebook
- Analyze a DataFrame as you would in Tableau.
- https://github.com/Kanaries/pygwalker
- A GUI-based Python code generator.
- Import libraries, perform data I/O, create plots, write code for ML models, etc. by clicking buttons.
- https://github.com/visualpython/visualpython
- Provides an elegant UI to build, train and visualize neural networks.
- Browser-based tool.
- Change data, model architecture, hyperparameters, etc. by clicking buttons.
- https://playground.tensorflow.org/
- Generate a standardized EDA report for your dataset.
- Works in a Jupyter notebook
- Covers info about missing values, data statistics, correlation, data interactions, etc.
- https://pypi.org/project/pandas-profiling/