Sourcetable
sourcetable.comSourcetable combines spreadsheets and data analysis tools for creating financial models and working with datasets.
Looking for something like Data Science Journal? Here are 23 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 17 are open source.
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| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Sourcetable | — | Not stated | Web |
| 2 | Data Science Degree @ Berkeley | — | Not stated | Web |
| 3 | DrivenData | — | Not stated | Web |
| 4 | KNIME | — | Not stated | Web |
| 5 | 19 Questions | — | Yes | — |
| 6 | Intel® oneAPI Data Analytics Library | — | Yes | — |
| 7 | Feature Engine | — | Yes | — |
| 8 | Pycaret | — | Not stated | — |
| 9 | mljar-supervised | — | Yes | — |
| 10 | Featuretools | — | Yes | — |
Sourcetable combines spreadsheets and data analysis tools for creating financial models and working with datasets.
Earn your Master of Information and Data Science online from UC Berkeley in 2026. Master complex data and become a tech industry leader.
DrivenData hosts data science competitions where participants build predictive models for organizations addressing social challenges.
KNIME provides data analysis tools and a visual workflow builder for data science solutions.
19 Questions assigns attributes to objects using machine learning and Bayesian inference, according to its project description.
oneDAL is a C++ and DPC++ library for accelerated machine learning routines on tabular data, governed by the UXL Foundation.
Feature Engine provides Python tools for feature engineering and selection that are compatible with scikit-learn.
PyCaret provides a low code AutoML platform for Python, with a scikit-learn native engine and React control plane.
mljar-supervised provides tabular data AutoML with feature engineering, hyperparameter tuning, explanations, and documentation.
The Featuretools Python library supports automated feature engineering and is published as open source.
tsfresh automatically extracts relevant features from time series data.
Snorkel helps generate training data programmatically through weak supervision.
This project profiles data quality and supports exploratory analysis of Pandas and Spark DataFrames.
DVC tracks data versions and machine learning experiments for collaborative development.
Python library for decision tree visualization and model interpretation.
Optimus supports agile data preparation workflows across Pandas, Dask, cuDF, Vaex, and PySpark.
An AI-first alternative to Jupyter, Deepnote supports Python, R, and SQL, with local IDE use, cloud collaboration, and data apps.
BambooAI analyzes data with a language model in a persistent Python kernel and supports web and Docker workflows.
A Julia package for probability distributions and associated functions.
Modin scales Pandas data workflows by changing a single line of code in a project.
Lance provides an open lakehouse format for multimodal AI, with vector indexing and data versioning.
Cleanlab provides a Python library for data quality and machine learning with messy real world data and labels.
Desbordante profiles data to find patterns and supports data-cleaning scenarios through console and web application interfaces.
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