tsfresh automatically extracts relevant features from time series data.
Open source
24 alternativesSourcetable
Sourcetable combines spreadsheets and data analysis tools for creating financial models and working with datasets.
About Sourcetable
Sourcetable is a web-based spreadsheet that combines AI chat with formulas, SQL and Python. Users upload files or connect databases and applications, then ask questions in plain English to analyze data, build financial models, and create charts, dashboards and reports. It supports spreadsheet files (.xls, .xlsx, .csv), .tsv, PDF, JSON, MySQL, PostgreSQL, MongoDB, application data and plain text data. Use involves uploading files or connecting external data sources.
Key features
- Ask questions in plain English to analyze spreadsheet data
- Generate charts and graphs from data
- Query databases and applications using AI connectors
- Use Python, SQL and formulas for custom analysis
- Clean and structure raw data into usable datasets
- Work with multi-tab spreadsheets including cross-tab lookups
Best for: People who use spreadsheets and datasets for finance, analysis, operations, research, marketing, or education work.
Good for
- Supports multiple file and database formats including .xls, .csv, PDF, JSON and MongoDB
- Works with multi-tab spreadsheets and can reference tabs by name
- Includes Python libraries such as Pandas, NumPy, Scikit-learn and Matplotlib
Sourcetable at a glance
- Website
- sourcetable.com
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Sourcetable FAQ
How do I analyze data?
Upload a file and start asking questions. The AI can answer questions and do work, or you can take manual control using formulas and features similar to Excel, Google Sheets or Python.
What data sources are supported?
Spreadsheets (.xls, .xlsx, .csv), tabular data (.tsv), PDF, JSON, and database data (MySQL, PostgreSQL, MongoDB), plus application data and most plain text data.
What data science tools are available?
Python, SQL, NumPy, Pandas, SciPy, Scikit-learn, StatsModels, Matplotlib, Plotly, and Seaborn, with AI analysis and cleaning without writing code.
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