Fast. Accurate. Easy to use. Stata is a complete, integrated software package that provides all your data science needs—data manipulation, visualization, statistics, and automated reporting.
Master your data
Stata’s data management features give you complete control.
- Frames—manage multiple datasets simultaneously
- Import, export
- JDBC, ODBC, SQL
- Sort, match, merge, join, append, create
- Built-in spreadsheet
- Unicode
- Process text or binary data
- Access data locally or on the web
- Collect statistics across groups
- BLOBs—strings that can hold entire documents
- Billions of observations
- Hundreds of thousands of variables
- Survival data, panel data, multilevel data, survey data, discrete choice data, multiple-imputation data, categorical data, time-series data
And much more, to support all your data science needs.
Stata makes it easy to generate publication-quality, distinctly styled graphs.
You can point and click to create a custom graph. Or you can write scripts to produce hundreds or thousands of graphs in a reproducible manner. Export graphs to EPS or TIFF for publication, to PNG or SVG for the web, or to PDF for viewing. With the integrated Graph Editor, you click to change anything about your graph or to add titles, notes, lines, arrows, and text.
Automated reporting
All the tools you need to automate reporting your results.
- Dynamic Markdown documents
- Create Word documents
- Create PDF documents
- Create Excel files
- Customizable tables
- Schemes for graphics
- Word, HTML, PDF, Excel, SVG, PNG
PyStata — Python and Stata
Highlights
- Use Stata from within Python
- Stata API functions to run Stata commands and access Stata data and returned results from Python
- IPython magic command to use Stata from Jupyter Notebook
Use any Python package within Stata
- Matplotlib and seaborn for visualization
- Beautiful Soup and Scrapy for web scraping
- NumPy and pandas for numerical analysis
- TensorFlow and scikit-learn for machine learning
- And much more
PyStata allows you to invoke Stata directly from any standalone Python environment and to call Python directly from Stata, thus, greatly expanding Stata’s Python integration features.
New features in PyStata include
- the ability to use Stata from any standalone Python environment like Jupyter Notebook, Spyder IDE, PyCharm IDE or Wing IDE
- the ability to use Stata from Python Shell, like the Windows Command Prompt, the macOS terminal, or the Unix terminal
- three IPython magic commands: stata, mata, and pystata; and
- a suite of API functions from within Python to run Stata commands and access Stata data and returned results.
These tools, together with the Stata Function Interface (sfi) module, allow users to easily integrate Stata’s vast statistical and data management methods into any data science project using Python.
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