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Description
Introducing an innovative reactive notebook designed for Python, which allows you to conduct repeatable experiments, run scripts seamlessly, launch applications, and manage versions using git.
🚀 Comprehensive: it serves as a substitute for jupyter, streamlit, jupytext, ipywidgets, papermill, and additional tools.
⚡️ Dynamic: when you execute a cell, marimo automatically runs all related cells or flags them as outdated.
🖐️ Engaging: easily connect sliders, tables, and plots to your Python code without the need for callbacks.
🔬 Reliable: ensures no hidden states, guarantees deterministic execution, and includes built-in package management for consistency.
🏃 Functional: capable of being executed as a Python script, allowing for customization via CLI arguments.
🛜 Accessible: can be transformed into an interactive web application or presentation, and functions in the browser using WASM.
🛢️ Tailored for data: efficiently query dataframes and databases using SQL, plus filter and search through dataframes effortlessly.
🐍 git-compatible: stores notebooks as .py files, making version control straightforward.
⌨️ A contemporary editor: features include GitHub Copilot, AI helpers, vim keybindings, a variable explorer, and an array of other enhancements to streamline your workflow.
With these capabilities, this notebook elevates the way you work with Python, promoting a more efficient and collaborative coding environment.
Description
Statsmodels is a Python library designed for the estimation of various statistical models, enabling users to perform statistical tests and explore data effectively. Each estimator comes with a comprehensive array of result statistics, which are validated against established statistical software to ensure accuracy. This package is distributed under the open-source Modified BSD (3-clause) license, promoting free use and modification. Users can specify models using R-style formulas or utilize pandas DataFrames for convenience. To discover available results, you can check dir(results), and you will find that attributes are detailed in results.__doc__, while methods include their own docstrings for further guidance. Additionally, numpy arrays can be employed as an alternative to formulas. For most users, the simplest way to install statsmodels is through the Anaconda distribution, which caters to data analysis and scientific computing across various platforms. Overall, statsmodels serves as a powerful tool for statisticians and data analysts alike.
API Access
Has API
API Access
Has API
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Pricing Details
$0
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
marimo
Founded
2022
Country
United States
Website
marimo.io
Vendor Details
Company Name
statsmodels
Website
www.statsmodels.org/stable/index.html
Product Features
Application Development
Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development