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Description

Pandas is an open-source data analysis and manipulation tool that is not only fast and powerful but also highly flexible and user-friendly, all within the Python programming ecosystem. It provides various tools for importing and exporting data across different formats, including CSV, text files, Microsoft Excel, SQL databases, and the efficient HDF5 format. With its intelligent data alignment capabilities and integrated management of missing values, users benefit from automatic label-based alignment during computations, which simplifies the process of organizing disordered data. The library features a robust group-by engine that allows for sophisticated aggregating and transforming operations, enabling users to easily perform split-apply-combine actions on their datasets. Additionally, pandas offers extensive time series functionality, including the ability to generate date ranges, convert frequencies, and apply moving window statistics, as well as manage date shifting and lagging. Users can even create custom time offsets tailored to specific domains and join time series data without the risk of losing any information. This comprehensive set of features makes pandas an essential tool for anyone working with data in Python.

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

Screenshots View All

Screenshots View All

Integrations

3LC
Activeeon ProActive
Amazon SageMaker Data Wrangler
Anaconda
ApertureDB
Avanzai
Coiled
Dagster
Flower
Flyte
Giskard
Kedro
LanceDB
MLJAR Studio
RunCode
Spyder
TeamStation
ThinkData Works
Union Pandera
skills.ai

Integrations

3LC
Activeeon ProActive
Amazon SageMaker Data Wrangler
Anaconda
ApertureDB
Avanzai
Coiled
Dagster
Flower
Flyte
Giskard
Kedro
LanceDB
MLJAR Studio
RunCode
Spyder
TeamStation
ThinkData Works
Union Pandera
skills.ai

Pricing Details

No price information available.
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

pandas

Founded

2008

Website

pandas.pydata.org

Vendor Details

Company Name

statsmodels

Website

www.statsmodels.org/stable/index.html

Product Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Product Features

Alternatives

Alternatives

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