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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 Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Anaconda No 
ApertureDB Yes 
Avanzai Yes 
Cleanlab Yes 
Coiled Yes 
Daft Yes 
DagsHub Yes 
Flower Yes 
Flyte Yes 
GLM-5.1 Yes 
GLM-5.2 Yes 
GLM-5.3 Yes 
Giskard Yes 
LanceDB Yes 
MLJAR Studio Yes 
OrcaSheets Yes 
Python No 
Spyder Yes 
ThinkData Works Yes 
Yandex Data Proc Yes 

Integrations

Anaconda Yes 
ApertureDB No 
Avanzai No 
Cleanlab No 
Coiled No 
Daft No 
DagsHub No 
Flower No 
Flyte No 
GLM-5.1 No 
GLM-5.2 No 
GLM-5.3 No 
Giskard No 
LanceDB No 
MLJAR Studio No 
OrcaSheets No 
Python Yes 
Spyder No 
ThinkData Works No 
Yandex Data Proc No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

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 No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Product Features

Alternatives

Alternatives

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