statsmodels alternatives and similar packages

Based on the "Science and Data Analysis" category.
Alternatively, view statsmodels alternatives based on common mentions on social networks and blogs.

• Pandas

  9.9 9.9 L2 statsmodels VS Pandas

  Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
  

• NumPy

  9.8 10.0 L1 statsmodels VS NumPy

  The fundamental package for scientific computing with Python.
  

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• SciPy

  9.4 10.0 L2 statsmodels VS SciPy

  SciPy library main repository
  

• SymPy

  9.4 10.0 L2 statsmodels VS SymPy

  A computer algebra system written in pure Python
  

• NetworkX

  9.4 9.5 L3 statsmodels VS NetworkX

  Network Analysis in Python
  

• Dask

  9.2 9.6 L2 statsmodels VS Dask

  Parallel computing with task scheduling
  

• Numba

  8.9 9.8 L3 statsmodels VS Numba

  NumPy aware dynamic Python compiler using LLVM
  

• PyMC

  8.9 9.6 L4 statsmodels VS PyMC

  Bayesian Modeling and Probabilistic Programming in Python
  

• Getting Started

  8.8 9.3 statsmodels VS Getting Started

  PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
  

• astropy

  8.3 9.9 L2 statsmodels VS astropy

  Astronomy and astrophysics core library
  

• Biopython

  8.3 9.6 L2 statsmodels VS Biopython

  Official git repository for Biopython (originally converted from CVS)
  

• orange

  8.1 9.4 L2 statsmodels VS orange

  🍊 :bar_chart: :bulb: Orange: Interactive data analysis
  

• Interactive Parallel Computing with IPython

  7.4 7.3 L3 statsmodels VS Interactive Parallel Computing with IPython

  IPython Parallel: Interactive Parallel Computing in Python
  

• blaze

  7.2 0.0 L4 statsmodels VS blaze

  NumPy and Pandas interface to Big Data
  

• Statsforecast

  7.2 8.7 statsmodels VS Statsforecast

  Lightning ⚡️ fast forecasting with statistical and econometric models.
  

• RDKit

  7.2 9.6 L1 statsmodels VS RDKit

  The official sources for the RDKit library
  

• Cubes

  5.9 0.0 L3 statsmodels VS Cubes

  [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
  

• Open Mining

  5.7 0.0 L3 statsmodels VS Open Mining

  DISCONTINUED. Business Intelligence (BI) in Python, OLAP
  

• #<Sawyer::Resource:0x00007f547e829e00>

  5.7 5.5 statsmodels VS #<Sawyer::Resource:0x00007f547e829e00>

  A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
  

• bcbio-nextgen

  5.4 6.0 L3 statsmodels VS bcbio-nextgen

  Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis
  

• NIPY

  5.4 8.7 L3 statsmodels VS NIPY

  Workflows and interfaces for neuroimaging packages
  

• bcolz

  4.7 0.0 statsmodels VS bcolz

  DISCONTINUED. A columnar data container that can be compressed.
  

• bccb

  4.5 4.4 L4 statsmodels VS bccb

  Incubator for useful bioinformatics code, primarily in Python and R

• Neupy

  4.3 0.0 L5 statsmodels VS Neupy

  NeuPy is a Tensorflow based python library for prototyping and building neural networks

• Bubbles

  3.6 0.0 L5 statsmodels VS Bubbles

  [NOT MAINTAINED] Bubbles – Python ETL framework

• PyDy

  3.5 6.8 L3 statsmodels VS PyDy

  Multibody dynamics tool kit.
  

• signac

  2.4 7.6 statsmodels VS signac

  Manage large and heterogeneous data spaces on the file system.
  

• harold

  2.4 1.8 L2 statsmodels VS harold

  An open-source systems and controls toolbox for Python3

• PatZilla

  2.1 5.4 statsmodels VS PatZilla

  PatZilla is a modular patent information research platform and data integration toolkit with a modern user interface and access to multiple data sources.
  

• LynxKite

  2.1 8.4 statsmodels VS LynxKite

  The complete graph data science platform
  

• Kotori

  2.0 4.9 statsmodels VS Kotori

  A flexible data historian based on InfluxDB, Grafana, MQTT, and more. Free, open, simple.
  

• Terkin

  1.8 0.0 statsmodels VS Terkin

  Datalogger for MicroPython and CPython.
  

• cclib

  0.9 statsmodels VS cclib

  A library for parsing and interpreting the results of computational chemistry packages.

• dask-memusage

  0.9 0.0 statsmodels VS dask-memusage

  A low-impact profiler to figure out how much memory each task in Dask is using

• ElasticBatch

  0.8 0.0 statsmodels VS ElasticBatch

  Elasticsearch tool for easily collecting and batch inserting Python data and pandas DataFrames

• Open Babel

  - statsmodels VS Open Babel

  A chemical toolbox designed to speak the many languages of chemical data.

* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.

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Popular Comparisons

• statsmodels
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