pandas

Momentum

Each signal is ranked as a percentile among the technologies that have it. A signal without enough history is not counted, and never shown as zero. How momentum works

Official repository stars

Collecting

Star growth needs repository snapshots 30 days apart.49,896 stars now

Member repository stars

Collecting

Star growth needs repository snapshots 30 days apart.0 new members in 30 days

Package adoption

—Not published by its registries

Its packages’ registries publish no adoption figure, so there is nothing to grow.

Open models

—No official models

No official model on Hugging Face, so this signal does not apply.

News

Collecting

News counts once there are 3 events across the last 60 days; it has 0.0 in the last 30 days · 0 in the 30 before

Adoption by registry

The growth of pandas’s own packages, one row per registry in that registry’s own unit. Registries count different things over different windows, so they are never added together.

No registry has two observations of pandas’s own packages about 30 days apart yet, so there is no growth to show. Nothing is estimated in its place.

News activity

Events · 7 days

0published events that mention it

Events · 30 days

0published events that mention it

Previous 30 days

0events in the 30 days before

Momentum history

Momentum history starts OCT 8, 2026. A chart appears once two daily snapshots carry a score; none does so far.

Repositories

Official 1

• pandas-dev/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

  Official repositoryPython

  49.9K stars

Members 74repositories tagged with one of its aliases, most-starred first

• capitalone/DataProfiler

  What's in your data? Extract schema, statistics and entities from datasets

  Tagged pandasPython

  1.6K stars

• pyjanitor-devs/pyjanitor

  Clean APIs for data cleaning. Python implementation of R package Janitor

  Tagged pandasPython

  1.5K stars

• MaxHalford/prince

  :crown: Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA

  Tagged pandasPython

  1.5K stars

• SciSharp/NumSharp

  High Performance Computation for N-D Tensors in .NET, similar API to NumPy.

  Tagged pandasC#

  1.5K stars

• JoinQuant/jqdatasdk

  简单易用的量化金融数据包(easy utility for getting financial market data of China)

  Tagged pandasPython

  1.4K stars

• data-forge/data-forge-ts

  The JavaScript data transformation and analysis toolkit inspired by Pandas and LINQ.

  Tagged pandasTypeScript

  1.4K stars

• jupyter-incubator/sparkmagic

  Jupyter magics and kernels for working with remote Spark clusters

  Tagged pandas-dataframePython

  1.4K stars

• rocketlaunchr/dataframe-go

  DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

  Tagged pandasGo

  1.3K stars

• rsvp/fecon235

  Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics

  Tagged pandasJupyter Notebook

  1.3K stars

• wq/django-rest-pandas

  📊📈 Serves up Pandas dataframes via the Django REST Framework for use in client-side (i.e. d3.js) visualizations and offline analysis (e.g. Excel)

  Tagged pandasPython

  1.3K stars

• xorbitsai/xorbits

  Scalable Python DS & ML, in an API compatible & lightning fast way.

  Tagged pandasPython

  1.2K stars

• machow/siuba

  Python library for using dplyr like syntax with pandas and SQL

  Tagged pandasPython

  1.2K stars

Packages

“Is” packages are pandas itself; ecosystem packages depend on them. The two are counted separately and never added together. Adoption is each registry’s own figure, with its percentile within that registry.

Is 1the technology itself, most-adopted first

• pandas

  Powerful data structures for data analysis, time series, and statistics

  Listed in the catalogPyPI

  —Not published by PyPI

Ecosystem 953packages that depend on it, most-adopted first

• streamlit-aggrid

  Streamlit component implementation of ag-grid

  Depends on pandasPyPI

  —Not published by PyPI
• streamlit-data-editor-plus

  A faster way to build and share data apps

  Depends on pandasPyPI

  —Not published by PyPI
• streamlit-dialog

  A faster way to build and share data apps

  Depends on pandasPyPI

  —Not published by PyPI
• streamlit-nightly

  A faster way to build and share data apps

  Depends on pandasPyPI

  —Not published by PyPI
• streamlit-umami-patched

  A faster way to build and share data apps

  Depends on pandasPyPI

  —Not published by PyPI
• strictdoc

  StrictDoc is open-source software for technical documentation and requirements management.

  Depends on pandasPyPI

  —Not published by PyPI
• styleframe

  A library that wraps pandas and openpyxl and allows easy styling of dataframes in excel. Documentation can be found at http://styleframe.readthedocs.org

  Depends on pandasPyPI

  —Not published by PyPI
• sumo-rl

  RL environments and learning code for traffic signal control in SUMO.

  Depends on pandasPyPI

  —Not published by PyPI
• superduper-framework

  Build compositional and declarative AI applications and agents

  Depends on pandasPyPI

  —Not published by PyPI
• superduper-ibis

  Superduper ibis is a plugin for ibis-framework that allows you to use Superduper as a backend for your ibis queries.

  Depends on pandasPyPI

  —Not published by PyPI
• superduper-sql

  `superduper_sql` is a plugin for SQL databases that allows you to use these databases as databackends for Superduper.

  Depends on pandasPyPI

  —Not published by PyPI
• svql

  Query SystemVerilog modules with SQL.

  Depends on pandasPyPI

  —Not published by PyPI

Latest news the 0 latest events that mention it

No published news event mentions pandas yet.