Technology · Library
pandas
Library · Catalog tech@1
Data analysis library for Python.
- Categories
- Matched as
- 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
Momentum
Collecting0 of 5 signalsNo score yet. Momentum is published only when at least 2 of the 5 signals have history. pandas has 0, so there is no single number: each signal is shown on its own below. It is not a zero, and nothing is estimated in its place.
Snapshot OCT 24, 2026 · Scoring tech@1
- 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
49.9K stars
Members 74repositories tagged with one of its aliases, most-starred first
- deepchecks/deepchecks
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
4.1K stars
- jmcnamara/XlsxWriter
A Python module for creating Excel XLSX files.
4K stars
- nalepae/pandarallel
A simple and efficient tool to parallelize Pandas operations on all available CPUs
3.8K stars
- databricks/koalas
Koalas: pandas API on Apache Spark
3.4K stars
- delta-io/delta-rs
A native Rust library for Delta Lake, with bindings into Python
3.3K stars
- pydata/pandas-datareader
Extract data from a wide range of Internet sources into a pandas DataFrame.
3.3K stars
- adamerose/PandasGUI
A GUI for Pandas DataFrames
3.3K stars
- fbdesignpro/sweetviz
Visualize and compare datasets, target values and associations, with one line of code.
3.1K stars
- man-group/arctic
High performance datastore for time series and tick data
3.1K stars
- weld-project/weld
High-performance runtime for data analytics applications
3K stars
- reloadware/reloadium
Hot Reloading and Profiling for Python
3K stars
- posit-dev/great-tables
Make awesome display tables using Python
2.9K 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
Not published by PyPI
Ecosystem 953packages that depend on it, most-adopted first
- apache-airflow-providers-influxdb
Provider package apache-airflow-providers-influxdb for Apache Airflow
Not published by PyPI - apache-airflow-providers-papermill
Provider package apache-airflow-providers-papermill for Apache Airflow
Not published by PyPI - apache-airflow-providers-presto
Provider package apache-airflow-providers-presto for Apache Airflow
Not published by PyPI - apache-airflow-providers-salesforce
Provider package apache-airflow-providers-salesforce for Apache Airflow
Not published by PyPI - apache-airflow-providers-snowflake
Provider package apache-airflow-providers-snowflake for Apache Airflow
Not published by PyPI - apache-airflow-providers-trino
Provider package apache-airflow-providers-trino for Apache Airflow
Not published by PyPI - apache-flink
Apache Flink Python API
Not published by PyPI - apache-hamilton
Apache Hamilton (incubating) is a lightweight Python library for directed acyclic graphs (DAGs) of transformations. Your DAG is **portable**; it runs anywhere Python runs, whether it's a script, notebook, Airflow pipeline, FastAPI server, etc. Your DAG is **expressive**; Apache Hamilton has extensive features to define and modify the execution of a DAG (e.g., data validation, experiment tracking, remote execution).
Not published by PyPI - apache-iotdb
Apache IoTDB client API
Not published by PyPI - apache-superset
A modern, enterprise-ready business intelligence web application
Not published by PyPI - aplr
Automatic Piecewise Linear Regression
Not published by PyPI - applypilot
AI-powered end-to-end job application pipeline
Not published by PyPI
Latest news the 0 latest events that mention it
No published news event mentions pandas yet.