Polars · DataFrames

Best practices for polars data processing with dataframely. An agent skill from Quantco/dataframely.

Quantco/dataframely

Agentforce session tracing extraction and analysis. An agent skill from Jaganpro/sf-skills.

Jaganpro/sf-skills

Queries the data warehouse with SQL and answers business questions about data.

astronomer/agents

Analyzes CSV, Parquet and JSON data with DuckDB, Polars, numpy and matplotlib, preferring a persistent kernel over repeated one-shot processes.

code-yeongyu/oh-my-openagent

Fast DataFrame library (Apache Arrow). An agent skill from davila7/claude-code-templates.

davila7/claude-code-templates

Guide for using OptimusKG, the biomedical knowledge graph, through the optimuskg Python client.

mims-harvard/OptimusKG

Runbook for closing gaps between a Flowfile visual flow's results and its exported Polars or FlowFrame Python code, measured by tests rather than by eye.

Edwardvaneechoud/Flowfile

Use Hypothesis for property-based testing to automatically generate comprehensive test cases, find edge cases, and write more robust tests with minimal example shrinking.

anam-org/metaxy

Effectively use Narwhals to write dataframe-agnostic code that works seamlessly across multiple Python dataframe libraries.

anam-org/metaxy

Fast genomic interval operations (overlap, nearest, merge, coverage, cluster, complement, subtract, count-overlaps), multi-format bioinformatics I/O, DataFusion SQL, and pileup on Polars DataFrames…

ClawBio/ClawBio

Performs genomic interval overlap, nearest, merge, coverage, complement and subtraction on Polars DataFrames, and reads or writes BED, VCF, BCF, BAM, CRAM, GFF, GTF, FASTA and FASTQ data.

K-Dense-AI/scientific-agent-skills

High-performance DataFrame library for Python ETL, analytics, and pandas migration.

K-Dense-AI/scientific-agent-skills

Data ingestion patterns for loading data from cloud storage, APIs, files, and streaming sources into databases.

ancoleman/ai-design-components

Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow).

ancoleman/ai-design-components

Deep dive into flowfileframe — the Polars-LazyFrame-shaped Python API that builds an in-process flowfilecore FlowGraph as a side effect of every method call — covering the FlowFrame/Expr internals…

Edwardvaneechoud/Flowfile

Pick how to write a figure before custom plot code. An agent skill from probabl-ai/skills.

probabl-ai/skills

Python data pipelines with modular architecture. An agent skill from jamditis/claude-skills-journalism.

jamditis/claude-skills-journalism

Downloads education datasets from configured mirror sources (parquet/CSV) with local Polars filtering.

brycewang-stanford/Auto-Empirical-Research-Skills

Polars DataFrame library for high-performance data manipulation.

brycewang-stanford/Auto-Empirical-Research-Skills

Complex survey analysis: strata/PSU/weights, variance estimation (Taylor, BRR, jackknife, bootstrap), survey GLM, domain analysis, calibration.

brycewang-stanford/Auto-Empirical-Research-Skills

R-to-Python translation for data analysis. An agent skill from brycewang-stanford/Auto-Empirical-Research-Skills.

brycewang-stanford/Auto-Empirical-Research-Skills

Core Python library for astronomy/astrophysics: units with dimensional analysis, celestial coordinate transforms (ICRS/Galactic/AltAz/FK5), FITS I/O, tables (FITS/HDF5/VOTable/CSV), cosmology…

jaechang-hits/SciAgent-Skills

Fast in-memory DataFrame with lazy evaluation, parallel execution, Arrow backend.

jaechang-hits/SciAgent-Skills

Out-of-core DataFrame for billion-row data via lazy evaluation and memory-mapped files.

jaechang-hits/SciAgent-Skills

Parallel/distributed computing for larger-than-RAM data. An agent skill from jaechang-hits/SciAgent-Skills.

jaechang-hits/SciAgent-Skills