Results for “pandas-migration”
10 skills
jorcan polars
Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for fast in-memory analysis and pandas migration.
0 · bundle
k-dense-ai polars
Process data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.
30.2k · bundle
lucaspmarie-a11y polars
Process in-memory datasets with Polars' expression API, lazy evaluation, and parallel execution, including pandas migration patterns and I/O for CSV, Parquet, and JSON.
5
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nimoqup046-collab polars
Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for faster pandas-style workflows.
2
jeffallan pandas-pro
Perform efficient pandas DataFrame operations for data analysis, manipulation, and transformation with production-grade patterns.
10.4k · bundle
schattenspiegel pandas-python
Write, review, debug, test, or optimize pandas Series, DataFrame, Index, groupby, merge, reshape, dtype, missing-value, and time-series code.
0 · bundle
k-dense-ai geopandas
Extends pandas for geospatial vector data analysis, including reading/writing shapefiles, GeoJSON, GeoPackage, and PostGIS, performing spatial joins, geometric operations, coordinate transformations, and creating static or interactive maps.
30.2k · bundle
schattenspiegel polars-python
Write, review, debug, test, and optimize Python Polars code with version-grounded object types, schemas, and execution boundaries.
0 · bundle
lingxling polars
High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.
253 · bundle
phoroth polars
Process in-memory tabular data with a fast, expression-based DataFrame library that supports lazy evaluation, parallel execution, and Apache Arrow semantics.
3