1. 1. Introduction
  2. 2. Getting started
  3. 3. Polars expressions
    ❱
    1. 3.1. Expressions
    2. 3.2. Contexts
    3. 3.3. GroupBy
    4. 3.4. Folds
    5. 3.5. Window functions
    6. 3.6. List context and row-wise compute
    7. 3.7. Numpy universal functions
    8. 3.8. Custom functions
    9. 3.9. Examples
    10. 3.10. API
    11. 3.11. Video introduction
  4. 4. Indexing
  5. 5. Data Types
  6. 6. Coming from Pandas
  7. 7. Coming from Apache Spark
  8. 8. Time-series
  9. 9. How can I?
    ❱
    1. 9.1. IO
      ❱
      1. 9.1.1. CSV files
      2. 9.1.2. Parquet files
      3. 9.1.3. Multiple files
      4. 9.1.4. Read from a database
      5. 9.1.5. Interact with AWS
      6. 9.1.6. Interact with Google BigQuery
      7. 9.1.7. Interact with Postgres
      8. 9.1.8. Interoperability
        ❱
        1. 9.1.8.1. Arrow
        2. 9.1.8.2. NumPy
      9. 9.1.9. Data handling
        ❱
        1. 9.1.9.1. Process strings
        2. 9.1.9.2. Process timestamps
  10. 10. Performance
    ❱
    1. 10.1. Strings
  11. 11. Optimizations
    ❱
    1. 11.1. Lazy API
      ❱
      1. 11.1.1. Predicate pushdown
      2. 11.1.2. Projection pushdown
      3. 11.1.3. Other optimizations
  12. 12. Reference guides

Polars - User Guide

Data handling