1.
Introduction
2.
Getting started
❱
2.1.
Polars quick exploration guide
3.
Polars expressions
❱
3.1.
Expressions
3.2.
Contexts
3.3.
GroupBy
3.4.
Folds
3.5.
Window functions
3.6.
List context and row-wise compute
3.7.
Numpy universal functions
3.8.
Custom functions
3.9.
Python Examples
3.10.
Rust Examples
3.11.
API
3.12.
Video introduction
4.
Data Types
5.
Coming from Pandas
6.
Coming from Apache Spark
7.
How can I?
❱
7.1.
IO
❱
7.1.1.
CSV files
7.1.2.
Parquet files
7.1.3.
JSON files
7.1.4.
Multiple files
7.1.5.
Read from a database
7.1.6.
Interact with AWS
7.1.7.
Interact with Google BigQuery
7.1.8.
Interact with Postgres
7.1.9.
Interoperability
❱
7.1.9.1.
Arrow
7.1.9.2.
NumPy
7.2.
Selecting data
❱
7.2.1.
Selecting with expressions
7.2.2.
Selecting with indexing
7.3.
Data handling
❱
7.3.1.
Process strings
7.3.2.
Process timestamps
7.3.3.
Process missing data
7.4.
Time-series
❱
7.4.1.
Parsing dates and times
7.4.2.
Filtering by dates
7.4.3.
Fixed and rolling temporal groupby
7.4.4.
Resampling
7.5.
Combining data
❱
7.5.1.
Concatenation
7.5.2.
Joining
7.6.
Multiprocessing
8.
Performance
❱
8.1.
Strings
9.
Optimizations
❱
9.1.
Lazy API
❱
9.1.1.
Predicate pushdown
9.1.2.
Projection pushdown
9.1.3.
Other optimizations
10.
Testing
11.
Reference guides
12.
Contributing
Light
Rust
Coal
Navy
Ayu (default)
Polars - User Guide
Data handling