#dataframes (3)

Cheat sheets (3)

modin — Drop-in pandas at Scale

Speed up pandas workloads across all CPU cores with a one-line import swap. Covers Ray and Dask backends, config tuning, pandas interop, and when modin wins vs polars.

python modin pandas dataframes parallel ray dask data

polars — Fast DataFrames

High-performance DataFrames with a lazy expression API. Covers read/write, select, filter, group_by, joins, LazyFrame, datetime, string operations, and pandas interop.

python polars dataframes data csv parquet sql

pandas — DataFrames

Load, filter, transform, and aggregate tabular data with pandas. Covers DataFrame creation, read_csv, groupby, merge, and the SettingWithCopy pitfall.

python pandas dataframes data csv analysis

g h	home
g p	Programming section
g p	Python section
g j	JavaScript section
g t	TypeScript section
g o	OS section
g l	Linux section
g w	Windows section
g z	z/OS section
g o	macOS section
g a	AI section
g c	Claude Code section
g c	Codex CLI section
g c	Claude API section
g p	Prompting section
g f	Frameworks section
g p	Packages section
g p	Pip (Python) section
g p	npm (Node) section
g p	Cargo (Rust) section
g p	Go modules section
g g	graph view
g t	tags index

⌘K / /	open search palette
t	cycle theme (dark → light → system)
?	toggle this panel

[ / ]	previous / next sheet in section
j / k	scroll down / up