API Reference

Welcome to the Polynx API reference. This section contains detailed documentation of all classes, methods, and functions provided by Polynx.

Reference Sections

- :material-table: __[DataFrame](dataframe.md)__ --- String querying, multi-statement assignments, group aggregations, sorting, and statistical utilities. - :material-timer-sand: __[LazyFrame](lazyframe.md)__ --- Deferred query execution, lazy string expressions, lazy column indexing, and query collection. - :material-format-list-numbered: __[Series](series.md)__ --- Polars Series wrapper with sequence indexing, length operations, and data export. - :material-code-parentheses: __[Expressions (Expr)](expr.md)__ --- Window aggregations, rolling product calculation, and method chaining. - :material-code-tags: __[String DSL Functions](dsl.md)__ --- Functions callable within string expressions: `case_when`, `select`, `where`, `mondf`, horizontal operations, and `@var`. - :material-swap-horizontal: __[Input / Output & Merge](io.md)__ --- Pandas-style `plx.merge()`, top-level Polars functions (`concat`, `read_csv`, `read_parquet`), and unwrapping. - :material-tune: __[Configuration & Cache](config.md)__ --- Cache modes (`raw`, `hash`, `custom_lru`, `none`), capacity management, and diagnostic metrics. - :material-function: __[User Defined Functions (UDF)](udf.md)__ --- Custom Python function registration for invocation inside string expressions.

Quick Reference Table

Function / Method	Category	Description
`df.query(query_str)`	DataFrame	Filter rows using string expressions with variable substitution
`df.eval(query_str, mode)`	DataFrame	Evaluate mathematical or string expressions returning calculated columns
`df.assign(query_str)`	DataFrame	Append calculated columns evaluated from string expressions
`df.wc(args, *kwargs)`	DataFrame	Extended `with_columns` supporting multi-statement assignment strings
`df.gb(gp_keys, expr, with_subtotal)`	DataFrame	Group by with string aggregation expressions and optional subtotals
`df.describe(group_keys, ...)`	DataFrame	Extended descriptive statistics supporting group keys
`df.dd()`	DataFrame	Deduplicate rows keeping first occurrence and maintaining order
`df.dsort(by)`	DataFrame	Sort rows in descending order
`df.asort(by)`	DataFrame	Sort rows in ascending order
`df.unstack()`	DataFrame	Pivot DataFrame using last two columns as keys and values
`df.vcnt(col)`	DataFrame	Value counts grouped by column(s), sorted descending
`df.ucnt(col)`	DataFrame	Total distinct / unique row count as a scalar integer
`df.round(decimal)`	DataFrame	Round all floating-point columns to specified decimal places
`df.cum_max()`	DataFrame	Cumulative maximum across all floating-point columns
`df.to_list(col_name)`	DataFrame	Extract column values directly as a Python list
`df.max(col_name)`	DataFrame	Extract scalar maximum value from a column
`df.min(col_name)`	DataFrame	Extract scalar minimum value from a column
`df.size(unit, return_size)`	DataFrame	Inspect and report estimated memory footprint
`df.rename(new_cols)`	DataFrame	Rename columns using either a dictionary mapping or a list of new names
`df.pplot(args, *kwargs)`	DataFrame	Quick plotting via Pandas plotting API
`df.to_polars()`	Interop	Return native `polars.DataFrame`
`df.to_pandas()`	Interop	Return native `pandas.DataFrame`
`expr.rolling_prod(...)`	Expr	Rolling window product via log-sum-exp
`plx.merge(left, right, ...)`	Functions	Pandas-style DataFrame join with automatic overlapping column suffixes
`case_when(conds, choices, default)`	String DSL	Conditional branching supporting multi-condition lists or ternary pairs
`select(conds, choices, default)`	String DSL	Multi-condition branching mirroring `numpy.select`
`where(cond, choice, default)`	String DSL	Ternary condition branching mirroring `numpy.where`
`mondf(beg_date, end_date)`	String DSL	Calculate difference in months between two date/datetime columns
`max_horizontal(...)`	String DSL	Compute row-wise maximum across columns
`min_horizontal(...)`	String DSL	Compute row-wise minimum across columns
`plx.register_udf(name, fn)`	UDF	Register Python function for use inside string expressions
`plx.config.set_cache_mode(mode)`	Config	Configure expression caching backend (`raw`, `hash`, `custom_lru`, `none`)
`plx.clear_all_expr_caches()`	Config	Clear all internal expression caches