### Complete SQL Query Example

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/07-sql.md

Demonstrates creating a DataFrame, setting up an SQL context, and executing multiple SQL queries for data analysis. Use `eager: true` to get immediate results.

```typescript
import pl from 'nodejs-polars';

// Create sample data
const moviesData = [
  { title: 'The Godfather', year: 1972, budget: 6_000_000, gross: 134_821_952, imdb: 9.2 },
  { title: 'The Dark Knight', year: 2008, budget: 185_000_000, gross: 533_316_061, imdb: 9.0 },
  { title: 'Schindler\'s List', year: 1993, budget: 22_000_000, gross: 96_067_179, imdb: 8.9 },
  { title: 'Pulp Fiction', year: 1994, budget: 8_000_000, gross: 107_930_000, imdb: 8.9 },
  { title: 'The Shawshank Redemption', year: 1994, budget: 25_000_000, gross: 28_341_469, imdb: 9.3 }
];

const df = pl.readRecords(moviesData);

// Create SQL context
const ctx = pl.SQLContext({ films: df });

// Query 1: Find high-rated films
const highRated = ctx.execute(
  `
  SELECT title, year, imdb 
  FROM films 
  WHERE imdb > 9 
  ORDER BY imdb DESC
`,
  { eager: true }
);

console.log(highRated);

// Query 2: Profitability analysis
const profitable = ctx.execute(
  `
  SELECT 
    title, 
    (gross - budget) as profit,
    ROUND((100.0 * (gross - budget) / budget), 2) as roi_percent
  FROM films
  WHERE gross > budget
  ORDER BY profit DESC
`,
  { eager: true }
);

console.log(profitable);

// Query 3: Decade analysis
const byDecade = ctx.execute(
  `
  SELECT 
    CAST((year / 10) * 10 AS INT) as decade,
    COUNT(*) as count,
    AVG(imdb) as avg_rating,
    SUM(gross) as total_gross
  FROM films
  GROUP BY decade
  ORDER BY decade DESC
`,
  { eager: true }
);

console.log(byDecade);

```

--------------------------------

### Install project dependencies

Source: https://github.com/pola-rs/nodejs-polars/blob/main/CONTRIBUTING.md

After cloning the repository, install all necessary project dependencies using yarn.

```bash
yarn install
```

--------------------------------

### Chaining Example

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/configuration.md

Demonstrates the chainability of Configuration API methods for fluent usage.

```APIDOC
## Chaining

All methods return Config for fluent chaining:

### Example
```typescript
import pl from 'nodejs-polars';

pl.Config
  .setAsciiTables(true)
  .setTblRows(10)
  .setTblCols(5)
  .setThousandsSeparator(true);
```
```

--------------------------------

### Schema Example

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Illustrates creating a schema object and using it to initialize a DataFrame.

```typescript
const schema: Schema = {
  name: pl.String,
  age: pl.Int32,
  created: pl.Datetime('ns', 'UTC')
};

const df = pl.DataFrame(data, { schema });
```

--------------------------------

### Installing Node.js Polars

Source: https://github.com/pola-rs/nodejs-polars/blob/main/README.md

Provides installation commands for nodejs-polars using popular package managers like yarn, npm, and Bun. It also notes that frequent updates are common.

```sh
$ yarn add nodejs-polars # yarn
$ npm i -s nodejs-polars # npm
$ bun i -D nodejs-polars # Bun

```

--------------------------------

### Datetime Examples

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Demonstrates creating Datetime types with different time units and timezones.

```typescript
pl.Datetime();
```

```typescript
pl.Datetime('ns');
```

```typescript
pl.Datetime('us', 'America/New_York');
```

--------------------------------

### Example: Compute Dot Product

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Demonstrates calculating the dot product of two Series.

```typescript
const s1 = pl.Series([1, 2, 3]);
const s2 = pl.Series([4, 5, 6]);
s1.dot(s2); // 1*4 + 2*5 + 3*6 = 32
```

--------------------------------

### Decimal Type Example

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Shows how to instantiate a Decimal type with specified precision and scale.

```typescript
pl.Decimal(10, 2); // 10 digits total, 2 after decimal
```

--------------------------------

### Field Class Example

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Demonstrates how to create a `Field` instance and define a schema using it.

```typescript
const field = new Field('my_column', pl.Int64);
const schema = { my_column: pl.Int64 };
```

--------------------------------

### Series Constructor Examples

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Illustrates practical usage of the Series constructor with various parameter combinations.

```typescript
const s = pl.Series('my_series', [1, 2, 3]);
const s = pl.Series([1, 2, 3]); // name defaults to ''
const s = pl.Series('nums', [1, 2, 3], pl.Float64);
const s = pl.Series({ name: 'data', values: [1, 2, 3] });
```

--------------------------------

### Clone the nodejs-polars repository

Source: https://github.com/pola-rs/nodejs-polars/blob/main/CONTRIBUTING.md

Fork the repository and then clone it from your fork to start development.

```bash
git clone https://github.com/<your-github-username>/nodejs-polars.git
```

--------------------------------

### Example: Fill Null Values

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Demonstrates filling null values using 'forward' and 'min' strategies.

```typescript
s.fillNull('forward'); // forward fill
s.fillNull('min'); // fill with minimum value
```

--------------------------------

### Example: Explode Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Shows how to use `explode` to transform a Series of lists into a flat Series.

```typescript
const s = pl.Series([[1, 2], [3, 4]]);
s.explode(); // [1, 2, 3, 4]
```

--------------------------------

### sample()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/01-dataframe.md

Get a random sample of rows from the DataFrame, with options for number of samples, fraction, replacement, and seed.

```APIDOC
## sample()

### Description
Random sample of rows.

### Method
```typescript
sample(options?: { n?: number, fraction?: number, withReplacement?: boolean, seed?: number }): DataFrame
```

### Parameters
#### Path Parameters
- **n** (number) - Optional - Number of rows to sample
- **fraction** (number) - Optional - Fraction of rows to sample (0-1)
- **withReplacement** (boolean) - Optional - Sample with replacement; default false
- **seed** (number) - Optional - Random seed

### Response
#### Success Response (200)
- **DataFrame** - Sampled DataFrame.
```

--------------------------------

### IO Operations

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Provides examples for reading from and writing to various file formats like CSV, JSON, and Parquet.

```APIDOC
## IO Operations

### Description
Provides examples for reading from and writing to various file formats like CSV, JSON, and Parquet.

### IO Operations

```typescript
// Read CSV
const df = pl.readCSV('data.csv');
const df = pl.readCSV('col1,col2\n1,a\n2,b');

// Read JSON
const df = pl.readJSON('data.json');

// Read Parquet
const df = pl.readParquet('data.parquet');

// Write CSV
df.writeCSV('output.csv');
const csv = df.writeCSV();

// Write Parquet
df.writeParquet('output.parquet');
```
```

--------------------------------

### groupBy()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Starts a groupby operation on a LazyDataFrame, allowing for subsequent aggregations.

```APIDOC
## groupBy()

### Description
Starts a groupby operation on a LazyDataFrame, allowing for subsequent aggregations.

### Method Signature
```typescript
groupBy(...columns: (string | Expr)[]): LazyGroupBy
groupBy(columns: (string | Expr)[]): LazyGroupBy
```

### Parameters
- **columns** ((string | Expr)[]) - Required - Column names or expressions to group by

### Returns
LazyGroupBy object.

### Example
```typescript
ldf.groupBy('group').agg([pl.col('value').sum()]);
ldf.groupBy('a', 'b').agg(pl.col('c').mean());
```
```

--------------------------------

### intRange()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Creates a range of integers. It supports specifying start, end, step, and an option to materialize the range into a Series.

```APIDOC
## intRange()

### Description
Creates a range of integers.

### Signature
```typescript
intRange(start: number, end: number, step?: number, eager?: boolean): Expr | Series
```

### Parameters
#### Path Parameters
- **start** (number) - Required - Start value (inclusive)
- **end** (number) - Required - End value (exclusive)
- **step** (number) - Optional - Increment step; default 1
- **eager** (boolean) - Optional - Materialize to Series; default false

### Returns
Expr or Series if eager=true.

### Examples
```typescript
pl.intRange(0, 5);
pl.intRange(0, 10, 2);
pl.intRange(5, 0, -1);
pl.intRange(0, 5, 1, true);
```
```

--------------------------------

### Accessing Polars Library Version

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Shows how to access the currently installed version of the nodejs-polars library.

```typescript
import pl from 'nodejs-polars';
console.log(pl.version);
```

--------------------------------

### SQL Error Handling Example

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/07-sql.md

Demonstrates how to catch and log SQL parse errors using a try-catch block. This is useful for debugging invalid SQL syntax.

```typescript
try {
  const result = ctx.execute('SELEC * FROM table', { eager: true });
} catch (e) {
  console.error('SQL Error:', e.message);
}
```

--------------------------------

### Start Conditional Expression

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Initiates a conditional expression. Use .then() and .otherwise() to define the branches.

```typescript
pl.when(pl.col('a') > 5)
  .then(pl.lit('high'))
  .otherwise(pl.lit('low'))
```

--------------------------------

### Method Chaining Example

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/04-expr.md

Demonstrates fluent method chaining for Polars expressions. Multiple operations like filtering, aggregation, aliasing, and casting can be chained sequentially.

```typescript
pl.col('value')
  .filter(pl.col('status').eq('active'))
  .sum()
  .alias('active_sum')
  .cast(pl.Int32)
```

--------------------------------

### when().then().otherwise()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Starts a conditional expression. It allows defining a condition and specifying the resulting expression for both true and false outcomes.

```APIDOC
## when()

### Description
Starts a conditional expression.

### Signature
```typescript
when(condition: Expr): When
```

### Returns
When object with `.then()` method.

### Example
```typescript
pl.when(pl.col('a') > 5)
  .then(pl.lit('high'))
  .otherwise(pl.lit('low'))
```
See [Expression API Reference](04-expr.md) for full documentation.
```

--------------------------------

### Get First N Elements of Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Illustrates retrieving the first n elements from a Series.

```typescript
head(n?: number): Series
```

--------------------------------

### Writing DataFrame to CSV

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Shows how to write a DataFrame to a CSV file or get its CSV representation as a string.

```typescript
// Write CSV
df.writeCSV('output.csv');
const csv = df.writeCSV();
```

--------------------------------

### Create Integer Range

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Generates a range of integers. Supports custom start, end, step, and eager materialization to a Series.

```typescript
pl.intRange(0, 5);
pl.intRange(0, 10, 2);
pl.intRange(5, 0, -1);
pl.intRange(0, 5, 1, true);
```

--------------------------------

### DataFrame Properties

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/01-dataframe.md

Access properties of a DataFrame to get information about its dimensions and structure.

```APIDOC
## DataFrame Properties

### shape
```typescript
shape: { height: number; width: number }
```
Returns object with `height` (row count) and `width` (column count).

### height
```typescript
height: number
```
Number of rows in the DataFrame.

### width
```typescript
width: number
```
Number of columns in the DataFrame.

### columns
```typescript
columns: string[]
get columns(): string[]
set columns(cols: string[]): void
```
Get or set column names.

### dtypes
```typescript
dtypes: DataType[]
```
Array of DataType for each column in column order.
```

--------------------------------

### Get LazyDataFrame Column Names

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Retrieves an array of column names from the LazyDataFrame.

```typescript
get columns(): string[]
```

--------------------------------

### Build the debug binary

Source: https://github.com/pola-rs/nodejs-polars/blob/main/CONTRIBUTING.md

Compile the project in debug mode to prepare for local development and testing.

```bash
yarn build:debug
```

--------------------------------

### Get Group Indices

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

The `groups` function returns the group indices for groupby operations.

```typescript
df.groups();
```

--------------------------------

### GroupBy Aggregation: Last Value

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/06-groupby.md

Get the last value of a column within each group.

```typescript
pl.col('value').last();
```

--------------------------------

### GroupBy Aggregation: First Value

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/06-groupby.md

Get the first value of a column within each group.

```typescript
pl.col('value').first();
```

--------------------------------

### Configuring Table Display Options

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Illustrates how to configure global settings for table display, such as the number of rows, columns, and character width.

```typescript
import pl from 'nodejs-polars';

pl.Config.setTblRows(5);
pl.Config.setTblCols(3);
pl.Config.setTblWidthChars(100);
pl.Config.setAsciiTables(true);
```

--------------------------------

### Display DataFrame as Last Expression in Deno (v1.38)

Source: https://github.com/pola-rs/nodejs-polars/blob/main/README.md

In Deno 1.38+, a DataFrame can be displayed by simply being the last expression in a cell. This example fetches data and reads it into a DataFrame.

```typescript
import pl from "npm:nodejs-polars";
let response = await fetch(
  "https://cdn.jsdelivr.net/npm/world-atlas@1/world/110m.tsv",
);
let data = await response.text();
let df = pl.readCSV(data, { sep: "\t" });
df
```

--------------------------------

### Run project tests

Source: https://github.com/pola-rs/nodejs-polars/blob/main/CONTRIBUTING.md

Execute the test suite to ensure all functionalities are working as expected.

```bash
yarn test
```

--------------------------------

### Create DataFrames and Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/INDEX.md

Demonstrates creating DataFrames from objects, reading from CSV, scanning Parquet files, creating Series, and reading data from records.

```typescript
// DataFrame
const df = pl.DataFrame({ a: [1, 2, 3], b: ['x', 'y', 'z'] });
const df = pl.readCSV('file.csv');
const ldf = pl.scanParquet('large.parquet');

// Series
const s = pl.Series('name', [1, 2, 3]);

// From records
const df = pl.readRecords([{ a: 1, b: 'x' }, { a: 2, b: 'y' }]);
```

--------------------------------

### Method Chaining

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/04-expr.md

Demonstrates method chaining for expressions.

```APIDOC
## Method Chaining

All expression methods return an `Expr`, allowing for fluent method chaining.

**Example**:
```typescript
pl.col('value')
  .filter(pl.col('status').eq('active'))
  .sum()
  .alias('active_sum')
  .cast(pl.Int32)
```
```

--------------------------------

### clone()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Creates a cheap deep clone of the Series.

```APIDOC
## clone()

### Description
Create a cheap deep clone.

### Method Signature
```typescript
clone(): Series
```

### Returns
- Cloned Series.
```

--------------------------------

### DataFrame Creation

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Demonstrates various ways to create a DataFrame, including from an object with inferred or explicit schemas, and from an array of records.

```APIDOC
## DataFrame Creation

### Description
Demonstrates various ways to create a DataFrame, including from an object with inferred or explicit schemas, and from an array of records.

### Creating DataFrames

```typescript
// From object with inferred schema
const df = pl.DataFrame({ a: [1, 2, 3], b: ['x', 'y', 'z'] });

// With explicit schema
const df = pl.DataFrame(
  { a: [1, 2, 3], b: ['x', 'y', 'z'] },
  { schema: { a: pl.Int32, b: pl.String } }
);

// From array of records
const records = [{ a: 1, b: 'x' }, { a: 2, b: 'y' }];
const df = pl.readRecords(records);
```
```

--------------------------------

### Get Unique Values from an Expression

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/04-expr.md

Remove duplicate values from an expression using the `unique` method.

```typescript
unique(): Expr
```

--------------------------------

### Get Last N Elements of Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Illustrates retrieving the last n elements from a Series.

```typescript
tail(n?: number): Series
```

--------------------------------

### Executing SQL Queries with SQLContext

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Demonstrates how to use SQLContext to execute SQL queries against DataFrames, with an option for eager execution.

```typescript
const ctx = pl.SQLContext({ df1, df2 });
const result = ctx.execute('SELECT * FROM df1 WHERE x > 10', { eager: true });
```

--------------------------------

### Series Constructor Overloads

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Demonstrates the different ways to instantiate a Series, including providing name, values, and dtype, or using an options object.

```typescript
Series(
  name?: string,
  values?: ArrayLike<any>,
  dtype?: DataType
): Series

Series(
  options: { name?: string, values: ArrayLike<any>, dtype?: DataType }
): Series
```

--------------------------------

### SQL Queries

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Shows how to execute SQL queries against DataFrames using the SQLContext.

```APIDOC
## SQL Queries

### Description
Shows how to execute SQL queries against DataFrames using the SQLContext.

### SQL Queries

```typescript
const ctx = pl.SQLContext({ df1, df2 });
const result = ctx.execute('SELECT * FROM df1 WHERE x > 10', { eager: true });
```
```

--------------------------------

### sample()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Returns a random sample of elements from the Series with various options for sampling.

```APIDOC
## sample()

### Description
Random sample of elements.

### Method Signature
```typescript
sample(options?: { n?: number, fraction?: number, withReplacement?: boolean, seed?: number }): Series
```

### Parameters
#### Path Parameters
- **n** (number) - Optional - Number of elements to sample.
- **fraction** (number) - Optional - Fraction to sample (0-1).
- **withReplacement** (boolean) - Optional - Sample with replacement; default false.
- **seed** (number) - Optional - Random seed.

### Returns
- Sampled Series.
```

--------------------------------

### List Operations

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Perform operations on List Series, such as getting lengths, accessing elements by index, joining, and exploding.

```APIDOC
### List Operations (list)

Available on List Series:

```typescript
s.list.lengths();
s.list.getByIndex(index);
s.list.join(separator);
s.list.explode();
```
```

--------------------------------

### Create Empty SQLContext

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/07-sql.md

Initialize an empty SQLContext without any pre-registered tables.

```typescript
import pl from 'nodejs-polars';

// Empty context
const ctx = pl.SQLContext();
```

--------------------------------

### argSortBy()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Get the indices that would sort the data by the specified expressions. This is useful for understanding the order of elements after sorting.

```APIDOC
## argSortBy()

### Description
Get indices that would sort by expressions.

### Method
(Not specified, likely a method on a DataFrame or Expression object)

### Parameters
- **...exprs** (Expr[]) - Expressions to sort by.

### Request Example
```typescript
df.select(pl.argSortBy('col1', 'col2'));
```

### Response
- **Expr** - Returns an expression object representing the sorting indices.
```

--------------------------------

### Get Sorting Indices

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Use `argSortBy` to obtain the indices that would sort the DataFrame based on one or more columns.

```typescript
df.select(pl.argSortBy('col1', 'col2'));
```

--------------------------------

### describe()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Computes and returns summary statistics for the Series, including min, max, mean, standard deviation, and count.

```APIDOC
## describe()

### Description
Compute summary statistics.

### Method
Not applicable (Instance method)

### Returns
- **DataFrame** - A DataFrame containing statistics (min, max, mean, std, count, etc.).
```

--------------------------------

### Series Properties

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Access properties of a Series to get its name, data type, length, or specialized function namespaces.

```APIDOC
## Series Properties

### name
- **Type**: `string`
- **Description**: The name of the Series.

### dtype
- **Type**: `DataType`
- **Description**: The data type of all values in the Series.

### length
- **Type**: `number`
- **Description**: Number of elements in the Series.

### str
- **Type**: `SeriesStringFunctions`
- **Description**: String operations namespace. Only valid for String type Series.

### dt
- **Type**: `SeriesDateFunctions`
- **Description**: Datetime operations namespace. Valid for Date, Time, Datetime, Duration types.

### list
- **Type**: `SeriesListFunctions`
- **Description**: List operations namespace. Only valid for List type Series.

### struct
- **Type**: `SeriesStructFunctions`
- **Description**: Struct operations namespace. Only valid for Struct type Series.
```

--------------------------------

### describePlan()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Retrieves the unoptimized query plan of the LazyDataFrame as a string.

```APIDOC
## describePlan()

### Description
Get unoptimized query plan as string.

### Method
`describePlan(): string`

### Response
#### Success Response
- **string** - String representation of logical plan.

### Request Example
```typescript
const plan = ldf.describePlan();
```
```

--------------------------------

### Join LazyDataFrame on Same Column

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Example of joining two LazyDataFrames on a column with the same name. Uses the 'on' option for simplicity.

```typescript
ldf1.join(ldf2, { on: 'id' });
```

--------------------------------

### Run precommit checks

Source: https://github.com/pola-rs/nodejs-polars/blob/main/CONTRIBUTING.md

Ensure all tests pass and code is formatted correctly before committing changes.

```bash
yarn precommit
```

--------------------------------

### Importing Data Types and Creating DataFrame

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Demonstrates how to import the Polars namespace and use data types for schema definition when creating a DataFrame.

```typescript
import pl from 'nodejs-polars';
const dt = pl.Int64;
const df = pl.DataFrame({ a: [1, 2, 3] }, { schema: { a: pl.Int64 } });
```

--------------------------------

### Multiple Grouping Columns

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/06-groupby.md

Demonstrates grouping by multiple columns using either string arguments or an array of strings.

```APIDOC
## Multiple Grouping Columns

### Description
Group by unique combinations of multiple columns.

### Examples
```typescript
// Using multiple string arguments
df.groupBy('col1', 'col2').agg(pl.col('value').sum());

// Using an array of strings
df.groupBy(['col1', 'col2']).agg(pl.col('value').sum());
```
```

--------------------------------

### head()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Returns the first n elements of the Series.

```APIDOC
## head()

### Description
Return first n elements (default 5).

### Method Signature
```typescript
head(n?: number): Series
```
```

--------------------------------

### Get Column as Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/01-dataframe.md

Retrieve a specific column from the DataFrame as a Series object. This can also be done using bracket notation.

```typescript
const s = df.getColumn('a');
```

```typescript
const s = df['a'];
```

--------------------------------

### Get Indices of Unique Values

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Returns a Series containing the indices of the first occurrence of each unique value in the original Series.

```typescript
argUnique(): Series
```

--------------------------------

### Configuration Settings

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Demonstrates how to configure Polars display options such as table rows, columns, and character width.

```APIDOC
## Configuration Settings

### Description
Demonstrates how to configure Polars display options such as table rows, columns, and character width.

### Configuration

```typescript
import pl from 'nodejs-polars';

pl.Config.setTblRows(5);
pl.Config.setTblCols(3);
pl.Config.setTblWidthChars(100);
pl.Config.setAsciiTables(true);
```
```

--------------------------------

### Get Indices of True Values in Boolean Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

For a boolean Series, returns a Series containing the indices where the values are true.

```typescript
argTrue(): Series
```

--------------------------------

### Importing Node.js Polars

Source: https://github.com/pola-rs/nodejs-polars/blob/main/README.md

Demonstrates how to import the nodejs-polars library using both ES Module (esm) and CommonJS (require) syntax.

```javascript
// esm
import pl from 'nodejs-polars';

// require
const pl = require('nodejs-polars');

```

--------------------------------

### Create SQLContext with Pre-registered Tables

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/07-sql.md

Initialize a SQLContext with DataFrames or LazyDataFrames already registered as tables.

```typescript
import pl from 'nodejs-polars';

// Pre-register tables
const df1 = pl.DataFrame({ a: [1, 2], b: [3, 4] });
const df2 = pl.DataFrame({ c: [5, 6], d: [7, 8] });
const ctx = pl.SQLContext({ table1: df1, table2: df2 });
```

--------------------------------

### groups()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Get group indices for groupby operations. This function is used in conjunction with groupby operations to identify the indices belonging to each group.

```APIDOC
## groups()

### Description
Get group indices for groupby operations.

### Method
(Not specified, likely a method on a DataFrame or Expression object)

### Response
- **Expr** - Returns an expression object representing the group indices.
```

--------------------------------

### Clone Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Illustrates creating a cheap deep clone of a Series.

```typescript
clone(): Series
```

--------------------------------

### Correcting List Operation

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/errors.md

Shows how to perform list-specific operations before aggregation, such as getting the lengths of lists within a column, to avoid InvalidOperationError.

```typescript
// ❌ Wrong
const result = listCol.mean();

// ✅ Correct
const result = listCol.list.lengths().mean();
```

--------------------------------

### WriteAvroOptions

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Avro output options, specifying the compression codec to be used.

```APIDOC
## WriteAvroOptions

### Description
Avro output options.

### Fields
- **compression** (string) - Optional - Compression codec. Supported values: 'uncompressed', 'snappy', 'deflate'.
```

--------------------------------

### Aggregate LazyDataFrame after GroupBy

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Perform aggregation operations on a grouped LazyDataFrame. Examples show summing a column and calculating the mean of another.

```typescript
ldf.groupBy('group').agg([pl.col('value').sum()]);
ldf.groupBy('a', 'b').agg(pl.col('c').mean());
```

--------------------------------

### Describe Unoptimized Query Plan

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Retrieve the unoptimized logical query plan as a string.

```typescript
ldf.describePlan();
```

--------------------------------

### List Operations

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/04-expr.md

Provides methods for manipulating list-type expressions, such as getting lengths, accessing elements, exploding, concatenating, slicing, and performing aggregations.

```typescript
expr.list.lengths();
expr.list.getByIndex(index);
expr.list.getByIndexExpr(index);
expr.list.first();
expr.list.last();
expr.list.explode();
expr.list.concat(other);
expr.list.join(separator);
expr.list.slice(offset, length);
expr.list.head(n);
expr.list.tail(n);
expr.list.contains(item);
expr.list.unique();
expr.list.max();
expr.list.min();
expr.list.sum();
expr.list.mean();
expr.list.reverse();
expr.list.sort();
```

--------------------------------

### Get the last value expression

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/04-expr.md

Use the `last()` aggregation function to retrieve the last value in a column or group. This is often used after sorting.

```typescript
pl.last();
```

--------------------------------

### Describe Optimized Query Plan

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Retrieve the optimized logical query plan as a string, with optional optimization configurations.

```typescript
ldf.describeOptimizedPlan(opts);
```

--------------------------------

### Efficient GroupBy with Projection Pushdown

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/06-groupby.md

Demonstrates an efficient way to perform groupBy by selecting only necessary columns before the operation, leveraging projection pushdown.

```typescript
// ✅ More efficient
df.select(['group', 'value'])
  .groupBy('group')
  .agg(pl.col('value').sum());
```

--------------------------------

### Get the first value expression

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/04-expr.md

Use the `first()` aggregation function to retrieve the first value in a column or group. This is often used after sorting.

```typescript
pl.first();
```

--------------------------------

### Get Unique Rows from LazyDataFrame

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Remove duplicate rows from a LazyDataFrame. You can specify a subset of columns to consider for uniqueness and control which duplicate to keep.

```typescript
unique(options?: { subset?: string[], keep?: 'first' | 'last' | 'none', maintainOrder?: boolean }): LazyDataFrame
```

--------------------------------

### Version Information

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Demonstrates how to access the version of the nodejs-polars library.

```APIDOC
## Version

### Description
Access the library version.

### Version

```typescript
import pl from 'nodejs-polars';
console.log(pl.version);
```
```

--------------------------------

### Struct Operations

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/04-expr.md

Methods for interacting with struct-type expressions, including retrieving field names, getting specific fields by name, and unnesting struct fields.

```typescript
expr.struct.fieldNames();
expr.struct.getFieldByName(field);
expr.struct.getAllFields();
expr.struct.unnest();
```

--------------------------------

### Create SQLContext with Mixed Eager and Lazy Frames

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/07-sql.md

Initialize a SQLContext with a mix of eager DataFrames and lazy LazyDataFrames.

```typescript
import pl from 'nodejs-polars';

// Mix eager and lazy
const ldf = pl.scanCSV('large.csv');
const ctx = pl.SQLContext({ eager_table: df1, lazy_table: ldf });
```

--------------------------------

### Get Last N Rows

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/01-dataframe.md

Use `tail()` to retrieve the last `n` rows of a DataFrame. Defaults to the last 5 rows if `n` is not specified.

```typescript
df.tail(10);
```

--------------------------------

### Chain Configuration Settings

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/configuration.md

All configuration methods are chainable, allowing for fluent API usage to set multiple display options in a single statement.

```typescript
import pl from 'nodejs-polars';

pl.Config
  .setAsciiTables(true)
  .setTblRows(10)
  .setTblCols(5)
  .setThousandsSeparator(true);
```

--------------------------------

### Get First N Rows

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/01-dataframe.md

Use `head()` to retrieve the first `n` rows of a DataFrame. Defaults to the first 5 rows if `n` is not specified.

```typescript
df.head(10);
```

--------------------------------

### WriteIPCOptions

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Arrow IPC output options, allowing selection of the compression codec.

```APIDOC
## WriteIPCOptions

### Description
Arrow IPC output options.

### Fields
- **compression** (string) - Optional - Compression codec. Supported values: 'uncompressed', 'lz4', 'zstd'.
```

--------------------------------

### Get First N Rows of LazyDataFrame

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Retrieve the first 'n' rows from a LazyDataFrame. Defaults to 5 rows if 'n' is not specified. Useful for previewing data.

```typescript
head(n?: number): LazyDataFrame
```

--------------------------------

### Configure Polars Display and Behavior

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/INDEX.md

Demonstrates how to configure Polars settings such as the number of rows displayed, table formatting, and ASCII table output.

```typescript
pl.Config
  .setTblRows(10)
  .setAsciiTables(true)
  .setTblWidthChars(100);
```

--------------------------------

### SQLContext Constructor

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/07-sql.md

Creates a SQL context, which allows executing SQL queries against registered DataFrames or LazyDataFrames. You can optionally pre-register tables during initialization.

```APIDOC
## SQLContext Constructor

```typescript
SQLContext(frames?: Record<string, DataFrame | LazyDataFrame>): SQLContext
```

### Description
Create a SQL context with optional initial DataFrames/LazyFrames.

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
* **frames** (Record<string, DataFrame | LazyDataFrame>) - Optional - Initial tables to register

### Request Example
```typescript
import pl from 'nodejs-polars';

// Empty context
const ctx = pl.SQLContext();

// Pre-register tables
const df1 = pl.DataFrame({ a: [1, 2], b: [3, 4] });
const df2 = pl.DataFrame({ c: [5, 6], d: [7, 8] });
const ctx = pl.SQLContext({ table1: df1, table2: df2 });

// Mix eager and lazy
const ldf = pl.scanCSV('large.csv');
const ctx = pl.SQLContext({ eager_table: df1, lazy_table: ldf });
```

### Response
#### Success Response (200)
* **SQLContext instance**

#### Response Example
None
```

--------------------------------

### Struct Operations on Struct Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Access and manipulate Struct Series, including retrieving field names, getting fields by name, retrieving all fields, and unnesting the struct.

```typescript
s.struct.fieldNames();
s.struct.getFieldByName(field);
s.struct.getAllFields();
s.struct.unnest();
```

--------------------------------

### Sample Series Elements

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Demonstrates how to randomly sample elements from a Series with options for count, fraction, replacement, and seed.

```typescript
sample(options?: { n?: number, fraction?: number, withReplacement?: boolean, seed?: number }): Series
```

--------------------------------

### List Operations on List Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Manipulate List Series by getting lengths, retrieving elements by index, joining elements with a separator, or exploding the list into separate rows.

```typescript
s.list.lengths();
s.list.getByIndex(index);
s.list.join(separator);
s.list.explode();
```

--------------------------------

### format()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Formats a string using expressions as arguments, similar to Python's string formatting. Allows embedding dynamic values into strings.

```APIDOC
## format()

### Description
Format string with expressions using format string syntax.

### Signature
```typescript
format(fmt: string, ...args: Expr[]): Expr
```

### Example
```typescript
pl.format('Value: {}', pl.col('value'));
pl.format('{} - {}, Age: {}', pl.col('first'), pl.col('last'), pl.col('age'));
```
```

--------------------------------

### setVerbose

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/configuration.md

Enable verbose or debug logging output. This method is chainable.

```APIDOC
## setVerbose

### Description
Enable verbose/debug logging output.

### Method
Config.setVerbose(active?: boolean): Config

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
- **active** (boolean) - Optional - Enable verbose logging. Defaults to false.

### Returns
Config
```

--------------------------------

### String Operations on Utf8 Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Perform string manipulations on Utf8 Series, including getting lengths, converting case, checking for patterns, splitting, and replacing substrings.

```typescript
s.str.lengths();
s.str.toUppercase();
s.str.toLowercase();
s.str.contains(pattern);
s.str.split(by);
s.str.replace(pattern, value);
```

--------------------------------

### Get Indices for Sorting Series

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Returns a Series containing the indices that would sort the original Series. Options allow for descending order and placing nulls last.

```typescript
argSort(options?: { descending?: boolean, nullsLast?: boolean }): Series
```

```typescript
argSort(descending?: boolean): Series
```

--------------------------------

### Import Polars in Deno

Source: https://github.com/pola-rs/nodejs-polars/blob/main/README.md

Import the nodejs-polars library in Deno using npm.

```typescript
import pl from "npm:nodejs-polars";
```

--------------------------------

### Get Unique Series Elements

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Returns a new Series containing only the unique elements from the original Series. Duplicates can be optionally removed by keeping the first or last occurrence.

```typescript
unique(options?: { keep?: 'first' | 'last' }): Series
```

--------------------------------

### Display DataFrame in Deno Notebook (v1.37)

Source: https://github.com/pola-rs/nodejs-polars/blob/main/README.md

Use the display function to show a DataFrame in a Deno notebook. Requires fetching data and reading it into a DataFrame.

```typescript
import pl from "npm:nodejs-polars";
import { display } from "https://deno.land/x/display@v1.1.2/mod.ts";

let response = await fetch(
  "https://cdn.jsdelivr.net/npm/world-atlas@1/world/110m.tsv",
);
let data = await response.text();
let df = pl.readCSV(data, { sep: "\t" });
await display(df)
```

--------------------------------

### Get Last N Rows of LazyDataFrame

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Retrieve the last 'n' rows from a LazyDataFrame. Defaults to 5 rows if 'n' is not specified. Useful for examining the tail end of data.

```typescript
tail(n?: number): LazyDataFrame
```

--------------------------------

### head()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/08-utilities.md

Returns an expression that selects the first n values.

```APIDOC
## head()

### Description
Return first n values.

### Method Signature
```typescript
head(n?: number): Expr
```
```

--------------------------------

### Join LazyDataFrame on Different Columns with Join Type

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Example of joining two LazyDataFrames on columns with different names, specifying a 'left' join type. Uses 'leftOn' and 'rightOn' options.

```typescript
ldf1.join(ldf2, { leftOn: 'id1', rightOn: 'id2', how: 'left' });
```

--------------------------------

### head()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/03-lazydataframe.md

Returns the first n rows of a LazyDataFrame. Defaults to the first 5 rows.

```APIDOC
## head()

### Description
Returns the first n rows of a LazyDataFrame. Defaults to the first 5 rows.

### Method Signature
```typescript
head(n?: number): LazyDataFrame
```

### Parameters
- **n** (number) - Optional - Number of rows to return; default 5

### Returns
LazyDataFrame with the first n rows.
```

--------------------------------

### Compile Polars from Source (Fastest Binary)

Source: https://github.com/pola-rs/nodejs-polars/blob/main/README.md

Compile the Polars library from source for the fastest binary, which may result in long compile times. This command builds the TypeScript code and the Rust binary.

```bash
cd nodejs-polars && yarn build && yarn build:ts
```

--------------------------------

### Creating DataFrame with Explicit Schema

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Illustrates creating a DataFrame by explicitly defining the schema for each column.

```typescript
// With explicit schema
const df = pl.DataFrame(
  { a: [1, 2, 3], b: ['x', 'y', 'z'] },
  { schema: { a: pl.Int32, b: pl.String } }
);
```

--------------------------------

### Writing DataFrame to Parquet

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Demonstrates writing a DataFrame to a Parquet file.

```typescript
// Write Parquet
df.writeParquet('output.parquet');
```

--------------------------------

### Grouping and Aggregation

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/00-overview.md

Shows how to perform group-by operations and aggregations on DataFrames, both eagerly and lazily.

```APIDOC
## Grouping and Aggregation

### Description
Shows how to perform group-by operations and aggregations on DataFrames, both eagerly and lazily.

### Grouping and Aggregation

```typescript
// Eager groupby
df.groupBy('group_col').agg(pl.col('value').sum(), pl.col('value').mean());

// Lazy groupby
df.lazy()
  .groupBy('group_col')
  .agg([pl.col('value').sum(), pl.col('value').mean()])
  .collect();
```
```

--------------------------------

### JoinOptions

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Configuration for join operations, allowing specification of join keys, strategy, and handling of duplicate columns.

```APIDOC
## JoinOptions

### Description
Configuration for join operations. This type can be one of `SameNameColumnJoinOptions`, `DifferentNameColumnJoinOptions`, or `CrossJoinOptions`.

### Fields

#### `SameNameColumnJoinOptions`
- **on** (string | string[]) - Required - Join key column(s).
- **how** (JoinType) - Optional - Join strategy; default 'inner'.
- **suffix** (string) - Optional - Suffix for duplicate columns; default '_right'.
- **coalesce** (boolean) - Optional - Merge join columns; default true.
- **validate** (string) - Optional - Validation mode (advanced).

#### `DifferentNameColumnJoinOptions`
- **leftOn** (string | string[]) - Required - Join key column(s) on the left DataFrame.
- **rightOn** (string | string[]) - Required - Join key column(s) on the right DataFrame.
- **how** (JoinType) - Optional - Join strategy; default 'inner'.
- **suffix** (string) - Optional - Suffix for duplicate columns; default '_right'.
- **coalesce** (boolean) - Optional - Merge join columns; default true.
- **validate** (string) - Optional - Validation mode (advanced).

#### `CrossJoinOptions`
- **how** ('cross') - Required - Must be 'cross' for a cross join.
- **suffix** (string) - Optional - Suffix for duplicate columns; default '_right'.
- **coalesce** (boolean) - Optional - Merge join columns; default true.
- **validate** (string) - Optional - Validation mode (advanced).

**JoinType**: 'left' | 'inner' | 'full' | 'semi' | 'anti' | 'cross'
```

--------------------------------

### Execute SQL Query Eagerly

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/07-sql.md

Execute a SQL query and immediately return the results as a DataFrame. Use this when you need the data right away.

```typescript
const ctx = pl.SQLContext({ films: df });

// Execute eagerly (immediate result)
const result = ctx.execute('SELECT * FROM films WHERE year > 1990', { eager: true });
```

--------------------------------

### ReadParquetOptions

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Configuration options for reading Parquet files. Allows specifying columns, number of rows, parallelization strategy, and adding a row count column.

```APIDOC
## ReadParquetOptions

### Description
Options for reading Parquet files. You can select specific columns, limit the number of rows, define the parallelization strategy, and optionally add a row count column.

### Fields
- **columns** (string[] | number[]) - Optional - Columns to read.
- **numRows** (number) - Optional - Maximum number of rows to read.
- **parallel** (string) - Optional - Parallelization strategy ('auto', 'columns', 'row_groups', 'none'). Defaults to 'auto'.
- **rowCount** (RowCount) - Optional - Configuration to add a row count column.
```

--------------------------------

### groupBy()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/01-dataframe.md

Initiate a groupby operation for subsequent aggregation. Can group by multiple columns.

```APIDOC
## groupBy()

### Description
Start a groupby operation for aggregation.

### Method
```typescript
groupBy(...columns: (string | Expr)[]): GroupBy
groupBy(columns: (string | Expr)[]): GroupBy
```

### Parameters
#### Path Parameters
- **columns** ((string | Expr)[]) - Required - Column names to group by

### Response
#### Success Response (200)
- **GroupBy** - GroupBy object with `.agg()` method.

### Request Example
```typescript
df.groupBy('group').agg(pl.col('value').sum());
df.groupBy('a', 'b').agg([pl.col('c').mean(), pl.col('d').max()]);
```
```

--------------------------------

### head()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/01-dataframe.md

Retrieve the first 'n' rows of the DataFrame.

```APIDOC
## head()

### Description
Return first n rows (default 5).

### Method
```typescript
head(n?: number): DataFrame
```

### Parameters
#### Path Parameters
- **n** (number) - Optional - Number of rows to retrieve; default 5.
```

--------------------------------

### describe()

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/01-dataframe.md

Compute and return summary statistics for numeric columns in the DataFrame.

```APIDOC
## describe()

### Description
Compute summary statistics (mean, std, min, max, median) for numeric columns.

### Method
```typescript
describe(): DataFrame
```

### Response
#### Success Response (200)
- **DataFrame** - DataFrame with statistics.
```

--------------------------------

### Utility Methods

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/04-expr.md

General utility methods for expressions.

```APIDOC
## Utility Methods

### abs(): Expr

Calculates the absolute value of the expression.

**Returns**: Expr.

### sign(): Expr

Returns the sign of the value (-1, 0, or 1).

### sqrt(): Expr

Calculates the square root of the expression.

### pow(exponent: number | Expr): Expr

Raises the expression to the power of the given exponent.

### log(base?: number): Expr

Calculates the logarithm of the expression.

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| base | number | No | Logarithm base; default e |

### log10(): Expr

Calculates the base-10 logarithm of the expression.

### exp(): Expr

Calculates the exponential of the expression (e^x).

### sin(): Expr

Calculates the sine of the expression.

### cos(): Expr

Calculates the cosine of the expression.

### tan(): Expr

Calculates the tangent of the expression.
```

--------------------------------

### Convert Series to Array

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/api-reference/02-series.md

Shows how to convert a Series into a standard JavaScript array.

```typescript
const arr = s.toArray(); // [1, 2, 3]
```

--------------------------------

### ScanParquetOptions

Source: https://github.com/pola-rs/nodejs-polars/blob/main/_autodocs/types.md

Options for lazily scanning Parquet files. Includes settings for row limits, indexing, caching, parallelization, partitioning, and cloud storage.

```APIDOC
## ScanParquetOptions

### Description
Options for lazily scanning Parquet files. This allows for efficient reading of large datasets by deferring computation. You can control row limits, caching, parallelization, and Hive partitioning.

### Fields
- **nRows** (number) - Optional - Maximum number of rows to scan.
- **rowIndexName** (string) - Optional - Name for the row index column.
- **rowIndexOffset** (number) - Optional - Offset for the row index.
- **cache** (boolean) - Optional - Whether to cache the scanned data.
- **parallel** (string) - Optional - Parallelization strategy ('auto', 'columns', 'row_groups', 'none').
- **glob** (boolean) - Optional - Whether to use glob patterns for file paths.
- **hivePartitioning** (boolean) - Optional - Whether to enable Hive partitioning.
- **hiveSchema** (unknown) - Optional - Schema for Hive partitioning.
- **tryParseHiveDates** (boolean) - Optional - Whether to try parsing Hive dates.
- **rechunk** (boolean) - Optional - Whether to rechunk the data.
- **lowMemory** (boolean) - Optional - Whether to use low memory mode.
- **useStatistics** (boolean) - Optional - Whether to use statistics for optimization.
- **cloudOptions** (Record<string, string>) - Optional - Cloud storage options.
- **retries** (number) - Optional - Number of retries for cloud operations.
- **includeFilePaths** (string) - Optional - Path to include files.
- **allowMissingColumns** (boolean) - Optional - Whether to allow missing columns.
```