Struct DataProfiler 

pub struct DataProfiler { /* private fields */ }

Data profiler

Implementations

impl DataProfiler

pub fn infer_data_type(&self, data: &[String]) -> DataType

Infer data type from sample values

pub fn get_value_frequencies(&self, data: &[String]) -> Vec<ValueFrequency>

Get value frequencies

pub fn calculate_length_stats(&self, data: &[String]) -> LengthStats

Calculate length statistics

pub fn calculate_numeric_stats(&self, data: &[String]) -> Option<NumericStats>

Calculate numeric statistics

pub fn calculate_date_stats(&self, data: &[String]) -> Option<DateStats>

Calculate date statistics

pub fn calculate_text_stats(&self, data: &[String]) -> TextStats

Calculate text statistics

impl DataProfiler

pub fn new() -> Self

Create a new profiler with options

pub fn with_max_distinct_values(self, max: usize) -> Self

Set maximum distinct values to track

pub fn with_sample_size(self, size: usize) -> Self

Set sample size for large datasets

pub fn profile( &self, data: &[Vec<String>], file_path: &str, ) -> Result<DataProfile>

Profile data from rows

impl DataProfiler

pub fn calculate_column_quality_score( &self, null_percentage: f64, unique_percentage: f64, data_type: &DataType, length_stats: Option<&LengthStats>, numeric_stats: Option<&NumericStats>, ) -> f64

Calculate column quality score

pub fn calculate_overall_quality_score( &self, columns: &[ColumnProfile], null_percentage: f64, duplicate_percentage: f64, ) -> f64

Calculate overall quality score

pub fn generate_recommendations( &self, columns: &[ColumnProfile], null_percentage: f64, duplicate_percentage: f64, ) -> Vec<String>

Generate data quality recommendations

pub fn generate_report(&self, profile: &DataProfile) -> String

Generate a human-readable profile report

Trait Implementations

impl Default for DataProfiler

fn default() -> Self

Returns the “default value” for a type.