KSLCore/ksl.utilities.io.tabularfiles/TabularInputFile

TabularInputFile

class TabularInputFile : TabularFile(source)

An abstraction for reading rows of tabular data. Columns of the tabular data can be of numeric or text. Using this subclass of TabularFile users can read rows of data. The user is responsible for iterating rows with data of the appropriate type for the column and reading the row into their program.

Use the static methods of TabularFile to create and define the columns of the file. Use the methods of this class to read rows.

Constructors

TabularInputFile

constructor(path: Path)

Types

Companion

object Companion

RowIterator

inner class RowIterator @JvmOverloads constructor(startingRowNum: Long = 1) : Iterator<RowGetterIfc>

Properties

rowBufferSize

var rowBufferSize: Int

totalNumberRows

val totalNumberRows: Long

Functions

asDataFrame

open override fun asDataFrame(): AnyFrame

Converts the columns and rows to a Dataframe.

fun close()

Remember to close the file after all processing

exportToCSV

@JvmOverloads

fun exportToCSV(out: PrintWriter, header: Boolean = true)

Writes the data in the file to a CSV file

exportToExcelWorkbook

fun exportToExcelWorkbook(wbName: String, wbDirectory: Path)

This is not optimized for large files and may have memory and performance issues.

fetchNumericColumn

@JvmOverloads

fun fetchNumericColumn(columnNum: Int, maxRows: Int = 0, removeMissing: Boolean = false): DoubleArray

@JvmOverloads

fun fetchNumericColumn(columnName: String, maxRows: Int = 0, removeMissing: Boolean = false): DoubleArray

Obviously, there are memory issues if there are a lot of rows.

fetchRow

fun fetchRow(rowNum: Long): RowGetterIfc

Returns the row. If the provided row number is larger than the number of rows in the file then an exception is thrown. Use fetchRow() if you do not check the number of rows.

fetchRows

fun fetchRows(minRowNum: Long, maxRowNum: Long): List<RowGetterIfc>

Returns the rows between minRowNum and maxRowNum, inclusive. Since there may be memory implications when using this method, please use it wisely. In fact, use the provided iterator instead.

fetchTextColumn

@JvmOverloads

fun fetchTextColumn(columnNum: Int, maxRows: Int = 0, removeMissing: Boolean = false): Array<String?>

@JvmOverloads

fun fetchTextColumn(columnName: String, maxRows: Int = 0, removeMissing: Boolean = false): Array<String?>

Obviously, there are memory issues if there are a lot of rows.

iterator

@JvmOverloads

fun iterator(startingRow: Long = 1): TabularInputFile.RowIterator

numericColumns

@JvmOverloads

fun numericColumns(maxRows: Int = 0, removeMissing: Boolean = false): Map<String, DoubleArray>

printAsText

@JvmOverloads

fun printAsText(minRowNum: Long = 1, maxRowNum: Long = minRowNum + 10)

This is not optimized for large files and may have memory and performance issues.

textColumns

@JvmOverloads

fun textColumns(maxRows: Int = 0, removeMissing: Boolean = false): Map<String, Array<String?>>

toReport

fun TabularInputFile.toReport(title: String = path.fileName.toString(), maxRows: Int = 500, confidenceLevel: Double = 0.95, detail: Boolean = false, showPlots: Boolean = true, block: ReportBuilder.() -> Unit = { tabularInputFileResults( file = this@toReport, maxRows = maxRows, confidenceLevel = confidenceLevel, detail = detail, showPlots = showPlots ) }): ReportNode.Document

Builds a ReportNode.Document for this TabularInputFile whose default content is the full standard report (tabularInputFileResults): column schema, compact statistics table for numeric columns, text-column summary, and per-column drill-down sections with histograms and value-frequency tables.

writeAsText

@JvmOverloads

fun writeAsText(out: PrintWriter, minRowNum: Long = 1, maxRowNum: Long = totalNumberRows)

This is not optimized for large files and may have memory and performance issues.

TabularInputFile

See also

Constructors

Types

Properties

Functions