tech.tablesaw.io.csv

Class CsvReader

java.lang.Object

tech.tablesaw.io.csv.CsvReader

@Immutable
public class CsvReader
extends Object

Constructor Summary

Constructors

Constructor and Description
CsvReader() Constructs a CsvReader
CsvReader(List<ColumnType> typeDetectionList) Constructs a CsvReader with the given list of ColumnTypes These are the only types that the CsvReader can detect and parse

Method Summary

Modifier and Type	Method and Description
ColumnType[]	detectColumnTypes(InputStream stream, CsvReadOptions options) Estimates and returns the type for each column in the delimited text file file
List<ColumnType>	getTypeArray() Returns the list of types that specifies the order in which types are tested in the detection algorithm.
Table	headerOnly(ColumnType[] types, boolean header, CsvReadOptions options, File file) Returns a Table constructed from a CSV File with the given file name
String	printColumnTypes(String csvFileName, boolean header, char delimiter, Locale locale) Returns a string representation of the column types in file csvFilename, as determined by the type-detection algorithm
Table	read(CsvReadOptions options)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

CsvReader

public CsvReader()

Constructs a CsvReader

CsvReader

public CsvReader(List<ColumnType> typeDetectionList)

Constructs a CsvReader with the given list of ColumnTypes These are the only types that the CsvReader can detect and parse

Method Detail

read

public Table read(CsvReadOptions options)
           throws IOException

Throws:

IOException

headerOnly

public Table headerOnly(ColumnType[] types,
                        boolean header,
                        CsvReadOptions options,
                        File file)
                 throws IOException

Returns a Table constructed from a CSV File with the given file name

The @code{fileName} is used as the initial table name for the new table

Parameters:

types - An array of the types of columns in the file, in the order they appear

header - Is the first row in the file a header?

options - Sets the format for and instructions for parsing

file - The fully specified file name. It is used to provide a default name for the table

Returns:

A Relation containing the data in the csv file.

Throws:

IOException - if file cannot be read

printColumnTypes

public String printColumnTypes(String csvFileName,
                               boolean header,
                               char delimiter,
                               Locale locale)
                        throws IOException

Returns a string representation of the column types in file csvFilename, as determined by the type-detection algorithm

This method is intended to help analysts quickly fix any erroneous types, by printing out the types in a format such that they can be edited to correct any mistakes, and used in an array literal

For example:

LOCAL_DATE, // 0 date SHORT, // 1 approval STRING, // 2 who

Note that the types are array separated, and that the index position and the column name are printed such that they would be interpreted as comments if you paste the output into an array:

Throws:

IOException - if file cannot be read

detectColumnTypes

public ColumnType[] detectColumnTypes(InputStream stream,
                                      CsvReadOptions options)
                               throws IOException

Estimates and returns the type for each column in the delimited text file file

The type is determined by checking a sample of the data in the file. Because only a sample of the data is checked, the types may be incorrect. If that is the case a Parse Exception will be thrown.

The method printColumnTypes() can be used to print a list of the detected columns that can be corrected and used to explicitly specify the correct column types.

Throws:

IOException

getTypeArray

public List<ColumnType> getTypeArray()

Returns the list of types that specifies the order in which types are tested in the detection algorithm.