DataFrame class abstract

An in-memory storage to keep data in column-like manner with human readable headers with possibility to convert the data to pure numeric representation.

Constructors

DataFrame(Iterable<Iterable> data, {bool headerExists = true, Iterable<String> header = const [], String autoHeaderPrefix = defaultHeaderPrefix, Iterable<int> columns = const [], Iterable<String> columnNames = const []})

Creates a dataframe from the non-typed data that is represented as two-dimensional array, where each element is a row of table-like data. The first element of the two-dimensional array may be a header of a dataset:

factory

DataFrame.fromJson(Map<String, dynamic> json)

factory

DataFrame.fromMatrix(Matrix matrix, {Iterable<String> header = const [], String autoHeaderPrefix = defaultHeaderPrefix, Iterable<int> columns = const [], Iterable<int> discreteColumns = const [], Iterable<String> discreteColumnNames = const []})

Create a DataFrame instance from a instance of Matrix

factory

DataFrame.fromRawCsv(String rawContent, {String fieldDelimiter = defaultFieldDelimiter, String textDelimiter = defaultTextDelimiter, String? textEndDelimiter, String eol = '\n', bool headerExists = true, Iterable<String> header = const [], String autoHeaderPrefix = defaultHeaderPrefix, Iterable<int> columns = const [], Iterable<String> columnNames = const []})

Creates a dataframe instance from stringified csv rawContent.

factory

DataFrame.fromSeries(Iterable<Series> series)

Create a DataFrame instance from a collection of Series

factory

Properties

hashCode → int

The hash code for this object.

no setter, inherited

header → Iterable<String>

Returns a collection of names of all series (like a table header)

no setter

rows → Iterable<Iterable>

Returns a collection of all data item rows of the DataFrame's source data

no setter

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

series → Iterable<Series>

Returns a lazy series (columns) collection of the DataFrame.

no setter

shape → List<int>

Returns a list of two integers representing the shape of the dataframe: the first integer is a number of rows, the second integer - a number of columns

no setter

Methods

addSeries(Series series) → DataFrame

Returns a dataframe with a new series added to the end of this dataframe's series collection

dropSeries({Iterable<int> indices, Iterable<String> names}) → DataFrame

Returns a new DataFrame without specified series

map<T, R>(R mapper(T value)) → DataFrame

Returns a new DataFrame with modified data according to the mapper function

mapSeries<T, R>(R mapper(T value), {int? index, String? name}) → DataFrame

Returns a new DataFrame with a modified series according to the mapper function

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

sampleFromRows(Iterable<int> indices) → DataFrame

Returns a dataframe, sampled from rows that are obtained from the rows indices

sampleFromSeries({Iterable<int> indices, Iterable<String> names}) → DataFrame

Returns a dataframe, sampled from series that are obtained from the series indices or series names.

saveAsJson(String fileName, {bool rewrite = false}) → Future<File>

inherited

shuffle({int seed}) → DataFrame

Returns a new DataFrame with shuffled rows of this DataFrame

toJson() → Map<String, dynamic>

inherited

toMatrix([DType dtype]) → Matrix

Converts the DataFrame into Matrix.

toString({int maxRows = 10, int maxCols = 7}) → String

Returns a nicely formatted string to inspect the data of the DataFrame as the example below shows

override

Operators

operator ==(Object other) → bool

The equality operator.

inherited

operator [](Object key) → Series

Returns a specific Series by a key.