Package | Description |
---|---|
tech.tablesaw.aggregate | |
tech.tablesaw.api | |
tech.tablesaw.columns.strings | |
tech.tablesaw.table |
Modifier and Type | Method and Description |
---|---|
Table |
Summarizer.by(CategoricalColumn<?>... columns) |
static Table |
CrossTab.columnPercents(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2)
Returns a table containing the column percents made from a source table, after first
calculating the counts cross-tabulated from the given columns
|
static Table |
CrossTab.columnPercents(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2)
Returns a table containing the column percents made from a source table, after first
calculating the counts cross-tabulated from the given columns
|
static Table |
CrossTab.counts(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2)
Returns a table containing two-dimensional cross-tabulated counts for each combination of
values in
column1 and column2 |
static Table |
CrossTab.counts(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2)
Returns a table containing two-dimensional cross-tabulated counts for each combination of
values in
column1 and column2 |
Summarizer |
Summarizer.groupBy(CategoricalColumn<?>... columns) |
static Table |
PivotTable.pivot(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2,
NumericColumn<?> values,
AggregateFunction<?,?> aggregateFunction) |
static Table |
PivotTable.pivot(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2,
NumericColumn<?> values,
AggregateFunction<?,?> aggregateFunction) |
static Table |
CrossTab.rowPercents(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2)
Returns a table containing the row percents made from a source table, after first calculating
the counts cross-tabulated from the given columns
|
static Table |
CrossTab.rowPercents(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2)
Returns a table containing the row percents made from a source table, after first calculating
the counts cross-tabulated from the given columns
|
static Table |
CrossTab.tablePercents(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2)
Returns a table containing the table percents made from a source table, after first calculating
the counts cross-tabulated from the given columns
|
static Table |
CrossTab.tablePercents(Table table,
CategoricalColumn<?> column1,
CategoricalColumn<?> column2)
Returns a table containing the table percents made from a source table, after first calculating
the counts cross-tabulated from the given columns
|
Modifier and Type | Class and Description |
---|---|
class |
BooleanColumn
A column in a base table that contains float values
|
class |
DateColumn
A column in a base table that contains float values
|
class |
DateTimeColumn
A column in a table that contains long-integer encoded (packed) local date-time values
|
class |
InstantColumn
A column in a table that contains long-integer encoded (packed) local date-time values
|
class |
IntColumn |
class |
LongColumn |
class |
ShortColumn |
class |
StringColumn
A column that contains String values.
|
class |
TextColumn
A column that contains String values.
|
class |
TimeColumn
A column in a base table that contains float values
|
Modifier and Type | Method and Description |
---|---|
List<CategoricalColumn<?>> |
Table.categoricalColumns(String... columnNames)
Returns only the columns whose names are given in the input array
|
Modifier and Type | Method and Description |
---|---|
Table |
Table.countBy(CategoricalColumn<?> groupingColumn)
Returns a table containing two columns, the grouping column, and a column named "Count" that
contains the counts for each grouping column value
|
Table |
Table.pivot(CategoricalColumn<?> column1,
CategoricalColumn<?> column2,
NumericColumn<?> column3,
AggregateFunction<?,?> aggregateFunction)
Returns a pivot on this table, where: The first column contains unique values from the index
column1 There are n additional columns, one for each unique value in column2 The values in each
of the cells in these new columns are the result of applying the given AggregateFunction to the
data in column3, grouped by the values of column1 and column2
|
Table |
Table.pivot(CategoricalColumn<?> column1,
CategoricalColumn<?> column2,
NumericColumn<?> column3,
AggregateFunction<?,?> aggregateFunction)
Returns a pivot on this table, where: The first column contains unique values from the index
column1 There are n additional columns, one for each unique value in column2 The values in each
of the cells in these new columns are the result of applying the given AggregateFunction to the
data in column3, grouped by the values of column1 and column2
|
TableSliceGroup |
Table.splitOn(CategoricalColumn<?>... columns)
Returns a non-overlapping and exhaustive collection of "slices" over this table.
|
Table[] |
Table.stratifiedSampleSplit(CategoricalColumn<?> column,
double table1Proportion)
Splits the table into two stratified samples, this uses the specified column to divide the
table into groups, randomly assigning records to each according to the proportion given in
trainingProportion.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractStringColumn<C extends AbstractColumn<C,String>>
Abstract super class for Text like columns.
|
Modifier and Type | Method and Description |
---|---|
CategoricalColumn<?> |
Relation.categoricalColumn(int columnNumber) |
CategoricalColumn<?> |
Relation.categoricalColumn(String columnName) |
Modifier and Type | Method and Description |
---|---|
List<CategoricalColumn<?>> |
Relation.categoricalColumns(String... columnName)
Returns the columns whose names are given in the input array
|
Modifier and Type | Method and Description |
---|---|
static StandardTableSliceGroup |
StandardTableSliceGroup.create(Table original,
CategoricalColumn<?>... columns)
Returns a viewGroup splitting the original table on the given columns.
|
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