minBy

Returns the first element of this DataColumn for which the given selector returns the minimum value.

The result of the expression is considered the 'input' of this operation.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Throws a NoSuchElementException when there is nothing left to compare, for instance when the input is empty or contains only null (or, if skipNaN is true, only null and NaN) values.

Don't confuse minBy with minOf, which returns the minimum selector value itself instead of the element it belongs to.

See also:

• minByOrNull — returns null instead of throwing for a column with nothing to compare.

• maxBy — the mirror operation.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// The shortest first name in the "name"/"firstName" column
df.name.firstName.minBy { it.length }

Parameters

Throws

Returns the first row of this DataFrame for which the given expression returns the minimum value.

The given RowExpression is evaluated for each row of the dataframe. The row is both the receiver and the argument (it) of the expression, so the values in it can be accessed directly.

For more information: See RowExpression on the documentation website.

The result of the expression is considered the 'input' of this operation.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Throws a NoSuchElementException when there is nothing left to compare, for instance when the input is empty or contains only null (or, if skipNaN is true, only null and NaN) values.

Don't confuse minBy with minOf, which returns the minimum expression value itself instead of the row it belongs to.

See also:

• minByOrNull — returns null instead of throwing when there's nothing to compare.

• maxBy — the mirror operation.

• sortBy — orders all rows instead of taking just the smallest one.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// The row with the smallest "age"
df.minBy { age }
// The row with the smallest weight-to-age ratio
df.minBy { (weight ?: 0) / age }

Parameters

Throws

Returns the first row of this DataFrame that has the smallest value in the column with the given name.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Throws a NoSuchElementException when there is nothing left to compare, for instance when the input is empty or contains only null (or, if skipNaN is true, only null and NaN) values.

Don't confuse minBy with minOf, which returns the minimum value a row expression returns itself, instead of the row it belongs to.

See also:

• minByOrNull — returns null instead of throwing when there's nothing to compare.

• min — returns the smallest value itself instead of the row it belongs to.

• maxBy — the mirror operation.

• sortBy — orders all rows instead of taking just the smallest one.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// The row with the smallest "age"
df.minBy("age")

Parameters

Throws

Reduces each group of this GroupBy to the first row for which the given rowExpression returns the minimum value.

This operation does not produce a result right away. Instead, it returns a ReducedGroupBy — an intermediate step which can be finished with concat (to get a DataFrame with the selected rows), values, or into.

See GroupBy reducing for more details.

The given RowExpression is evaluated for each row of the dataframe. The row is both the receiver and the argument (it) of the expression, so the values in it can be accessed directly.

For more information: See RowExpression on the documentation website.

The result of the expression is considered the 'input' of this operation.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Groups that have no values to compare cannot select a row, and produce null values instead.

Don't confuse minBy with minOf, which returns the minimum value itself instead of the row it belongs to.

See also:

• maxBy — the mirror operation.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// For each city, the full row of the person with the smallest "age"
df.groupBy { city }.minBy { age }.concat()

Parameters

Reduces each group of this GroupBy to the first row that has the smallest value in the column with the given name.

This operation does not produce a result right away. Instead, it returns a ReducedGroupBy — an intermediate step which can be finished with concat (to get a DataFrame with the selected rows), values, or into.

See GroupBy reducing for more details.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Groups that have no values to compare cannot select a row, and produce null values instead.

Don't confuse minBy with minOf, which returns the minimum value a row expression returns itself, instead of the row it belongs to.

See also:

• min — the minimum value itself instead of the row it belongs to.

• maxBy — the mirror operation.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// For each city, the full row of the person with the smallest "age"
df.groupBy { city }.minBy("age").concat()

Parameters

Reduces this Pivot by taking from each group the first row for which the given rowExpression returns the minimum value.

The given RowExpression is evaluated for each row of the dataframe. The row is both the receiver and the argument (it) of the expression, so the values in it can be accessed directly.

For more information: See RowExpression on the documentation website.

The result of the expression is considered the 'input' of this operation.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Groups that have no values to compare cannot select a row, and produce null values instead.

This operation does not produce a result right away. Instead, it returns a ReducedPivot — an intermediate step which can be finished with values or with.

Don't confuse minBy with minOf, which returns the minimum value the expression returns itself, instead of the row.

Check out the Pivot Grammar.

See also:

• maxBy — the mirror operation.

• Pivot reducing — all other ways to reduce a Pivot.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// For each city, the "name" of the person with the smallest weight-to-age ratio
df.pivot { city }.minBy { (weight ?: 0) / age }.with { name }

Parameters

Reduces this Pivot by taking from each group the first row that has the smallest value in the given column.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Groups that have no values to compare cannot select a row, and produce null values instead.

This operation does not produce a result right away. Instead, it returns a ReducedPivot — an intermediate step which can be finished with values or with.

Don't confuse minBy with minOf, which returns the minimum value a row expression returns itself, instead of the row.

Check out the Pivot Grammar.

See also:

• min{ columns } — the minimum value itself, instead of the row.

• maxBy — the mirror operation.

• Pivot reducing — all other ways to reduce a Pivot.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// For each city, the "name" of the youngest person
df.pivot { city }.minBy("age").with { name }

Parameters

Reduces this PivotGroupBy by taking from each group the first row for which the given rowExpression returns the minimum value.

The given RowExpression is evaluated for each row of the dataframe. The row is both the receiver and the argument (it) of the expression, so the values in it can be accessed directly.

For more information: See RowExpression on the documentation website.

The result of the expression is considered the 'input' of this operation.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Groups that have no values to compare cannot select a row, and produce null values instead.

This operation does not produce a result right away. Instead, it returns a ReducedPivotGroupBy — an intermediate step which can be finished with values or with.

Don't confuse minBy with minOf, which returns the minimum value the expression returns itself, instead of the row.

Check out the PivotGroupBy Grammar.

See also:

• maxBy — the mirror operation.

• PivotGroupBy reducing — all other ways to reduce a PivotGroupBy.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// Per city and last name, the "firstName" of the person with the smallest weight-to-age ratio
df.pivot { city }.groupBy { name.lastName }.minBy { (weight ?: 0) / age }.with { name.firstName }

Parameters

Reduces this PivotGroupBy by taking from each group the first row that has the smallest value in the given column.

Only self-comparable values are supported: values of a type T : Comparable<T> that are mutually comparable (like strings, primitive numbers, or dates). This includes all primitive number types, but no mix of different number types, which would result in a ClassCastException.

null values in the input are always ignored.

If the input contains NaN values, the result will be NaN, unless skipNaN is set to true.

Groups that have no values to compare cannot select a row, and produce null values instead.

This operation does not produce a result right away. Instead, it returns a ReducedPivotGroupBy — an intermediate step which can be finished with values or with.

Don't confuse minBy with minOf, which returns the minimum value a row expression returns itself, instead of the row.

Check out the PivotGroupBy Grammar.

See also:

• min{ columns } — the minimum value itself, instead of the row.

• maxBy — the mirror operation.

• PivotGroupBy reducing — all other ways to reduce a PivotGroupBy.

• The Min Operation — an overview of all min modes.

For more information: See minBy on the documentation website.

Example

// Per city and last name, the "firstName" of the youngest person
df.pivot { city }.groupBy { name.lastName }.minBy("age").with { name.firstName }

Parameters