into

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ columnA into"columnB" }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ "columnA" into"columnB" }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ col(0) into"columnB" }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ columnA intocolumnB }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ columnA intoType::columnB }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ "columnA" intocolumnB }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ "columnA" intoType::columnB }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ Type::columnA into"columnB" }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ Type::columnA intocolumnB }

Parameters

Rename: named / into

Renaming a column in the ColumnsSelectionDsl is done by calling the infix functions named or into. They behave exactly the same, so it's up to contextual preference which one to use. Any combination of Access APIs can be used to specify the column to rename and which name should be used instead.

For more information: See Rename: named / into on the documentation website.

Check out: Grammar

For Example:

df.select{ name named"Full Name" }

df.select{ expr{ 0 } into"zeroes" }

df.select{ "colA" namedType::colB }

Example for this overload:

df.select{ Type::columnA intoType::columnB }

Parameters