datatable.Frame.to_numpy()

Convert frame into a 2D numpy array, optionally forcing it into the specified type.

In a limited set of circumstances the returned numpy array will be created as a data view, avoiding copying the data. This happens if all of these conditions are met:

  • the frame has only one column, which is not virtual;

  • the column’s type is not string;

  • the type argument was not used.

In all other cases the returned numpy array will have a copy of the frame’s data. If the frame has multiple columns of different stypes, then the values will be upcasted into the smallest common stype.

If the frame has any NA values, then the returned numpy array will be an instance of numpy.ma.masked_array.

Parameters

type
Type | <type-like>

Cast frame into this type before converting it into a numpy array. Here “type-like” can be any value that is acceptable to the dt.Type constructor.

column
int

Convert a single column instead of the whole frame. This column index can be negative, indicating columns counted from the end of the frame.

c_contiguous
bool

If False, the resulting numpy array will have the same memory layout as the datatable frame, i.e. column-major or C_CONTIGUOUS. If True, the numpy array will be row-major or F_CONTIGUOUS.

return
numpy.ndarray | numpy.ma.core.MaskedArray

The returned array will be 2-dimensional with the same .shape as the original frame. However, if the option column was used, then the returned array will be 1-dimensional with the length of .nrows.

A masked array is returned if the frame contains NA values but the corresponding numpy array does not support NAs.

except
ImportError

If the numpy module is not installed.