larray.from_series

larray.from_series(s, sort_rows=False, fill_value=nan, meta=None, copy=True, **kwargs) → Array[source]

Convert Pandas Series into Array.

Parameters:

sPandas Series: Input Pandas Series.
sort_rowsbool, optional: Whether to sort the rows alphabetically. Defaults to False.
fill_valuescalar, optional: Value used to fill cells corresponding to label combinations which are not present in the input Series. Defaults to NaN.
metalist of pairs or dict or Metadata, optional: Metadata (title, description, author, creation_date, …) associated with the array. Keys must be strings. Values must be of type string, int, float, date, time or datetime.
copybool, optional: Whether to copy the data from the Series. Defaults to True. copy=False does not guarantee that no copy will be made, only that a copy is only done when necessary. If the resulting array shares the same data buffer than the original series, it will be read-only.

Returns:

Array

See also

Array.to_series

Examples

>>> from larray import ndtest
>>> s = ndtest((2, 2, 2), dtype=float).to_series()
>>> s
a   b   c
a0  b0  c0    0.0
        c1    1.0
    b1  c0    2.0
        c1    3.0
a1  b0  c0    4.0
        c1    5.0
    b1  c0    6.0
        c1    7.0
dtype: float64
>>> from_series(s)
 a  b\c   c0   c1
a0   b0  0.0  1.0
a0   b1  2.0  3.0
a1   b0  4.0  5.0
a1   b1  6.0  7.0