Detail: Series: Attribute

Overview: Series: Attribute

Series.STATIC = True
>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.STATIC
True
Series.T

Transpose. For a 1D immutable container, this returns a reference to self.

Returns:

Series

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.T
<Series>
<Index>
a        10
b        2
c        8
<<U1>    <int64>
Series.dtype

Return the dtype of the underlying NumPy array.

Returns:

numpy.dtype

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.dtype
int64
Series.index

The index instance assigned to this container.

Returns:

static_frame.Index

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.index
<Index>
a
b
c
<<U1>
Series.memory

Return a MemoryDisplay, providing the size in memory of this object. For compound containers, component sizes will also be provided. Size can be interpreted through six combinations of three configurations:

L: Local: memory ignoring referenced array data provided via views. LM: Local Materialized: memory where arrays that are locally owned report their byte payload LMD: Local Materialized Data: locally owned memory of arrays byte payloads, excluding all other components

R: Referenced: memory including referenced array data provided via views RM: Referenced Materialized: memory where arrays that are locally owned or referenced report their byte payload RMD: Referenced Materialized Data: localy owned and referenced array byte payloads, excluding all other components

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.memory
       L   Lu    LM   LMu   LMD LMDu  R    Ru    RM   RMu   RMD RMDu
Name   16  B     16   B     16  B     16   B     16   B     16  B
Index  800 B     832  B     576 B     8.89 KB    856  B     600 B
Values 136 B     152  B     24  B     136  B     152  B     24  B
Total  992 B     1.02 KB    656 B     9.08 KB    1.04 KB    680 B
Series.mloc

The memory location, represented as an integer, of the underlying NumPy array.

Series.name

A hashable label attached to this container.

Returns:

Hashable

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.name
Series.nbytes

Return the total bytes of the underlying NumPy array.

Returns:

int

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.nbytes
24
Series.ndim

Return the number of dimensions, which for a Series is always 1.

Returns:

int

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.ndim
1
Series.shape

Return a tuple describing the shape of the underlying NumPy array.

Returns:

Tuple[int]

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.shape
(3,)
Series.size

Return the size of the underlying NumPy array.

Returns:

int

>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c'))
>>> s.size
3

Series: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Assignment | Selector | Iterator | Operator Binary | Operator Unary | Accessor Values | Accessor Datetime | Accessor String | Accessor Fill Value | Accessor Regular Expression | Accessor Hashlib | Accessor Type Clinic