Detail: Frame: Attribute

Overview: Frame: Attribute

Frame.STATIC = True
>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.STATIC
True
Frame.T

Transpose. Return a Frame with index as columns and vice versa.

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.T
<Frame: x>
<Index>    0          1          2          3          <int64>
<Index>
a          10         2          8          3
b          False      True       True       False
c          1517-01-01 1517-04-01 1517-12-31 1517-06-30
<<U1>      <object>   <object>   <object>   <object>
Frame.columns

The IndexBase instance assigned for column labels.

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.columns
<Index>
a
b
c
<<U1>
Frame.dtypes

Return a Series of dytpes for each realizable column.

Returns

static_frame.Series

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.dtypes
<Series: x>
<Index>
a           int64
b           bool
c           datetime64[D]
<<U1>       <object>
Frame.index

The IndexBase instance assigned for row labels.

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.index
<Index>
0
1
2
3
<int64>
Frame.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

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.memory
        L    Lu    LM   LMu   LMD  LMDu  R     Ru    RM   RMu   RMD  RMDu
Name    50   B     50   B     50   B     50    B     50   B     50   B
Index   208  B     224  B     112  B     8.3   KB    256  B     144  B
Columns 756  B     788  B     564  B     8.83  KB    812  B     588  B
Blocks  1.4  KB    1.45 KB    1.12 KB    1.4   KB    1.45 KB    1.12 KB
Total   2.42 KB    2.52 KB    1.86 KB    10.52 KB    2.57 KB    1.92 KB
Frame.mloc

The memory locations, represented as an array of integers, of the underlying NumPy arrays.

Frame.name

A hashable label attached to this container.

Returns

Hashable

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.name
x
Frame.nbytes

Return the total bytes of the underlying NumPy array.

Returns

int

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.nbytes
68
Frame.ndim

Return the number of dimensions, which for a Frame is always 2.

Returns

int

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.ndim
2
Frame.shape

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

Returns

tp.Tuple[int, int]

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.shape
(4, 3)
Frame.size

Return the size of the underlying NumPy array.

Returns

int

>>> f = sf.Frame.from_fields(((10, 2, 8, 3), (False, True, True, False), ('1517-01-01', '1517-04-01', '1517-12-31', '1517-06-30')), columns=('a', 'b', 'c'), dtypes=dict(c=np.datetime64), name='x')
>>> f.size
12

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