Properties

Summary

property class parent truncated documentation
T WeightedSeries return the transpose, which is by definition self
_can_hold_na WeightedSeries  
_constructor WeightedSeries  
_constructor_expanddim WeightedSeries  
_constructor_sliced WeightedSeries Used when a manipulation result has one lower dimension(s) as the original, such as DataFrame single columns slicing. …
_info_axis WeightedSeries  
_is_cached WeightedSeries Return boolean indicating if self is cached or not.
_is_datelike_mixed_type WeightedSeries  
_is_mixed_type WeightedSeries  
_is_numeric_mixed_type WeightedSeries  
_is_view WeightedSeries Return boolean indicating if self is view of another array
_ndarray_values WeightedArray Internal pandas method for lossy conversion to a NumPy ndarray. This method is not part of the pandas interface. …
_ndarray_values WeightedSeries The data as an ndarray, possibly losing information. The expectation is that this is cheap to compute, and is primarily …
_obj_with_exclusions WeightedSeries internal compat with SelectionMixin
_selected_obj WeightedSeries internal compat with SelectionMixin
_selection_list WeightedSeries  
_selection_name WeightedSeries return a name for myself; this would ideally be called the ‘name’ property, but we cannot conflict with the …
_stat_axis WeightedSeries  
_values WeightedSeries return the internal repr of this data
asobject WeightedSeries Return object Series which contains boxed values.
at WeightedSeries Access a single value for a row/column label pair. Similar to loc, in that both provide label-based lookups. Use …
average ExecutionStat average processing time
axes WeightedSeries Return a list of the row axis labels
base WeightedSeries return the base object if the memory of the underlying data is shared
blocks WeightedSeries Internal property, property synonym for as_blocks()
daemon KThread A boolean value indicating whether this thread is a daemon thread. This must be set before start() is called, otherwise …
data WeightedSeries return the data pointer of the underlying data
deviation ExecutionStat standard deviation
dtype WeightedArray Returns @see cl WeightedSeriesDtype.
dtype WeightedSeries return the dtype object of the underlying data
dtypes WeightedSeries return the dtype object of the underlying data
empty WeightedSeries  
flags WeightedSeries return the ndarray.flags for the underlying data
ftype WeightedSeries return if the data is sparse|dense
ftypes WeightedSeries return if the data is sparse|dense
iat WeightedSeries Access a single value for a row/column pair by integer position. Similar to iloc, in that both provide integer-based …
ident KThread Thread identifier of this thread or None if it has not been started. This is a nonzero integer. See the get_ident() …
iloc WeightedSeries Purely integer-location based indexing for selection by position. .iloc[] is primarily integer position based (from …
imag WeightedSeries  
is_copy WeightedSeries  
is_monotonic WeightedSeries Return boolean if values in the object are monotonic_increasing
is_monotonic_decreasing WeightedSeries Return boolean if values in the object are monotonic_decreasing
is_monotonic_increasing WeightedSeries Return boolean if values in the object are monotonic_increasing
is_unique WeightedSeries Return boolean if values in the object are unique Returns ——- is_unique : boolean
itemsize WeightedSeries return the size of the dtype of the item of the underlying data
ix WeightedSeries A primarily label-location based indexer, with integer position fallback. Warning: Starting in 0.20.0, the .ix …
kind WeightedSeriesDtype A character code (one of ‘biufcmMOSUV’), default ‘O’ This should match the NumPy dtype used when the array is …
loc WeightedSeries Access a group of rows and columns by label(s) or a boolean array. .loc[] is primarily label based, but may also …
max_exec ExecutionStat maximum execution time
min_exec ExecutionStat minimum execution time
name WeightedSeries  
name WeightedSeriesDtype A string identifying the data type. Will be used for display in, e.g. Series.dtype
name KThread A string used for identification purposes only. It has no semantics. Multiple threads may be given the same name. …
names WeightedSeriesDtype Ordered list of field names, or None if there are no fields. This is for compatibility with NumPy arrays, and may …
nbytes WeightedArray The number of bytes needed to store this object in memory.
nbytes WeightedSeries return the number of bytes in the underlying data
ndim WeightedArray Extension Arrays are only allowed to be 1-dimensional.
ndim WeightedSeries return the number of dimensions of the underlying data, by definition 1
number ExecutionStat number of executions being measured
real WeightedSeries  
repeat ExecutionStat number of times the experiment is repeated
shape WeightedArray Return a tuple of the array dimensions.
shape WeightedSeries return a tuple of the shape of the underlying data
size WeightedSeries return the number of elements in the underlying data
strides WeightedSeries return the strides of the underlying data
type WeightedSeriesDtype The scalar type for the array, e.g. int It’s expected ExtensionArray[item] returns an instance of …
value WeightedDoubleAccessor Returns the values.
value WeightedDouble unweighted numeric value (counter)
value WeightedFloat unweighted numeric value (counter)
values WeightedSeries Return Series as ndarray or ndarray-like depending on the dtype Returns ——- arr : numpy.ndarray …
weight WeightedDoubleAccessor Returns the weights.
weight WeightedDouble weight
weight WeightedFloat weight