API Reference

Table of Contents

• API Reference

  • si_unit_pandas.__init__

  • si_unit_pandas.base

  • si_unit_pandas.parser

  • si_unit_pandas.temperature_array

Custom Pandas dtypes for values with SI units.

Classes:

Celsius(value)	float subclass representing a temperature in Celsius.
CelsiusType()	Numpy dtype representing a temperature in degrees Celsius.
Fahrenheit([value])	float subclass representing a temperature in Fahrenheit.
TemperatureArray(data[, dtype, copy])	Holder for Temperatures.

Functions:

to_temperature(values)

Convert values to a TemperatureArray.

class Celsius(value)

Bases: UserFloat

float subclass representing a temperature in Celsius.

Convert a string or number to a floating point number, if possible.

Methods:

__abs__()	Return abs(self).
__add__(other)	Return self + value.
__bool__()	True if self != 0.
__ceil__()	Finds the least Integral >= self.
__complex__()	complex(self) == complex(float(self), 0)
__divmod__(other)	Return divmod(self, value).
__eq__(other)	Return self == other.
__float__()	Return float(self).
__floor__()	Finds the greatest Integral <= self.
__floordiv__(other)	Return self // value.
__ge__(other)	Return self >= other.
__gt__(other)	Return self > other.
__int__()	Return int(self).
__le__(other)	Return self <= other.
__lt__(other)	Return self < other.
__mod__(other)	Return self % value.
__mul__(other)	Return self * value.
__ne__(other)	Return self != other.
__neg__()	Return - self.
__pos__()	Return + self.
__pow__(other[, mod])	Return pow(self, value, mod).
__radd__(other)	Return value + self.
__rdivmod__(other)	Return divmod(value, self).
__repr__()	Return a string representation of the temperature.
__rfloordiv__(other)	Return value // self.
__rmod__(other)	Return value % self.
__rmul__(other)	Return value * self.
__round__([ndigits])	Rounds self to ndigits decimal places, defaulting to 0.
__rpow__(other[, mod])	Return pow(value, self, mod).
__rsub__(other)	Return value - self.
__rtruediv__(other)	Return value / self.
__str__()	Return the temperature as a string.
__sub__(other)	Return value - self.
__truediv__(other)	Return self / value.
__trunc__()	trunc(self): Truncates self to an Integral.
as_integer_ratio()	rtype Tuple[int, int]
conjugate()	Conjugate is a no-op for Reals.
fromhex(_UserFloat__s)	rtype ~_F
hex()	rtype str
is_integer()	rtype bool

Attributes:

__slots__
_abc_impl
imag	Real numbers have no imaginary component.
real	Real numbers are their real component.

__abs__()

Return abs(self).

Return type

~_F

__add__(other)

Return self + value.

Return type

~_F

__bool__()

True if self != 0. Called for bool(self).

Return type

bool

__ceil__()

Finds the least Integral >= self.

__complex__()

complex(self) == complex(float(self), 0)

__divmod__(other)

Return divmod(self, value).

Return type

Tuple[~_F, ~_F]

__eq__(other)

Return self == other.

Return type

bool

__float__()

Return float(self).

Return type

float

__floor__()

Finds the greatest Integral <= self.

__floordiv__(other)

Return self // value.

Return type

~_F

__ge__(other)

Return self >= other.

Return type

bool

__gt__(other)

Return self > other.

Return type

bool

__int__()

Return int(self).

Return type

int

__le__(other)

Return self <= other.

Return type

bool

__lt__(other)

Return self < other.

Return type

bool

__mod__(other)

Return self % value.

Return type

~_F

__mul__(other)

Return self * value.

Return type

~_F

__ne__(other)

Return self != other.

Return type

bool

__neg__()

Return - self.

Return type

~_F

__pos__()

Return + self.

Return type

~_F

__pow__(other, mod=None)

Return pow(self, value, mod).

Return type

~_F

__radd__(other)

Return value + self.

Return type

~_F

__rdivmod__(other)

Return divmod(value, self).

Return type

Tuple[~_F, ~_F]

__repr__()

Return a string representation of the temperature.

Return type

str

__rfloordiv__(other)

Return value // self.

Return type

~_F

__rmod__(other)

Return value % self.

Return type

~_F

__rmul__(other)

Return value * self.

Return type

~_F

__round__(ndigits=None)

Rounds self to ndigits decimal places, defaulting to 0.

If ndigits is omitted or None, returns an Integral, otherwise returns a Real. Rounds half toward even.

Return type

Union[int, float]

__rpow__(other, mod=None)

Return pow(value, self, mod).

Return type

~_F

__rsub__(other)

Return value - self.

Return type

~_F

__rtruediv__(other)

Return value / self.

Return type

~_F

__slots__ = ()

__str__()

Return the temperature as a string.

Return type

str

__sub__(other)

Return value - self.

Return type

~_F

__truediv__(other)

Return self / value.

Return type

~_F

__trunc__()

trunc(self): Truncates self to an Integral.

Returns an Integral i such that:

• i>0 iff self>0;

• abs(i) <= abs(self);

• for any Integral j satisfying the first two conditions, abs(i) >= abs(j) [i.e. i has “maximal” abs among those].

i.e. “truncate towards 0”.

Return type

int

_abc_impl = <_abc_data object>

as_integer_ratio()

Return type

Tuple[int, int]

conjugate()

Conjugate is a no-op for Reals.

classmethod fromhex(_UserFloat__s)

Return type

~_F

hex()

Return type

str

property imag

Real numbers have no imaginary component.

is_integer()

Return type

bool

property real

Real numbers are their real component.

class CelsiusType

Bases: ExtensionDtype

Numpy dtype representing a temperature in degrees Celsius.

Methods:

__eq__(other)	Check whether ‘other’ is equal to self.
__ne__(other)	Return self!=value.
__str__()	Return str(self).
_get_common_dtype(dtypes)	Return the common dtype, if one exists.
construct_array_type()	Return the array type associated with this dtype.
construct_from_string(string)	Construct a CelsiusType from a string.
is_dtype(dtype)	Check if we match ‘dtype’.

Attributes:

_is_boolean	Whether this dtype should be considered boolean.
_is_numeric	Whether columns with this dtype should be considered numeric.
_metadata
kind
na_value	Default NA value to use for this type.
name
names	Ordered list of field names, or None if there are no fields.

Classes:

_record_type	alias of builtins.float
type	alias of TemperatureBase

__eq__(other)

Check whether ‘other’ is equal to self.

By default, ‘other’ is considered equal if either

• it’s a string matching ‘self.name’.

• it’s an instance of this type and all of the attributes in self._metadata are equal between self and other.

other : Any

bool

Return type

bool

__ne__(other)

Return self!=value.

Return type

bool

__str__()

Return str(self).

Return type

str

_get_common_dtype(dtypes)

Return the common dtype, if one exists.

Used in find_common_type implementation. This is for example used to determine the resulting dtype in a concat operation.

If no common dtype exists, return None (which gives the other dtypes the chance to determine a common dtype). If all dtypes in the list return None, then the common dtype will be “object” dtype (this means it is never needed to return “object” dtype from this method itself).

dtypeslist of dtypes

The dtypes for which to determine a common dtype. This is a list of np.dtype or ExtensionDtype instances.

Common dtype (np.dtype or ExtensionDtype) or None

Return type

Union[dtype, ExtensionDtype, None]

property _is_boolean

Whether this dtype should be considered boolean.

By default, ExtensionDtypes are assumed to be non-numeric. Setting this to True will affect the behavior of several places, e.g.

• is_bool

• boolean indexing

Return type

bool

property _is_numeric

Whether columns with this dtype should be considered numeric.

By default ExtensionDtypes are assumed to be non-numeric. They’ll be excluded from operations that exclude non-numeric columns, like (groupby) reductions, plotting, etc.

Return type

bool

_metadata: Tuple[str, …] = ()

_record_type

alias of builtins.float

classmethod construct_array_type()

Return the array type associated with this dtype.

type

Return type

Type[TemperatureArray]

classmethod construct_from_string(string)

Construct a CelsiusType from a string.

Parameters

string

classmethod is_dtype(dtype)

Check if we match ‘dtype’.

dtypeobject

The object to check.

bool

The default implementation is True if

1. cls.construct_from_string(dtype) is an instance of cls.

2. dtype is an object and is an instance of cls

3. dtype has a dtype attribute, and any of the above conditions is true for dtype.dtype.

Return type

bool

kind: str = 'O'

property na_value

Default NA value to use for this type.

This is used in e.g. ExtensionArray.take. This should be the user-facing “boxed” version of the NA value, not the physical NA value for storage. e.g. for JSONArray, this is an empty dictionary.

Return type

object

name: str = 'celsius'

property names

Ordered list of field names, or None if there are no fields.

This is for compatibility with NumPy arrays, and may be removed in the future.

Return type

Optional[List[str]]

type

alias of TemperatureBase

class Fahrenheit(value=0.0)

Bases: UserFloat

float subclass representing a temperature in Fahrenheit.

Convert a string or number to a floating point number, if possible.

Methods:

__abs__()	Return abs(self).
__add__(other)	Return self + value.
__bool__()	True if self != 0.
__ceil__()	Finds the least Integral >= self.
__complex__()	complex(self) == complex(float(self), 0)
__divmod__(other)	Return divmod(self, value).
__eq__(other)	Return self == other.
__float__()	Return float(self).
__floor__()	Finds the greatest Integral <= self.
__floordiv__(other)	Return self // value.
__ge__(other)	Return self >= other.
__gt__(other)	Return self > other.
__int__()	Return int(self).
__le__(other)	Return self <= other.
__lt__(other)	Return self < other.
__mod__(other)	Return self % value.
__mul__(other)	Return self * value.
__ne__(other)	Return self != other.
__neg__()	Return - self.
__pos__()	Return + self.
__pow__(other[, mod])	Return pow(self, value, mod).
__radd__(other)	Return value + self.
__rdivmod__(other)	Return divmod(value, self).
__repr__()	Return a string representation of the temperature.
__rfloordiv__(other)	Return value // self.
__rmod__(other)	Return value % self.
__rmul__(other)	Return value * self.
__round__([ndigits])	Rounds self to ndigits decimal places, defaulting to 0.
__rpow__(other[, mod])	Return pow(value, self, mod).
__rsub__(other)	Return value - self.
__rtruediv__(other)	Return value / self.
__str__()	Return the temperature as a string.
__sub__(other)	Return value - self.
__truediv__(other)	Return self / value.
__trunc__()	trunc(self): Truncates self to an Integral.
as_integer_ratio()	rtype Tuple[int, int]
conjugate()	Conjugate is a no-op for Reals.
fromhex(_UserFloat__s)	rtype ~_F
hex()	rtype str
is_integer()	rtype bool

Attributes:

__slots__
_abc_impl
imag	Real numbers have no imaginary component.
real	Real numbers are their real component.

__abs__()

Return abs(self).

Return type

~_F

__add__(other)

Return self + value.

Return type

~_F

__bool__()

True if self != 0. Called for bool(self).

Return type

bool

__ceil__()

Finds the least Integral >= self.

__complex__()

complex(self) == complex(float(self), 0)

__divmod__(other)

Return divmod(self, value).

Return type

Tuple[~_F, ~_F]

__eq__(other)

Return self == other.

Return type

bool

__float__()

Return float(self).

Return type

float

__floor__()

Finds the greatest Integral <= self.

__floordiv__(other)

Return self // value.

Return type

~_F

__ge__(other)

Return self >= other.

Return type

bool

__gt__(other)

Return self > other.

Return type

bool

__int__()

Return int(self).

Return type

int

__le__(other)

Return self <= other.

Return type

bool

__lt__(other)

Return self < other.

Return type

bool

__mod__(other)

Return self % value.

Return type

~_F

__mul__(other)

Return self * value.

Return type

~_F

__ne__(other)

Return self != other.

Return type

bool

__neg__()

Return - self.

Return type

~_F

__pos__()

Return + self.

Return type

~_F

__pow__(other, mod=None)

Return pow(self, value, mod).

Return type

~_F

__radd__(other)

Return value + self.

Return type

~_F

__rdivmod__(other)

Return divmod(value, self).

Return type

Tuple[~_F, ~_F]

__repr__()

Return a string representation of the temperature.

Return type

str

__rfloordiv__(other)

Return value // self.

Return type

~_F

__rmod__(other)

Return value % self.

Return type

~_F

__rmul__(other)

Return value * self.

Return type

~_F

__round__(ndigits=None)

Rounds self to ndigits decimal places, defaulting to 0.

If ndigits is omitted or None, returns an Integral, otherwise returns a Real. Rounds half toward even.

Return type

Union[int, float]

__rpow__(other, mod=None)

Return pow(value, self, mod).

Return type

~_F

__rsub__(other)

Return value - self.

Return type

~_F

__rtruediv__(other)

Return value / self.

Return type

~_F

__slots__ = ()

__str__()

Return the temperature as a string.

Return type

str

__sub__(other)

Return value - self.

Return type

~_F

__truediv__(other)

Return self / value.

Return type

~_F

__trunc__()

trunc(self): Truncates self to an Integral.

Returns an Integral i such that:

• i>0 iff self>0;

• abs(i) <= abs(self);

• for any Integral j satisfying the first two conditions, abs(i) >= abs(j) [i.e. i has “maximal” abs among those].

i.e. “truncate towards 0”.

Return type

int

_abc_impl = <_abc_data object>

as_integer_ratio()

Return type

Tuple[int, int]

conjugate()

Conjugate is a no-op for Reals.

classmethod fromhex(_UserFloat__s)

Return type

~_F

hex()

Return type

str

property imag

Real numbers have no imaginary component.

is_integer()

Return type

bool

property real

Real numbers are their real component.

class TemperatureArray(data, dtype=None, copy=False)

Bases: BaseArray

Holder for Temperatures.

TemperatureArray is a container for Temperatures. It satisfies pandas’ extension array interface, and so can be stored inside pandas.Series and pandas.DataFrame.

Attributes:

T	rtype ExtensionArray
__array_priority__
_can_hold_na
_dtype
_itemsize
_parser
_typ
can_hold_na
dtype	The dtype for this extension array, CelsiusType.
na_value	The missing value.
nbytes	The number of bytes needed to store this object in memory.
ndim
shape	Return a tuple of the array dimensions.
size	The number of elements in the array.

Methods:

__abs__()
__add__(other)
__and__(other)
__contains__(item)	Return for item in self.
__delitem__(where)
__divmod__(other)
__eq__(other)	Return for self == other (element-wise equality).
__floordiv__(other)
__ge__(other)	Return self>=value.
__getitem__(item)	Select a subset of self.
__gt__(other)	Return self>value.
__iadd__(other)
__iand__(other)
__ifloordiv__(other)
__ilshift__(other)
__imatmul__(other)
__imod__(other)
__imul__(other)
__invert__()
__ior__(other)
__ipow__(other)
__irshift__(other)
__isub__(other)
__iter__()	Iterate over elements of the array.
__itruediv__(other)
__ixor__(other)
__le__(other)	Return self<=value.
__len__()	Returns the length of this array.
__lshift__(other)
__lt__(other)	Return self<value.
__matmul__(other)
__mod__(other)
__mul__(other)
__ne__(other)	Return for self != other (element-wise in-equality).
__neg__()
__or__(other)
__pos__()
__pow__(other)
__radd__(other)
__rand__(other)
__rdivmod__(other)
__repr__()	Return repr(self).
__rfloordiv__(other)
__rlshift__(other)
__rmatmul__(other)
__rmod__(other)
__rmul__(other)
__ror__(other)
__rpow__(other)
__rrshift__(other)
__rshift__(other)
__rsub__(other)
__rtruediv__(other)
__rxor__(other)
__setitem__(key, value)	Set one or more values inplace.
__sub__(other)
__truediv__(other)
__xor__(other)
_concat_same_type(to_concat)	Concatenate multiple arrays.
_format_values()
_formatter([boxed])	Formatting function for scalar values.
_formatting_values()
_from_factorized(values, original)	Reconstruct an ExtensionArray after factorization.
_from_ndarray(data[, copy])	Zero-copy construction of a BaseArray from an ndarray.
_from_sequence(scalars[, dtype, copy])	Construct a new ExtensionArray from a sequence of scalars.
_from_sequence_of_strings(strings, *[, …])	Construct a new ExtensionArray from a sequence of strings.
_isstringslice(where)
_reduce(name, *[, skipna])	Return a scalar result of performing the reduction operation.
_values_for_argsort()	Return values for sorting.
_values_for_factorize()	Return an array and missing value suitable for factorization.
append(value)	Append a value to this TemperatureArray.
argmax()	Return the index of maximum value.
argmin()	Return the index of minimum value.
argsort([ascending, kind])	Return the indices that would sort this array.
astype(dtype[, copy])	Returns the array with its values as the given dtype.
copy([deep])	Return a copy of the array.
dropna()	Return ExtensionArray without NA values.
equals(other)	Return if another array is equivalent to this array.
factorize([na_sentinel])	Encode the extension array as an enumerated type.
fillna([value, method, limit])	Fill NA/NaN values using the specified method.
isin(other)	Check whether elements of self are in other.
isna()	Indicator for whether each element is missing.
ravel([order])	Return a flattened view on this array.
repeat(repeats[, axis])	Repeat elements of a ExtensionArray.
searchsorted(value[, side, sorter])	Find indices where elements should be inserted to maintain order.
setitem(indexer, value)	Set the ‘value’ inplace.
shift([periods, fill_value])	Shift values by desired number.
take(indices[, allow_fill, fill_value])	Take elements from an array.
to_numpy([dtype, copy, na_value])	Convert to a NumPy ndarray.
tolist()	Convert the array to a Python list.
transpose(*axes)	Return a transposed view on this array.
unique()	Compute the ExtensionArray of unique values.
view([dtype])	Return a view on the array.

property T

Return type

ExtensionArray

__abs__()

__add__(other)

__and__(other)

__array_priority__: int = 1000

__contains__(item)

Return for item in self.

Return type

bool

__delitem__(where)

__divmod__(other)

__eq__(other)

Return for self == other (element-wise equality).

__floordiv__(other)

__ge__(other)

Return self>=value.

__getitem__(item)

Select a subset of self.

Parameters

item (Union[int, slice, ndarray]) –

• int: The position in ‘self’ to get.

• slice: A slice object, where ‘start’, ‘stop’, and ‘step’ are integers or None.

• ndarray: A 1-d boolean NumPy ndarray the same length as ‘self’

Return type

scalar or ExtensionArray

Note

For scalar item, return a scalar value suitable for the array’s type. This should be an instance of self.dtype.type.

For slice key, return an instance of ExtensionArray, even if the slice is length 0 or 1.

For a boolean mask, return an instance of ExtensionArray, filtered to the values where item is True.

__gt__(other)

Return self>value.

__iadd__(other)

__iand__(other)

__ifloordiv__(other)

__ilshift__(other)

__imatmul__(other)

__imod__(other)

__imul__(other)

__invert__()

__ior__(other)

__ipow__(other)

__irshift__(other)

__isub__(other)

__iter__()

Iterate over elements of the array.

__itruediv__(other)

__ixor__(other)

__le__(other)

Return self<=value.

__len__()

Returns the length of this array.

Return type

int

__lshift__(other)

__lt__(other)

Return self<value.

__matmul__(other)

__mod__(other)

__mul__(other)

__ne__(other)

Return for self != other (element-wise in-equality).

__neg__()

__or__(other)

__pos__()

__pow__(other)

__radd__(other)

__rand__(other)

__rdivmod__(other)

__repr__()

Return repr(self).

Return type

str

__rfloordiv__(other)

__rlshift__(other)

__rmatmul__(other)

__rmod__(other)

__rmul__(other)

__ror__(other)

__rpow__(other)

__rrshift__(other)

__rshift__(other)

__rsub__(other)

__rtruediv__(other)

__rxor__(other)

__setitem__(key, value)

Set one or more values inplace.

This method is not required to satisfy the pandas extension array interface.

keyint, ndarray, or slice

When called from, e.g. Series.__setitem__, key will be one of

• scalar int

• ndarray of integers.

• boolean ndarray

• slice object

valueExtensionDtype.type, Sequence[ExtensionDtype.type], or object

value or values to be set of key.

None

__sub__(other)

__truediv__(other)

__xor__(other)

_can_hold_na = True

classmethod _concat_same_type(to_concat)

Concatenate multiple arrays.

Parameters

to_concat (Sequence[ABCExtensionArray]) – sequence of this type

Return type

ABCExtensionArray

_dtype: Type[pandas.core.dtypes.base.ExtensionDtype] = <si_unit_pandas.temperature.CelsiusType object>

_format_values()

_formatter(boxed=False)

Formatting function for scalar values.

This is used in the default ‘__repr__’. The returned formatting function receives instances of your scalar type.

boxedbool, default False

An indicated for whether or not your array is being printed within a Series, DataFrame, or Index (True), or just by itself (False). This may be useful if you want scalar values to appear differently within a Series versus on its own (e.g. quoted or not).

Callable[[Any], str]

A callable that gets instances of the scalar type and returns a string. By default, repr() is used when boxed=False and str() is used when boxed=True.

Return type

Callable[[Any], Optional[str]]

_formatting_values()

classmethod _from_factorized(values, original)

Reconstruct an ExtensionArray after factorization.

Parameters

• values (ndarray) – An integer ndarray with the factorized values.

• original (ExtensionArray) – The original ExtensionArray that factorize was called on.

See also

pandas.pandas.api.extensions.ExtensionArray.factorize()

classmethod _from_ndarray(data, copy=False)

Zero-copy construction of a BaseArray from an ndarray.

Parameters

• data (ndarray) – This should have CelsiusType._record_type dtype

• copy (bool) – Whether to copy the data. Default False.

Return type

~_A

Returns

classmethod _from_sequence(scalars, dtype=None, copy=False)

Construct a new ExtensionArray from a sequence of scalars.

Parameters

• scalars (Iterable) – Each element will be an instance of the scalar type for this array, cls.dtype.type.

• dtype (dtype, optional) – Construct for this particular dtype. This should be a Dtype compatible with the ExtensionArray. Default None.

• copy (bool) – If True, copy the underlying data. Default False.

classmethod _from_sequence_of_strings(strings, *, dtype=None, copy=False)

Construct a new ExtensionArray from a sequence of strings.

New in version 0.24.0.

stringsSequence

Each element will be an instance of the scalar type for this array, cls.dtype.type.

dtypedtype, optional

Construct for this particular dtype. This should be a Dtype compatible with the ExtensionArray.

copybool, default False

If True, copy the underlying data.

ExtensionArray

_isstringslice(where)

_itemsize: int = 16

property _parser

_reduce(name, *, skipna=True, **kwargs)

Return a scalar result of performing the reduction operation.

namestr

Name of the function, supported values are: { any, all, min, max, sum, mean, median, prod, std, var, sem, kurt, skew }.

skipnabool, default True

If True, skip NaN values.

**kwargs

Additional keyword arguments passed to the reduction function. Currently, ddof is the only supported kwarg.

scalar

TypeError : subclass does not define reductions

_typ = 'extension'

_values_for_argsort()

Return values for sorting.

ndarray

The transformed values should maintain the ordering between values within the array.

ExtensionArray.argsort : Return the indices that would sort this array.

Return type

ndarray

_values_for_factorize()

Return an array and missing value suitable for factorization.

values : ndarray

An array suitable for factorization. This should maintain order and be a supported dtype (Float64, Int64, UInt64, String, Object). By default, the extension array is cast to object dtype.

na_valueobject

The value in values to consider missing. This will be treated as NA in the factorization routines, so it will be coded as na_sentinel and not included in uniques. By default, np.nan is used.

The values returned by this method are also used in pandas.util.hash_pandas_object().

Return type

Tuple[ndarray, Any]

append(value)

Append a value to this TemperatureArray.

Parameters

value (Union[float, str, Sequence[Union[float, str]]])

argmax()

Return the index of maximum value.

In case of multiple occurrences of the maximum value, the index corresponding to the first occurrence is returned.

int

ExtensionArray.argmin

argmin()

Return the index of minimum value.

In case of multiple occurrences of the minimum value, the index corresponding to the first occurrence is returned.

int

ExtensionArray.argmax

argsort(ascending=True, kind='quicksort', *args, **kwargs)

Return the indices that would sort this array.

Parameters

• ascending (bool) – Whether the indices should result in an ascending or descending sort. Default True.

• kind (Union[Literal['quicksort'], Literal['mergesort'], Literal['heapsort']]) – {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional Sorting algorithm. Default 'quicksort'.

*args and **kwargs are passed through to numpy.argsort().

Return type

ndarray

Returns

Array of indices that sort self. If NaN values are contained, NaN values are placed at the end.

See also

numpy.argsort: Sorting implementation used internally.

astype(dtype, copy=True)

Returns the array with its values as the given dtype.

Parameters

• dtype

• copy – If True, returns a copy of the array. Default True.

can_hold_na: bool = True

copy(deep=False)

Return a copy of the array.

Parameters

deep (bool) – Default False.

Returns

Return type

ABCExtensionArray

data

Type:    ndarray

dropna()

Return ExtensionArray without NA values.

valid : ExtensionArray

property dtype

The dtype for this extension array, CelsiusType.

equals(other)

Return if another array is equivalent to this array.

Equivalent means that both arrays have the same shape and dtype, and all values compare equal. Missing values in the same location are considered equal (in contrast with normal equality).

otherExtensionArray

Array to compare to this Array.

boolean

Whether the arrays are equivalent.

Return type

bool

factorize(na_sentinel=- 1)

Encode the extension array as an enumerated type.

na_sentinelint, default -1

Value to use in the codes array to indicate missing values.

codesndarray

An integer NumPy array that’s an indexer into the original ExtensionArray.

uniquesExtensionArray

An ExtensionArray containing the unique values of self.

Note

uniques will not contain an entry for the NA value of the ExtensionArray if there are any missing values present in self.

factorize : Top-level factorize method that dispatches here.

pandas.factorize() offers a sort keyword as well.

Return type

Tuple[ndarray, ExtensionArray]

fillna(value=None, method=None, limit=None)

Fill NA/NaN values using the specified method.

valuescalar, array-like

If a scalar value is passed it is used to fill all missing values. Alternatively, an array-like ‘value’ can be given. It’s expected that the array-like have the same length as ‘self’.

method{‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None}, default None

Method to use for filling holes in reindexed Series pad / ffill: propagate last valid observation forward to next valid backfill / bfill: use NEXT valid observation to fill gap.

limitint, default None

If method is specified, this is the maximum number of consecutive NaN values to forward/backward fill. In other words, if there is a gap with more than this number of consecutive NaNs, it will only be partially filled. If method is not specified, this is the maximum number of entries along the entire axis where NaNs will be filled.

ExtensionArray

With NA/NaN filled.

isin(other)

Check whether elements of self are in other.

Comparison is done elementwise.

Parameters

other (Union[float, str, Sequence[Union[float, str]]])

Return type

ndarray

Returns

A 1-D boolean ndarray with the same length as self.

isna()

Indicator for whether each element is missing.

property na_value

The missing value.

Example:

>>> BaseArray([]).na_value
numpy.nan

property nbytes

The number of bytes needed to store this object in memory.

Return type

int

ndim: int = 1

ravel(order='C')

Return a flattened view on this array.

order : {None, ‘C’, ‘F’, ‘A’, ‘K’}, default ‘C’

ExtensionArray

• Because ExtensionArrays are 1D-only, this is a no-op.

• The “order” argument is ignored, is for compatibility with NumPy.

Return type

ExtensionArray

repeat(repeats, axis=None)

Repeat elements of a ExtensionArray.

Returns a new ExtensionArray where each element of the current ExtensionArray is repeated consecutively a given number of times.

repeatsint or array of ints

The number of repetitions for each element. This should be a non-negative integer. Repeating 0 times will return an empty ExtensionArray.

axisNone

Must be None. Has no effect but is accepted for compatibility with numpy.

repeated_arrayExtensionArray

Newly created ExtensionArray with repeated elements.

Series.repeat : Equivalent function for Series. Index.repeat : Equivalent function for Index. numpy.repeat : Similar method for numpy.ndarray. ExtensionArray.take : Take arbitrary positions.

>>> cat = pd.Categorical(['a', 'b', 'c'])
>>> cat
['a', 'b', 'c']
Categories (3, object): ['a', 'b', 'c']
>>> cat.repeat(2)
['a', 'a', 'b', 'b', 'c', 'c']
Categories (3, object): ['a', 'b', 'c']
>>> cat.repeat([1, 2, 3])
['a', 'b', 'b', 'c', 'c', 'c']
Categories (3, object): ['a', 'b', 'c']

searchsorted(value, side='left', sorter=None)

Find indices where elements should be inserted to maintain order.

New in version 0.24.0.

Find the indices into a sorted array self (a) such that, if the corresponding elements in value were inserted before the indices, the order of self would be preserved.

Assuming that self is sorted:

side	returned index i satisfies
left	self[i-1] < value <= self[i]
right	self[i-1] <= value < self[i]

valuearray_like

Values to insert into self.

side{‘left’, ‘right’}, optional

If ‘left’, the index of the first suitable location found is given. If ‘right’, return the last such index. If there is no suitable index, return either 0 or N (where N is the length of self).

sorter1-D array_like, optional

Optional array of integer indices that sort array a into ascending order. They are typically the result of argsort.

array of ints

Array of insertion points with the same shape as value.

numpy.searchsorted : Similar method from NumPy.

setitem(indexer, value)

Set the ‘value’ inplace.

property shape

Return a tuple of the array dimensions.

Return type

Tuple[int]

shift(periods=1, fill_value=None)

Shift values by desired number.

Newly introduced missing values are filled with self.dtype.na_value.

New in version 0.24.0.

periodsint, default 1

The number of periods to shift. Negative values are allowed for shifting backwards.

fill_valueobject, optional

The scalar value to use for newly introduced missing values. The default is self.dtype.na_value.

New in version 0.24.0.

ExtensionArray

Shifted.

If self is empty or periods is 0, a copy of self is returned.

If periods > len(self), then an array of size len(self) is returned, with all values filled with self.dtype.na_value.

Return type

ExtensionArray

property size

The number of elements in the array.

Return type

int

take(indices, allow_fill=False, fill_value=None)

Take elements from an array.

indicessequence of int

Indices to be taken.

allow_fillbool, default False

How to handle negative values in indices.

• False: negative values in indices indicate positional indices from the right (the default). This is similar to numpy.take().

• True: negative values in indices indicate missing values. These values are set to fill_value. Any other other negative values raise a ValueError.

fill_valueany, optional

Fill value to use for NA-indices when allow_fill is True. This may be None, in which case the default NA value for the type, self.dtype.na_value, is used.

For many ExtensionArrays, there will be two representations of fill_value: a user-facing “boxed” scalar, and a low-level physical NA value. fill_value should be the user-facing version, and the implementation should handle translating that to the physical version for processing the take if necessary.

ExtensionArray

IndexError

When the indices are out of bounds for the array.

ValueError

When indices contains negative values other than -1 and allow_fill is True.

numpy.take : Take elements from an array along an axis. api.extensions.take : Take elements from an array.

ExtensionArray.take is called by Series.__getitem__, .loc, iloc, when indices is a sequence of values. Additionally, it’s called by Series.reindex(), or any other method that causes realignment, with a fill_value.

Here’s an example implementation, which relies on casting the extension array to object dtype. This uses the helper method pandas.api.extensions.take().

def take(self, indices, allow_fill=False, fill_value=None):
    from pandas.core.algorithms import take

    # If the ExtensionArray is backed by an ndarray, then
    # just pass that here instead of coercing to object.
    data = self.astype(object)

    if allow_fill and fill_value is None:
        fill_value = self.dtype.na_value

    # fill value should always be translated from the scalar
    # type for the array, to the physical storage type for
    # the data, before passing to take.

    result = take(data, indices, fill_value=fill_value,
                  allow_fill=allow_fill)
    return self._from_sequence(result, dtype=self.dtype)

to_numpy(dtype=None, copy=False, na_value=<object object>)

Convert to a NumPy ndarray.

New in version 1.0.0.

This is similar to numpy.asarray(), but may provide additional control over how the conversion is done.

dtypestr or numpy.dtype, optional

The dtype to pass to numpy.asarray().

copybool, default False

Whether to ensure that the returned value is a not a view on another array. Note that copy=False does not ensure that to_numpy() is no-copy. Rather, copy=True ensure that a copy is made, even if not strictly necessary.

na_valueAny, optional

The value to use for missing values. The default value depends on dtype and the type of the array.

numpy.ndarray

Return type

ndarray

tolist()

Convert the array to a Python list.

Return type

List

transpose(*axes)

Return a transposed view on this array.

Because ExtensionArrays are always 1D, this is a no-op. It is included for compatibility with np.ndarray.

Return type

ExtensionArray

unique()

Compute the ExtensionArray of unique values.

uniques : ExtensionArray

Return type

ExtensionArray

view(dtype=None)

Return a view on the array.

dtypestr, np.dtype, or ExtensionDtype, optional

Default None.

ExtensionArray or np.ndarray

A view on the ExtensionArray’s data.

Return type

~ArrayLike

to_temperature(values)

Convert values to a TemperatureArray.

Parameters

values (Union[float, str, Sequence[Union[float, str]]])

Return type

TemperatureArray

si_unit_pandas.__init__

Custom Pandas dtypes for values with SI units.

Classes:

Celsius(value)	float subclass representing a temperature in Celsius.
CelsiusType()	Numpy dtype representing a temperature in degrees Celsius.
Fahrenheit([value])	float subclass representing a temperature in Fahrenheit.
TemperatureArray(data[, dtype, copy])	Holder for Temperatures.

Functions:

to_temperature(values)

Convert values to a TemperatureArray.

class Celsius(value)

Bases: UserFloat

float subclass representing a temperature in Celsius.

Convert a string or number to a floating point number, if possible.

Methods:

__abs__()	Return abs(self).
__add__(other)	Return self + value.
__bool__()	True if self != 0.
__ceil__()	Finds the least Integral >= self.
__complex__()	complex(self) == complex(float(self), 0)
__divmod__(other)	Return divmod(self, value).
__eq__(other)	Return self == other.
__float__()	Return float(self).
__floor__()	Finds the greatest Integral <= self.
__floordiv__(other)	Return self // value.
__ge__(other)	Return self >= other.
__gt__(other)	Return self > other.
__int__()	Return int(self).
__le__(other)	Return self <= other.
__lt__(other)	Return self < other.
__mod__(other)	Return self % value.
__mul__(other)	Return self * value.
__ne__(other)	Return self != other.
__neg__()	Return - self.
__pos__()	Return + self.
__pow__(other[, mod])	Return pow(self, value, mod).
__radd__(other)	Return value + self.
__rdivmod__(other)	Return divmod(value, self).
__repr__()	Return a string representation of the temperature.
__rfloordiv__(other)	Return value // self.
__rmod__(other)	Return value % self.
__rmul__(other)	Return value * self.
__round__([ndigits])	Rounds self to ndigits decimal places, defaulting to 0.
__rpow__(other[, mod])	Return pow(value, self, mod).
__rsub__(other)	Return value - self.
__rtruediv__(other)	Return value / self.
__str__()	Return the temperature as a string.
__sub__(other)	Return value - self.
__truediv__(other)	Return self / value.
__trunc__()	trunc(self): Truncates self to an Integral.
as_integer_ratio()	rtype Tuple[int, int]
conjugate()	Conjugate is a no-op for Reals.
fromhex(_UserFloat__s)	rtype ~_F
hex()	rtype str
is_integer()	rtype bool

Attributes:

__slots__
_abc_impl
imag	Real numbers have no imaginary component.
real	Real numbers are their real component.

__abs__()

Return abs(self).

Return type

~_F

__add__(other)

Return self + value.

Return type

~_F

__bool__()

True if self != 0. Called for bool(self).

Return type

bool

__ceil__()

Finds the least Integral >= self.

__complex__()

complex(self) == complex(float(self), 0)

__divmod__(other)

Return divmod(self, value).

Return type

Tuple[~_F, ~_F]

__eq__(other)

Return self == other.

Return type

bool

__float__()

Return float(self).

Return type

float

__floor__()

Finds the greatest Integral <= self.

__floordiv__(other)

Return self // value.

Return type

~_F

__ge__(other)

Return self >= other.

Return type

bool

__gt__(other)

Return self > other.

Return type

bool

__int__()

Return int(self).

Return type

int

__le__(other)

Return self <= other.

Return type

bool

__lt__(other)

Return self < other.

Return type

bool

__mod__(other)

Return self % value.

Return type

~_F

__mul__(other)

Return self * value.

Return type

~_F

__ne__(other)

Return self != other.

Return type

bool

__neg__()

Return - self.

Return type

~_F

__pos__()

Return + self.

Return type

~_F

__pow__(other, mod=None)

Return pow(self, value, mod).

Return type

~_F

__radd__(other)

Return value + self.

Return type

~_F

__rdivmod__(other)

Return divmod(value, self).

Return type

Tuple[~_F, ~_F]

__repr__()

Return a string representation of the temperature.

Return type

str

__rfloordiv__(other)

Return value // self.

Return type

~_F

__rmod__(other)

Return value % self.

Return type

~_F

__rmul__(other)

Return value * self.

Return type

~_F

__round__(ndigits=None)

Rounds self to ndigits decimal places, defaulting to 0.

If ndigits is omitted or None, returns an Integral, otherwise returns a Real. Rounds half toward even.

Return type

Union[int, float]

__rpow__(other, mod=None)

Return pow(value, self, mod).

Return type

~_F

__rsub__(other)

Return value - self.

Return type

~_F

__rtruediv__(other)

Return value / self.

Return type

~_F

__slots__ = ()

__str__()

Return the temperature as a string.

Return type

str

__sub__(other)

Return value - self.

Return type

~_F

__truediv__(other)

Return self / value.

Return type

~_F

__trunc__()

trunc(self): Truncates self to an Integral.

Returns an Integral i such that:

• i>0 iff self>0;

• abs(i) <= abs(self);

• for any Integral j satisfying the first two conditions, abs(i) >= abs(j) [i.e. i has “maximal” abs among those].

i.e. “truncate towards 0”.

Return type

int

_abc_impl = <_abc_data object>

as_integer_ratio()

Return type

Tuple[int, int]

conjugate()

Conjugate is a no-op for Reals.

classmethod fromhex(_UserFloat__s)

Return type

~_F

hex()

Return type

str

property imag

Real numbers have no imaginary component.

is_integer()

Return type

bool

property real

Real numbers are their real component.

class CelsiusType

Bases: ExtensionDtype

Numpy dtype representing a temperature in degrees Celsius.

Methods:

__eq__(other)	Check whether ‘other’ is equal to self.
__ne__(other)	Return self!=value.
__str__()	Return str(self).
_get_common_dtype(dtypes)	Return the common dtype, if one exists.
construct_array_type()	Return the array type associated with this dtype.
construct_from_string(string)	Construct a CelsiusType from a string.
is_dtype(dtype)	Check if we match ‘dtype’.

Attributes:

_is_boolean	Whether this dtype should be considered boolean.
_is_numeric	Whether columns with this dtype should be considered numeric.
_metadata
kind
na_value	Default NA value to use for this type.
name
names	Ordered list of field names, or None if there are no fields.

Classes:

_record_type	alias of builtins.float
type	alias of TemperatureBase

__eq__(other)

Check whether ‘other’ is equal to self.

By default, ‘other’ is considered equal if either

• it’s a string matching ‘self.name’.

• it’s an instance of this type and all of the attributes in self._metadata are equal between self and other.

other : Any

bool

Return type

bool

__ne__(other)

Return self!=value.

Return type

bool

__str__()

Return str(self).

Return type

str

_get_common_dtype(dtypes)

Return the common dtype, if one exists.

Used in find_common_type implementation. This is for example used to determine the resulting dtype in a concat operation.

If no common dtype exists, return None (which gives the other dtypes the chance to determine a common dtype). If all dtypes in the list return None, then the common dtype will be “object” dtype (this means it is never needed to return “object” dtype from this method itself).

dtypeslist of dtypes

The dtypes for which to determine a common dtype. This is a list of np.dtype or ExtensionDtype instances.

Common dtype (np.dtype or ExtensionDtype) or None

Return type

Union[dtype, ExtensionDtype, None]

property _is_boolean

Whether this dtype should be considered boolean.

By default, ExtensionDtypes are assumed to be non-numeric. Setting this to True will affect the behavior of several places, e.g.

• is_bool

• boolean indexing

Return type

bool

property _is_numeric

Whether columns with this dtype should be considered numeric.

By default ExtensionDtypes are assumed to be non-numeric. They’ll be excluded from operations that exclude non-numeric columns, like (groupby) reductions, plotting, etc.

Return type

bool

_metadata: Tuple[str, …] = ()

_record_type

alias of builtins.float

classmethod construct_array_type()

Return the array type associated with this dtype.

type

Return type

Type[TemperatureArray]

classmethod construct_from_string(string)

Construct a CelsiusType from a string.

Parameters

string

classmethod is_dtype(dtype)

Check if we match ‘dtype’.

dtypeobject

The object to check.

bool

The default implementation is True if

1. cls.construct_from_string(dtype) is an instance of cls.

2. dtype is an object and is an instance of cls

3. dtype has a dtype attribute, and any of the above conditions is true for dtype.dtype.

Return type

bool

kind: str = 'O'

property na_value

Default NA value to use for this type.

This is used in e.g. ExtensionArray.take. This should be the user-facing “boxed” version of the NA value, not the physical NA value for storage. e.g. for JSONArray, this is an empty dictionary.

Return type

object

name: str = 'celsius'

property names

Ordered list of field names, or None if there are no fields.

This is for compatibility with NumPy arrays, and may be removed in the future.

Return type

Optional[List[str]]

type

alias of TemperatureBase

class Fahrenheit(value=0.0)

Bases: UserFloat

float subclass representing a temperature in Fahrenheit.

Convert a string or number to a floating point number, if possible.

Methods:

__abs__()	Return abs(self).
__add__(other)	Return self + value.
__bool__()	True if self != 0.
__ceil__()	Finds the least Integral >= self.
__complex__()	complex(self) == complex(float(self), 0)
__divmod__(other)	Return divmod(self, value).
__eq__(other)	Return self == other.
__float__()	Return float(self).
__floor__()	Finds the greatest Integral <= self.
__floordiv__(other)	Return self // value.
__ge__(other)	Return self >= other.
__gt__(other)	Return self > other.
__int__()	Return int(self).
__le__(other)	Return self <= other.
__lt__(other)	Return self < other.
__mod__(other)	Return self % value.
__mul__(other)	Return self * value.
__ne__(other)	Return self != other.
__neg__()	Return - self.
__pos__()	Return + self.
__pow__(other[, mod])	Return pow(self, value, mod).
__radd__(other)	Return value + self.
__rdivmod__(other)	Return divmod(value, self).
__repr__()	Return a string representation of the temperature.
__rfloordiv__(other)	Return value // self.
__rmod__(other)	Return value % self.
__rmul__(other)	Return value * self.
__round__([ndigits])	Rounds self to ndigits decimal places, defaulting to 0.
__rpow__(other[, mod])	Return pow(value, self, mod).
__rsub__(other)	Return value - self.
__rtruediv__(other)	Return value / self.
__str__()	Return the temperature as a string.
__sub__(other)	Return value - self.
__truediv__(other)	Return self / value.
__trunc__()	trunc(self): Truncates self to an Integral.
as_integer_ratio()	rtype Tuple[int, int]
conjugate()	Conjugate is a no-op for Reals.
fromhex(_UserFloat__s)	rtype ~_F
hex()	rtype str
is_integer()	rtype bool

Attributes:

__slots__
_abc_impl
imag	Real numbers have no imaginary component.
real	Real numbers are their real component.

__abs__()

Return abs(self).

Return type

~_F

__add__(other)

Return self + value.

Return type

~_F

__bool__()

True if self != 0. Called for bool(self).

Return type

bool

__ceil__()

Finds the least Integral >= self.

__complex__()

complex(self) == complex(float(self), 0)

__divmod__(other)

Return divmod(self, value).

Return type

Tuple[~_F, ~_F]

__eq__(other)

Return self == other.

Return type

bool

__float__()

Return float(self).

Return type

float

__floor__()

Finds the greatest Integral <= self.

__floordiv__(other)

Return self // value.

Return type

~_F

__ge__(other)

Return self >= other.

Return type

bool

__gt__(other)

Return self > other.

Return type

bool

__int__()

Return int(self).

Return type

int

__le__(other)

Return self <= other.

Return type

bool

__lt__(other)

Return self < other.

Return type

bool

__mod__(other)

Return self % value.

Return type

~_F

__mul__(other)

Return self * value.

Return type

~_F

__ne__(other)

Return self != other.

Return type

bool

__neg__()

Return - self.

Return type

~_F

__pos__()

Return + self.

Return type

~_F

__pow__(other, mod=None)

Return pow(self, value, mod).

Return type

~_F

__radd__(other)

Return value + self.

Return type

~_F

__rdivmod__(other)

Return divmod(value, self).

Return type

Tuple[~_F, ~_F]

__repr__()

Return a string representation of the temperature.

Return type

str

__rfloordiv__(other)

Return value // self.

Return type

~_F

__rmod__(other)

Return value % self.

Return type

~_F

__rmul__(other)

Return value * self.

Return type

~_F

__round__(ndigits=None)

Rounds self to ndigits decimal places, defaulting to 0.

If ndigits is omitted or None, returns an Integral, otherwise returns a Real. Rounds half toward even.

Return type

Union[int, float]

__rpow__(other, mod=None)

Return pow(value, self, mod).

Return type

~_F

__rsub__(other)

Return value - self.

Return type

~_F

__rtruediv__(other)

Return value / self.

Return type

~_F

__slots__ = ()

__str__()

Return the temperature as a string.

Return type

str

__sub__(other)

Return value - self.

Return type

~_F

__truediv__(other)

Return self / value.

Return type

~_F

__trunc__()

trunc(self): Truncates self to an Integral.

Returns an Integral i such that:

• i>0 iff self>0;

• abs(i) <= abs(self);

• for any Integral j satisfying the first two conditions, abs(i) >= abs(j) [i.e. i has “maximal” abs among those].

i.e. “truncate towards 0”.

Return type

int

_abc_impl = <_abc_data object>

as_integer_ratio()

Return type

Tuple[int, int]

conjugate()

Conjugate is a no-op for Reals.

classmethod fromhex(_UserFloat__s)

Return type

~_F

hex()

Return type

str

property imag

Real numbers have no imaginary component.

is_integer()

Return type

bool

property real

Real numbers are their real component.

class TemperatureArray(data, dtype=None, copy=False)

Bases: BaseArray

Holder for Temperatures.

TemperatureArray is a container for Temperatures. It satisfies pandas’ extension array interface, and so can be stored inside pandas.Series and pandas.DataFrame.

Attributes:

T	rtype ExtensionArray
__array_priority__
_can_hold_na
_dtype
_itemsize
_parser
_typ
can_hold_na
dtype	The dtype for this extension array, CelsiusType.
na_value	The missing value.
nbytes	The number of bytes needed to store this object in memory.
ndim
shape	Return a tuple of the array dimensions.
size	The number of elements in the array.

Methods:

__abs__()
__add__(other)
__and__(other)
__contains__(item)	Return for item in self.
__delitem__(where)
__divmod__(other)
__eq__(other)	Return for self == other (element-wise equality).
__floordiv__(other)
__ge__(other)	Return self>=value.
__getitem__(item)	Select a subset of self.
__gt__(other)	Return self>value.
__iadd__(other)
__iand__(other)
__ifloordiv__(other)
__ilshift__(other)
__imatmul__(other)
__imod__(other)
__imul__(other)
__invert__()
__ior__(other)
__ipow__(other)
__irshift__(other)
__isub__(other)
__iter__()	Iterate over elements of the array.
__itruediv__(other)
__ixor__(other)
__le__(other)	Return self<=value.
__len__()	Returns the length of this array.
__lshift__(other)
__lt__(other)	Return self<value.
__matmul__(other)
__mod__(other)
__mul__(other)
__ne__(other)	Return for self != other (element-wise in-equality).
__neg__()
__or__(other)
__pos__()
__pow__(other)
__radd__(other)
__rand__(other)
__rdivmod__(other)
__repr__()	Return repr(self).
__rfloordiv__(other)
__rlshift__(other)
__rmatmul__(other)
__rmod__(other)
__rmul__(other)
__ror__(other)
__rpow__(other)
__rrshift__(other)
__rshift__(other)
__rsub__(other)
__rtruediv__(other)
__rxor__(other)
__setitem__(key, value)	Set one or more values inplace.
__sub__(other)
__truediv__(other)
__xor__(other)
_concat_same_type(to_concat)	Concatenate multiple arrays.
_format_values()
_formatter([boxed])	Formatting function for scalar values.
_formatting_values()
_from_factorized(values, original)	Reconstruct an ExtensionArray after factorization.
_from_ndarray(data[, copy])	Zero-copy construction of a BaseArray from an ndarray.
_from_sequence(scalars[, dtype, copy])	Construct a new ExtensionArray from a sequence of scalars.
_from_sequence_of_strings(strings, *[, …])	Construct a new ExtensionArray from a sequence of strings.
_isstringslice(where)
_reduce(name, *[, skipna])	Return a scalar result of performing the reduction operation.
_values_for_argsort()	Return values for sorting.
_values_for_factorize()	Return an array and missing value suitable for factorization.
append(value)	Append a value to this TemperatureArray.
argmax()	Return the index of maximum value.
argmin()	Return the index of minimum value.
argsort([ascending, kind])	Return the indices that would sort this array.
astype(dtype[, copy])	Returns the array with its values as the given dtype.
copy([deep])	Return a copy of the array.
dropna()	Return ExtensionArray without NA values.
equals(other)	Return if another array is equivalent to this array.
factorize([na_sentinel])	Encode the extension array as an enumerated type.
fillna([value, method, limit])	Fill NA/NaN values using the specified method.
isin(other)	Check whether elements of self are in other.
isna()	Indicator for whether each element is missing.
ravel([order])	Return a flattened view on this array.
repeat(repeats[, axis])	Repeat elements of a ExtensionArray.
searchsorted(value[, side, sorter])	Find indices where elements should be inserted to maintain order.
setitem(indexer, value)	Set the ‘value’ inplace.
shift([periods, fill_value])	Shift values by desired number.
take(indices[, allow_fill, fill_value])	Take elements from an array.
to_numpy([dtype, copy, na_value])	Convert to a NumPy ndarray.
tolist()	Convert the array to a Python list.
transpose(*axes)	Return a transposed view on this array.
unique()	Compute the ExtensionArray of unique values.
view([dtype])	Return a view on the array.

property T

Return type

ExtensionArray

__abs__()

__add__(other)

__and__(other)

__array_priority__: int = 1000

__contains__(item)

Return for item in self.

Return type

bool

__delitem__(where)

__divmod__(other)

__eq__(other)

Return for self == other (element-wise equality).

__floordiv__(other)

__ge__(other)

Return self>=value.

__getitem__(item)

Select a subset of self.

Parameters

item (Union[int, slice, ndarray]) –

• int: The position in ‘self’ to get.

• slice: A slice object, where ‘start’, ‘stop’, and ‘step’ are integers or None.

• ndarray: A 1-d boolean NumPy ndarray the same length as ‘self’

Return type

scalar or ExtensionArray

Note

For scalar item, return a scalar value suitable for the array’s type. This should be an instance of self.dtype.type.

For slice key, return an instance of ExtensionArray, even if the slice is length 0 or 1.

For a boolean mask, return an instance of ExtensionArray, filtered to the values where item is True.

__gt__(other)

Return self>value.

__iadd__(other)

__iand__(other)

__ifloordiv__(other)

__ilshift__(other)

__imatmul__(other)

__imod__(other)

__imul__(other)

__invert__()

__ior__(other)

__ipow__(other)

__irshift__(other)

__isub__(other)

__iter__()

Iterate over elements of the array.

__itruediv__(other)

__ixor__(other)

__le__(other)

Return self<=value.

__len__()

Returns the length of this array.

Return type

int

__lshift__(other)

__lt__(other)

Return self<value.

__matmul__(other)

__mod__(other)

__mul__(other)

__ne__(other)

Return for self != other (element-wise in-equality).

__neg__()

__or__(other)

__pos__()

__pow__(other)

__radd__(other)

__rand__(other)

__rdivmod__(other)

__repr__()

Return repr(self).

Return type

str

__rfloordiv__(other)

__rlshift__(other)

__rmatmul__(other)

__rmod__(other)

__rmul__(other)

__ror__(other)

__rpow__(other)

__rrshift__(other)

__rshift__(other)

__rsub__(other)

__rtruediv__(other)

__rxor__(other)

__setitem__(key, value)

Set one or more values inplace.

This method is not required to satisfy the pandas extension array interface.

keyint, ndarray, or slice

When called from, e.g. Series.__setitem__, key will be one of

• scalar int

• ndarray of integers.

• boolean ndarray

• slice object

valueExtensionDtype.type, Sequence[ExtensionDtype.type], or object

value or values to be set of key.

None

__sub__(other)

__truediv__(other)

__xor__(other)

_can_hold_na = True

classmethod _concat_same_type(to_concat)

Concatenate multiple arrays.

Parameters

to_concat (Sequence[ABCExtensionArray]) – sequence of this type

Return type

ABCExtensionArray

_dtype: Type[pandas.core.dtypes.base.ExtensionDtype] = <si_unit_pandas.temperature.CelsiusType object>

_format_values()

_formatter(boxed=False)

Formatting function for scalar values.

This is used in the default ‘__repr__’. The returned formatting function receives instances of your scalar type.

boxedbool, default False

An indicated for whether or not your array is being printed within a Series, DataFrame, or Index (True), or just by itself (False). This may be useful if you want scalar values to appear differently within a Series versus on its own (e.g. quoted or not).

Callable[[Any], str]

A callable that gets instances of the scalar type and returns a string. By default, repr() is used when boxed=False and str() is used when boxed=True.

Return type

Callable[[Any], Optional[str]]

_formatting_values()

classmethod _from_factorized(values, original)

Reconstruct an ExtensionArray after factorization.

Parameters

• values (ndarray) – An integer ndarray with the factorized values.

• original (ExtensionArray) – The original ExtensionArray that factorize was called on.

See also

pandas.pandas.api.extensions.ExtensionArray.factorize()

classmethod _from_ndarray(data, copy=False)

Zero-copy construction of a BaseArray from an ndarray.

Parameters

• data (ndarray) – This should have CelsiusType._record_type dtype

• copy (bool) – Whether to copy the data. Default False.

Return type

~_A

Returns

classmethod _from_sequence(scalars, dtype=None, copy=False)

Construct a new ExtensionArray from a sequence of scalars.

Parameters

• scalars (Iterable) – Each element will be an instance of the scalar type for this array, cls.dtype.type.

• dtype (dtype, optional) – Construct for this particular dtype. This should be a Dtype compatible with the ExtensionArray. Default None.

• copy (bool) – If True, copy the underlying data. Default False.

classmethod _from_sequence_of_strings(strings, *, dtype=None, copy=False)

Construct a new ExtensionArray from a sequence of strings.

New in version 0.24.0.

stringsSequence

Each element will be an instance of the scalar type for this array, cls.dtype.type.

dtypedtype, optional

Construct for this particular dtype. This should be a Dtype compatible with the ExtensionArray.

copybool, default False

If True, copy the underlying data.

ExtensionArray

_isstringslice(where)

_itemsize: int = 16

property _parser

_reduce(name, *, skipna=True, **kwargs)

Return a scalar result of performing the reduction operation.

namestr

Name of the function, supported values are: { any, all, min, max, sum, mean, median, prod, std, var, sem, kurt, skew }.

skipnabool, default True

If True, skip NaN values.

**kwargs

Additional keyword arguments passed to the reduction function. Currently, ddof is the only supported kwarg.

scalar

TypeError : subclass does not define reductions

_typ = 'extension'

_values_for_argsort()

Return values for sorting.

ndarray

The transformed values should maintain the ordering between values within the array.

ExtensionArray.argsort : Return the indices that would sort this array.

Return type

ndarray

_values_for_factorize()

Return an array and missing value suitable for factorization.

values : ndarray

An array suitable for factorization. This should maintain order and be a supported dtype (Float64, Int64, UInt64, String, Object). By default, the extension array is cast to object dtype.

na_valueobject

The value in values to consider missing. This will be treated as NA in the factorization routines, so it will be coded as na_sentinel and not included in uniques. By default, np.nan is used.

The values returned by this method are also used in pandas.util.hash_pandas_object().

Return type

Tuple[ndarray, Any]

append(value)

Append a value to this TemperatureArray.

Parameters

value (Union[float, str, Sequence[Union[float, str]]])

argmax()

Return the index of maximum value.

In case of multiple occurrences of the maximum value, the index corresponding to the first occurrence is returned.

int

ExtensionArray.argmin

argmin()

Return the index of minimum value.

In case of multiple occurrences of the minimum value, the index corresponding to the first occurrence is returned.

int

ExtensionArray.argmax

argsort(ascending=True, kind='quicksort', *args, **kwargs)

Return the indices that would sort this array.

Parameters

• ascending (bool) – Whether the indices should result in an ascending or descending sort. Default True.

• kind (Union[Literal['quicksort'], Literal['mergesort'], Literal['heapsort']]) – {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional Sorting algorithm. Default 'quicksort'.

*args and **kwargs are passed through to numpy.argsort().

Return type

ndarray

Returns

Array of indices that sort self. If NaN values are contained, NaN values are placed at the end.

See also

numpy.argsort: Sorting implementation used internally.

astype(dtype, copy=True)

Returns the array with its values as the given dtype.

Parameters

• dtype

• copy – If True, returns a copy of the array. Default True.

can_hold_na: bool = True

copy(deep=False)

Return a copy of the array.

Parameters

deep (bool) – Default False.

Returns

Return type

ABCExtensionArray

data

Type:    ndarray

dropna()

Return ExtensionArray without NA values.

valid : ExtensionArray

property dtype

The dtype for this extension array, CelsiusType.

equals(other)

Return if another array is equivalent to this array.

Equivalent means that both arrays have the same shape and dtype, and all values compare equal. Missing values in the same location are considered equal (in contrast with normal equality).

otherExtensionArray

Array to compare to this Array.

boolean

Whether the arrays are equivalent.

Return type

bool

factorize(na_sentinel=- 1)

Encode the extension array as an enumerated type.

na_sentinelint, default -1

Value to use in the codes array to indicate missing values.

codesndarray

An integer NumPy array that’s an indexer into the original ExtensionArray.

uniquesExtensionArray

An ExtensionArray containing the unique values of self.

Note

uniques will not contain an entry for the NA value of the ExtensionArray if there are any missing values present in self.

factorize : Top-level factorize method that dispatches here.

pandas.factorize() offers a sort keyword as well.

Return type

Tuple[ndarray, ExtensionArray]

fillna(value=None, method=None, limit=None)

Fill NA/NaN values using the specified method.

valuescalar, array-like

If a scalar value is passed it is used to fill all missing values. Alternatively, an array-like ‘value’ can be given. It’s expected that the array-like have the same length as ‘self’.

method{‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None}, default None

Method to use for filling holes in reindexed Series pad / ffill: propagate last valid observation forward to next valid backfill / bfill: use NEXT valid observation to fill gap.

limitint, default None

If method is specified, this is the maximum number of consecutive NaN values to forward/backward fill. In other words, if there is a gap with more than this number of consecutive NaNs, it will only be partially filled. If method is not specified, this is the maximum number of entries along the entire axis where NaNs will be filled.

ExtensionArray

With NA/NaN filled.

isin(other)

Check whether elements of self are in other.

Comparison is done elementwise.

Parameters

other (Union[float, str, Sequence[Union[float, str]]])

Return type

ndarray

Returns

A 1-D boolean ndarray with the same length as self.

isna()

Indicator for whether each element is missing.

property na_value

The missing value.

Example:

>>> BaseArray([]).na_value
numpy.nan

property nbytes

The number of bytes needed to store this object in memory.

Return type

int

ndim: int = 1

ravel(order='C')

Return a flattened view on this array.

order : {None, ‘C’, ‘F’, ‘A’, ‘K’}, default ‘C’

ExtensionArray

• Because ExtensionArrays are 1D-only, this is a no-op.

• The “order” argument is ignored, is for compatibility with NumPy.

Return type

ExtensionArray

repeat(repeats, axis=None)

Repeat elements of a ExtensionArray.

Returns a new ExtensionArray where each element of the current ExtensionArray is repeated consecutively a given number of times.

repeatsint or array of ints

The number of repetitions for each element. This should be a non-negative integer. Repeating 0 times will return an empty ExtensionArray.

axisNone

Must be None. Has no effect but is accepted for compatibility with numpy.

repeated_arrayExtensionArray

Newly created ExtensionArray with repeated elements.

Series.repeat : Equivalent function for Series. Index.repeat : Equivalent function for Index. numpy.repeat : Similar method for numpy.ndarray. ExtensionArray.take : Take arbitrary positions.

>>> cat = pd.Categorical(['a', 'b', 'c'])
>>> cat
['a', 'b', 'c']
Categories (3, object): ['a', 'b', 'c']
>>> cat.repeat(2)
['a', 'a', 'b', 'b', 'c', 'c']
Categories (3, object): ['a', 'b', 'c']
>>> cat.repeat([1, 2, 3])
['a', 'b', 'b', 'c', 'c', 'c']
Categories (3, object): ['a', 'b', 'c']

searchsorted(value, side='left', sorter=None)

Find indices where elements should be inserted to maintain order.

New in version 0.24.0.

Find the indices into a sorted array self (a) such that, if the corresponding elements in value were inserted before the indices, the order of self would be preserved.

Assuming that self is sorted:

side	returned index i satisfies
left	self[i-1] < value <= self[i]
right	self[i-1] <= value < self[i]

valuearray_like

Values to insert into self.

side{‘left’, ‘right’}, optional

If ‘left’, the index of the first suitable location found is given. If ‘right’, return the last such index. If there is no suitable index, return either 0 or N (where N is the length of self).

sorter1-D array_like, optional

Optional array of integer indices that sort array a into ascending order. They are typically the result of argsort.

array of ints

Array of insertion points with the same shape as value.

numpy.searchsorted : Similar method from NumPy.

setitem(indexer, value)

Set the ‘value’ inplace.

property shape

Return a tuple of the array dimensions.

Return type

Tuple[int]

shift(periods=1, fill_value=None)

Shift values by desired number.

Newly introduced missing values are filled with self.dtype.na_value.

New in version 0.24.0.

periodsint, default 1

The number of periods to shift. Negative values are allowed for shifting backwards.

fill_valueobject, optional

The scalar value to use for newly introduced missing values. The default is self.dtype.na_value.

New in version 0.24.0.

ExtensionArray

Shifted.

If self is empty or periods is 0, a copy of self is returned.

If periods > len(self), then an array of size len(self) is returned, with all values filled with self.dtype.na_value.

Return type

ExtensionArray

property size

The number of elements in the array.

Return type

int

take(indices, allow_fill=False, fill_value=None)

Take elements from an array.

indicessequence of int

Indices to be taken.

allow_fillbool, default False

How to handle negative values in indices.

• False: negative values in indices indicate positional indices from the right (the default). This is similar to numpy.take().

• True: negative values in indices indicate missing values. These values are set to fill_value. Any other other negative values raise a ValueError.

fill_valueany, optional

Fill value to use for NA-indices when allow_fill is True. This may be None, in which case the default NA value for the type, self.dtype.na_value, is used.

For many ExtensionArrays, there will be two representations of fill_value: a user-facing “boxed” scalar, and a low-level physical NA value. fill_value should be the user-facing version, and the implementation should handle translating that to the physical version for processing the take if necessary.

ExtensionArray

IndexError

When the indices are out of bounds for the array.

ValueError

When indices contains negative values other than -1 and allow_fill is True.

numpy.take : Take elements from an array along an axis. api.extensions.take : Take elements from an array.

ExtensionArray.take is called by Series.__getitem__, .loc, iloc, when indices is a sequence of values. Additionally, it’s called by Series.reindex(), or any other method that causes realignment, with a fill_value.

Here’s an example implementation, which relies on casting the extension array to object dtype. This uses the helper method pandas.api.extensions.take().

def take(self, indices, allow_fill=False, fill_value=None):
    from pandas.core.algorithms import take

    # If the ExtensionArray is backed by an ndarray, then
    # just pass that here instead of coercing to object.
    data = self.astype(object)

    if allow_fill and fill_value is None:
        fill_value = self.dtype.na_value

    # fill value should always be translated from the scalar
    # type for the array, to the physical storage type for
    # the data, before passing to take.

    result = take(data, indices, fill_value=fill_value,
                  allow_fill=allow_fill)
    return self._from_sequence(result, dtype=self.dtype)

to_numpy(dtype=None, copy=False, na_value=<object object>)

Convert to a NumPy ndarray.

New in version 1.0.0.

This is similar to numpy.asarray(), but may provide additional control over how the conversion is done.

dtypestr or numpy.dtype, optional

The dtype to pass to numpy.asarray().

copybool, default False

Whether to ensure that the returned value is a not a view on another array. Note that copy=False does not ensure that to_numpy() is no-copy. Rather, copy=True ensure that a copy is made, even if not strictly necessary.

na_valueAny, optional

The value to use for missing values. The default value depends on dtype and the type of the array.

numpy.ndarray

Return type

ndarray

tolist()

Convert the array to a Python list.

Return type

List

transpose(*axes)

Return a transposed view on this array.

Because ExtensionArrays are always 1D, this is a no-op. It is included for compatibility with np.ndarray.

Return type

ExtensionArray

unique()

Compute the ExtensionArray of unique values.

uniques : ExtensionArray

Return type

ExtensionArray

view(dtype=None)

Return a view on the array.

dtypestr, np.dtype, or ExtensionDtype, optional

Default None.

ExtensionArray or np.ndarray

A view on the ExtensionArray’s data.

Return type

~ArrayLike

to_temperature(values)

Convert values to a TemperatureArray.

Parameters

values (Union[float, str, Sequence[Union[float, str]]])

Return type

TemperatureArray

si_unit_pandas.base

Base functionality.

Classes:

NumPyBackedExtensionArrayMixin()

Mixin for pandas extension backed by a numpy array.

class NumPyBackedExtensionArrayMixin

Bases: ExtensionArray

Mixin for pandas extension backed by a numpy array.

Attributes:

T	rtype ExtensionArray
_can_hold_na
_typ
dtype	The dtype for this extension array, CelsiusType.
nbytes	The number of bytes needed to store this object in memory.
ndim	Extension Arrays are only allowed to be 1-dimensional.
shape	Return a tuple of the array dimensions.
size	The number of elements in the array.

Methods:

__contains__(item)	Return for item in self.
__eq__(other)	Return for self == other (element-wise equality).
__getitem__(item)	Select a subset of self.
__iter__()	Iterate over elements of the array.
__len__()	Returns the length of this array.
__ne__(other)	Return for self != other (element-wise in-equality).
__repr__()	Return repr(self).
__setitem__(key, value)	Set one or more values inplace.
_concat_same_type(to_concat)	Concatenate multiple arrays.
_formatter([boxed])	Formatting function for scalar values.
_formatting_values()
_from_factorized(values, original)	Reconstruct an ExtensionArray after factorization.
_from_sequence(scalars[, dtype, copy])	Construct a new ExtensionArray from a sequence of scalars.
_from_sequence_of_strings(strings, *[, …])	Construct a new ExtensionArray from a sequence of strings.
_reduce(name, *[, skipna])	Return a scalar result of performing the reduction operation.
_values_for_argsort()	Return values for sorting.
_values_for_factorize()	Return an array and missing value suitable for factorization.
argmax()	Return the index of maximum value.
argmin()	Return the index of minimum value.
argsort([ascending, kind])	Return the indices that would sort this array.
astype(dtype[, copy])	Cast to a NumPy array with ‘dtype’.
copy([deep])	Return a copy of the array.
dropna()	Return ExtensionArray without NA values.
equals(other)	Return if another array is equivalent to this array.
factorize([na_sentinel])	Encode the extension array as an enumerated type.
fillna([value, method, limit])	Fill NA/NaN values using the specified method.
isna()	A 1-D array indicating if each value is missing.
ravel([order])	Return a flattened view on this array.
repeat(repeats[, axis])	Repeat elements of a ExtensionArray.
searchsorted(value[, side, sorter])	Find indices where elements should be inserted to maintain order.
setitem(indexer, value)	Set the ‘value’ inplace.
shift([periods, fill_value])	Shift values by desired number.
take(indices, *[, allow_fill, fill_value])	Take elements from an array.
to_numpy([dtype, copy, na_value])	Convert to a NumPy ndarray.
tolist()	Convert the array to a Python list.
transpose(*axes)	Return a transposed view on this array.
unique()	Compute the ExtensionArray of unique values.
view([dtype])	Return a view on the array.

property T

Return type

ExtensionArray

__contains__(item)

Return for item in self.

Return type

bool

__eq__(other)

Return for self == other (element-wise equality).

Return type

~ArrayLike

__getitem__(item)

Select a subset of self.

itemint, slice, or ndarray

• int: The position in ‘self’ to get.

• slice: A slice object, where ‘start’, ‘stop’, and ‘step’ are integers or None

• ndarray: A 1-d boolean NumPy ndarray the same length as ‘self’

item : scalar or ExtensionArray

For scalar item, return a scalar value suitable for the array’s type. This should be an instance of self.dtype.type.

For slice key, return an instance of ExtensionArray, even if the slice is length 0 or 1.

For a boolean mask, return an instance of ExtensionArray, filtered to the values where item is True.

Return type

Union[ExtensionArray, Any]

__iter__()

Iterate over elements of the array.

__len__()

Returns the length of this array.

Return type

int

__ne__(other)

Return for self != other (element-wise in-equality).

Return type

~ArrayLike

__repr__()

Return repr(self).

Return type

str

__setitem__(key, value)

Set one or more values inplace.

This method is not required to satisfy the pandas extension array interface.

keyint, ndarray, or slice

When called from, e.g. Series.__setitem__, key will be one of

• scalar int

• ndarray of integers.

• boolean ndarray

• slice object

valueExtensionDtype.type, Sequence[ExtensionDtype.type], or object

value or values to be set of key.

None

_can_hold_na = True

classmethod _concat_same_type(to_concat)

Concatenate multiple arrays.

Parameters

to_concat (Sequence[ABCExtensionArray]) – sequence of this type

Return type

ABCExtensionArray

_dtype

Type:    Type[ExtensionDtype]

_formatter(boxed=False)

Formatting function for scalar values.

This is used in the default ‘__repr__’. The returned formatting function receives instances of your scalar type.

boxedbool, default False

An indicated for whether or not your array is being printed within a Series, DataFrame, or Index (True), or just by itself (False). This may be useful if you want scalar values to appear differently within a Series versus on its own (e.g. quoted or not).

Callable[[Any], str]

A callable that gets instances of the scalar type and returns a string. By default, repr() is used when boxed=False and str() is used when boxed=True.

Return type

Callable[[Any], Optional[str]]

_formatting_values()

classmethod _from_factorized(values, original)

Reconstruct an ExtensionArray after factorization.

Parameters

• values (ndarray) – An integer ndarray with the factorized values.

• original (ExtensionArray) – The original ExtensionArray that factorize was called on.

See also

pandas.pandas.api.extensions.ExtensionArray.factorize()

classmethod _from_sequence(scalars, dtype=None, copy=False)

Construct a new ExtensionArray from a sequence of scalars.

Parameters

• scalars (Iterable) – Each element will be an instance of the scalar type for this array, cls.dtype.type.

• dtype (dtype, optional) – Construct for this particular dtype. This should be a Dtype compatible with the ExtensionArray. Default None.

• copy (bool) – If True, copy the underlying data. Default False.

classmethod _from_sequence_of_strings(strings, *, dtype=None, copy=False)

Construct a new ExtensionArray from a sequence of strings.

New in version 0.24.0.

stringsSequence

Each element will be an instance of the scalar type for this array, cls.dtype.type.

dtypedtype, optional

Construct for this particular dtype. This should be a Dtype compatible with the ExtensionArray.

copybool, default False

If True, copy the underlying data.

ExtensionArray

_reduce(name, *, skipna=True, **kwargs)

Return a scalar result of performing the reduction operation.

namestr

Name of the function, supported values are: { any, all, min, max, sum, mean, median, prod, std, var, sem, kurt, skew }.

skipnabool, default True

If True, skip NaN values.

**kwargs

Additional keyword arguments passed to the reduction function. Currently, ddof is the only supported kwarg.

scalar

TypeError : subclass does not define reductions

_typ = 'extension'

_values_for_argsort()

Return values for sorting.

ndarray

The transformed values should maintain the ordering between values within the array.

ExtensionArray.argsort : Return the indices that would sort this array.

Return type

ndarray

_values_for_factorize()

Return an array and missing value suitable for factorization.

values : ndarray

An array suitable for factorization. This should maintain order and be a supported dtype (Float64, Int64, UInt64, String, Object). By default, the extension array is cast to object dtype.

na_valueobject

The value in values to consider missing. This will be treated as NA in the factorization routines, so it will be coded as na_sentinel and not included in uniques. By default, np.nan is used.

The values returned by this method are also used in pandas.util.hash_pandas_object().

Return type

Tuple[ndarray, Any]

argmax()

Return the index of maximum value.

In case of multiple occurrences of the maximum value, the index corresponding to the first occurrence is returned.

int

ExtensionArray.argmin

argmin()

Return the index of minimum value.

In case of multiple occurrences of the minimum value, the index corresponding to the first occurrence is returned.

int

ExtensionArray.argmax

argsort(ascending=True, kind='quicksort', *args, **kwargs)

Return the indices that would sort this array.

Parameters

• ascending (bool) – Whether the indices should result in an ascending or descending sort. Default True.

• kind (Union[Literal['quicksort'], Literal['mergesort'], Literal['heapsort']]) – {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional Sorting algorithm. Default 'quicksort'.

*args and **kwargs are passed through to numpy.argsort().

Return type

ndarray

Returns

Array of indices that sort self. If NaN values are contained, NaN values are placed at the end.

See also

numpy.argsort: Sorting implementation used internally.

astype(dtype, copy=True)

Cast to a NumPy array with ‘dtype’.

dtypestr or dtype

Typecode or data-type to which the array is cast.

copybool, default True

Whether to copy the data, even if not necessary. If False, a copy is made only if the old dtype does not match the new dtype.

arrayndarray

NumPy ndarray with ‘dtype’ for its dtype.

copy(deep=False)

Return a copy of the array.

Parameters

deep (bool) – Default False.

Returns

Return type

ABCExtensionArray

dropna()

Return ExtensionArray without NA values.

valid : ExtensionArray

property dtype

The dtype for this extension array, CelsiusType.

equals(other)

Return if another array is equivalent to this array.

Equivalent means that both arrays have the same shape and dtype, and all values compare equal. Missing values in the same location are considered equal (in contrast with normal equality).

otherExtensionArray

Array to compare to this Array.

boolean

Whether the arrays are equivalent.

Return type

bool

factorize(na_sentinel=- 1)

Encode the extension array as an enumerated type.

na_sentinelint, default -1

Value to use in the codes array to indicate missing values.

codesndarray

An integer NumPy array that’s an indexer into the original ExtensionArray.

uniquesExtensionArray

An ExtensionArray containing the unique values of self.

Note

uniques will not contain an entry for the NA value of the ExtensionArray if there are any missing values present in self.

factorize : Top-level factorize method that dispatches here.

pandas.factorize() offers a sort keyword as well.

Return type

Tuple[ndarray, ExtensionArray]

fillna(value=None, method=None, limit=None)

Fill NA/NaN values using the specified method.

valuescalar, array-like

If a scalar value is passed it is used to fill all missing values. Alternatively, an array-like ‘value’ can be given. It’s expected that the array-like have the same length as ‘self’.

method{‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None}, default None

Method to use for filling holes in reindexed Series pad / ffill: propagate last valid observation forward to next valid backfill / bfill: use NEXT valid observation to fill gap.

limitint, default None

If method is specified, this is the maximum number of consecutive NaN values to forward/backward fill. In other words, if there is a gap with more than this number of consecutive NaNs, it will only be partially filled. If method is not specified, this is the maximum number of entries along the entire axis where NaNs will be filled.

ExtensionArray

With NA/NaN filled.

isna()

A 1-D array indicating if each value is missing.

na_valuesUnion[np.ndarray, ExtensionArray]

In most cases, this should return a NumPy ndarray. For exceptional cases like SparseArray, where returning an ndarray would be expensive, an ExtensionArray may be returned.

If returning an ExtensionArray, then

• na_values._is_boolean should be True

• na_values should implement ExtensionArray._reduce()

• na_values.any and na_values.all should be implemented

Return type

~ArrayLike

property nbytes

The number of bytes needed to store this object in memory.

Return type

int

property ndim

Extension Arrays are only allowed to be 1-dimensional.

Return type

int

ravel(order='C')

Return a flattened view on this array.

order : {None, ‘C’, ‘F’, ‘A’, ‘K’}, default ‘C’

ExtensionArray

• Because ExtensionArrays are 1D-only, this is a no-op.

• The “order” argument is ignored, is for compatibility with NumPy.

Return type

ExtensionArray

repeat(repeats, axis=None)

Repeat elements of a ExtensionArray.

Returns a new ExtensionArray where each element of the current ExtensionArray is repeated consecutively a given number of times.

repeatsint or array of ints

The number of repetitions for each element. This should be a non-negative integer. Repeating 0 times will return an empty ExtensionArray.

axisNone

Must be None. Has no effect but is accepted for compatibility with numpy.

repeated_arrayExtensionArray

Newly created ExtensionArray with repeated elements.

Series.repeat : Equivalent function for Series. Index.repeat : Equivalent function for Index. numpy.repeat : Similar method for numpy.ndarray. ExtensionArray.take : Take arbitrary positions.

>>> cat = pd.Categorical(['a', 'b', 'c'])
>>> cat
['a', 'b', 'c']
Categories (3, object): ['a', 'b', 'c']
>>> cat.repeat(2)
['a', 'a', 'b', 'b', 'c', 'c']
Categories (3, object): ['a', 'b', 'c']
>>> cat.repeat([1, 2, 3])
['a', 'b', 'b', 'c', 'c', 'c']
Categories (3, object): ['a', 'b', 'c']

searchsorted(value, side='left', sorter=None)

Find indices where elements should be inserted to maintain order.

New in version 0.24.0.

Find the indices into a sorted array self (a) such that, if the corresponding elements in value were inserted before the indices, the order of self would be preserved.

Assuming that self is sorted:

side	returned index i satisfies
left	self[i-1] < value <= self[i]
right	self[i-1] <= value < self[i]

valuearray_like

Values to insert into self.

side{‘left’, ‘right’}, optional

If ‘left’, the index of the first suitable location found is given. If ‘right’, return the last such index. If there is no suitable index, return either 0 or N (where N is the length of self).

sorter1-D array_like, optional

Optional array of integer indices that sort array a into ascending order. They are typically the result of argsort.

array of ints

Array of insertion points with the same shape as value.

numpy.searchsorted : Similar method from NumPy.

setitem(indexer, value)

Set the ‘value’ inplace.

property shape

Return a tuple of the array dimensions.

Return type

Tuple[int]

shift(periods=1, fill_value=None)

Shift values by desired number.

Newly introduced missing values are filled with self.dtype.na_value.

New in version 0.24.0.

periodsint, default 1

The number of periods to shift. Negative values are allowed for shifting backwards.

fill_valueobject, optional

The scalar value to use for newly introduced missing values. The default is self.dtype.na_value.

New in version 0.24.0.

ExtensionArray

Shifted.

If self is empty or periods is 0, a copy of self is returned.

If periods > len(self), then an array of size len(self) is returned, with all values filled with self.dtype.na_value.

Return type

ExtensionArray

property size

The number of elements in the array.

Return type

int

take(indices, *, allow_fill=False, fill_value=None)

Take elements from an array.

indicessequence of int

Indices to be taken.

allow_fillbool, default False

How to handle negative values in indices.

• False: negative values in indices indicate positional indices from the right (the default). This is similar to numpy.take().

• True: negative values in indices indicate missing values. These values are set to fill_value. Any other other negative values raise a ValueError.

fill_valueany, optional

Fill value to use for NA-indices when allow_fill is True. This may be None, in which case the default NA value for the type, self.dtype.na_value, is used.

For many ExtensionArrays, there will be two representations of fill_value: a user-facing “boxed” scalar, and a low-level physical NA value. fill_value should be the user-facing version, and the implementation should handle translating that to the physical version for processing the take if necessary.

ExtensionArray

IndexError

When the indices are out of bounds for the array.

ValueError

When indices contains negative values other than -1 and allow_fill is True.

numpy.take : Take elements from an array along an axis. api.extensions.take : Take elements from an array.

ExtensionArray.take is called by Series.__getitem__, .loc, iloc, when indices is a sequence of values. Additionally, it’s called by Series.reindex(), or any other method that causes realignment, with a fill_value.

Here’s an example implementation, which relies on casting the extension array to object dtype. This uses the helper method pandas.api.extensions.take().

def take(self, indices, allow_fill=False, fill_value=None):
    from pandas.core.algorithms import take

    # If the ExtensionArray is backed by an ndarray, then
    # just pass that here instead of coercing to object.
    data = self.astype(object)

    if allow_fill and fill_value is None:
        fill_value = self.dtype.na_value

    # fill value should always be translated from the scalar
    # type for the array, to the physical storage type for
    # the data, before passing to take.

    result = take(data, indices, fill_value=fill_value,
                  allow_fill=allow_fill)
    return self._from_sequence(result, dtype=self.dtype)

Return type

ExtensionArray

to_numpy(dtype=None, copy=False, na_value=<object object>)

Convert to a NumPy ndarray.

New in version 1.0.0.

This is similar to numpy.asarray(), but may provide additional control over how the conversion is done.

dtypestr or numpy.dtype, optional

The dtype to pass to numpy.asarray().

copybool, default False

Whether to ensure that the returned value is a not a view on another array. Note that copy=False does not ensure that to_numpy() is no-copy. Rather, copy=True ensure that a copy is made, even if not strictly necessary.

na_valueAny, optional

The value to use for missing values. The default value depends on dtype and the type of the array.

numpy.ndarray

Return type

ndarray

tolist()

Convert the array to a Python list.

Return type

List

transpose(*axes)

Return a transposed view on this array.

Because ExtensionArrays are always 1D, this is a no-op. It is included for compatibility with np.ndarray.

Return type

ExtensionArray

unique()

Compute the ExtensionArray of unique values.

uniques : ExtensionArray

Return type

ExtensionArray

view(dtype=None)

Return a view on the array.

dtypestr, np.dtype, or ExtensionDtype, optional

Default None.

ExtensionArray or np.ndarray

A view on the ExtensionArray’s data.

Return type

~ArrayLike

si_unit_pandas.parser

si_unit_pandas.temperature_array