]jCtSrSSKJr SSKrSSKJrJr SSKrSSKJ r SSK J r \(aSSK J r SSKJr SS KJr SS KJr "S S 5r"S S5rSSS4SSjjr"SS5r\rSSjrSr\ "S5SSj5rSr\ "S5SSj5rSr\ "S5SSj5rg) z accessor.py contains base classes for implementing accessor properties that can be mixed into or pinned onto other pandas classes. ) annotationsN) TYPE_CHECKINGfinal) set_module)find_stack_level)Callable)TypeTIndex)NDFramec|^\rSrSr%\"5rS\S'\"5rS\S'\ S Sj5r S Sjr S U4Sjjr S r U=r$) DirNamesMixinset[str] _accessorszfrozenset[str] _hidden_attrsc4URUR-$)z* Delete unwanted __dir__ for this object. )rr)selfs Q/home/mande/repo/quber/.venv/lib/python3.13/site-packages/pandas/core/accessor.py_dir_deletionsDirNamesMixin._dir_deletions#s !3!333cjURVs1sHn[X5(dMUiM sn$s snf)z) Add additional __dir__ for this object. )rhasattr)raccessors r_dir_additionsDirNamesMixin._dir_additions*s'*.TXGD[[TU] 55nXR5- UR 5-n[ U5$)zX Provide method name lookup and completion. Notes ----- Only provide 'public' methods. )setsuper__dir__rrsorted)rrv __class__s rr!DirNamesMixin.__dir__0s?" #&&((D,?,?,A Abzr)returnr)r' list[str])__name__ __module__ __qualname____firstlineno__rr__annotations__ frozensetrrrrr!__static_attributes__ __classcell__)r$s@rrrs=5J $-KM>/ 4 4 U  rrcl\rSrSrSrS SjrS SjrS Sjr\SSS4SS jj5r S r g )PandasDelegate=z8 Abstract base class for delegating methods/properties. c[SU35e)NzYou cannot access the property  TypeErrorrnameargskwargss r_delegate_property_get%PandasDelegate._delegate_property_getBs9$@AArc [SUS35e)Nz The property z cannot be setr5)rr8valuer9r:s r_delegate_property_set%PandasDelegate._delegate_property_setEs-v^<==rc[SU35e)NzYou cannot call method r5r7s r_delegate_methodPandasDelegate._delegate_methodHs1$899rFcU$Nr&xs rPandasDelegate.Rs1rTc^^SUU4SjjnSUU4SjjnUH\n U(d[TT"U 5S5cM US:Xa U"U 5n OU"U 5n U(d[X 5(aMP[X U 5 M^ g)a\ Add accessors to cls from the delegate class. Parameters ---------- cls Class to add the methods/properties to. delegate Class to get methods/properties and docstrings. accessors : list of str List of accessors to add. typ : {'property', 'method'} overwrite : bool, default False Overwrite the method/property in the target class if it exists. accessor_mapping: Callable, default lambda x: x Callable to map the delegate's function to the cls' function. raise_on_missing: bool, default True Raise if an accessor does not exist on delegate. False skips the missing accessor. c >^U4SjnU4SjnTUlTUl[UU[TT"T55RS9$)Nc&>URT5$rE)r;)rr8s r_getter[PandasDelegate._add_delegate_accessors.._create_delegator_property.._getterks22488rc(>URTU5$rE)r?)r new_valuesr8s r_setter[PandasDelegate._add_delegate_accessors.._create_delegator_property.._setterns224DDr)fgetfsetdoc)r)propertygetattr__doc__)r8rMrQaccessor_mappingdelegates` r_create_delegator_propertyJPandasDelegate._add_delegate_accessors.._create_delegator_propertyjsI 9 E $G #G H&6t&<=EE rcl>^[TT"T55n[R"U5U4Sj5nU$)Nc0>UR"T/UQ70UD6$rE)rB)rr9r:r8s rfSPandasDelegate._add_delegate_accessors.._create_delegator_method..f}s,,TCDCFCCr)rW functoolswraps)r8methodr_rYrZs` r_create_delegator_methodHPandasDelegate._add_delegate_accessors.._create_delegator_methodzs9X'7'=>F __V $ D% DHrNrVr8str)rWrsetattr) clsrZ accessorstyp overwriterYraise_on_missingr[rdr8r_s ` ` r_add_delegate_accessors&PandasDelegate._add_delegate_accessorsKss>     D$H&6t&:  1URTTTTTTS9 U$)N)rlrYrm)rn)rirYrjrZrlrmrks radd_delegate_accessors.delegate_names..add_delegate_accessorss/ ##   -- $  rr&)rZrjrkrlrYrmrxs`````` rdelegate_namesrzsP   "!rc(\rSrSrSrSSjrSrSrg)Accessoraa Custom property-like object. A descriptor for accessors. Parameters ---------- name : str Namespace that will be accessed under, e.g. ``df.foo``. accessor : cls Class with the extension methods. Notes ----- For accessor, The class's __init__ method assumes that one of ``Series``, ``DataFrame`` or ``Index`` as the single argument ``data``. cXlX lgrE)_name _accessor)rr8rs r__init__Accessor.__init__s  !rcBUc UR$URU5$rE)r)robjris r__get__Accessor.__get__s ;>> !~~c""r)rrNrp)r)r*r+r,rXrrr/r&rrr|r|s&"#rr|c^^SUU4SjjnU$)a% Register a custom accessor on objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for pandas objects (DataFrame, Series, or Index). The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single object * raises an AttributeError if the object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. c >[TT5(a/[R"SU<ST<ST<S3[[ 5S9 [ TT[ TU55 TRRT5 U$)Nzregistration of accessor z under name z for type z: is overriding a preexisting attribute with the same name.) stacklevel) rwarningswarn UserWarningrrhr|radd)rrir8s r decorator%_register_accessor..decoratorsq 3   MM+H<|(*SG,01+-   T8D(34 4 r)rr r'r r&)r8rirs`` r_register_accessorrsZ   ra An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_dataframe_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(pandas_obj[col].dtype == 'int64' for col in pandas_obj.columns): ... raise AttributeError("All columns must contain integer values only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() ... >>> df = pd.DataFrame([[1, 2], ['x', 'y']]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: All columns must contain integer values only. >>> df = pd.DataFrame([[1, 2], [3, 4]]) >>> df.int_accessor.sum() 0 4 1 6 dtype: int64zpandas.api.extensionsc$SSKJn [X5$)a0 Register a custom accessor on DataFrame objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for DataFrame. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single DataFrame object * raises an AttributeError if the DataFrame object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_dataframe_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all( ... pandas_obj[col].dtype == "int64" for col in pandas_obj.columns ... ): ... raise AttributeError("All columns must contain integer values only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() >>> df = pd.DataFrame([[1, 2], ["x", "y"]]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: All columns must contain integer values only. >>> df = pd.DataFrame([[1, 2], [3, 4]]) >>> df.int_accessor.sum() 0 4 1 6 dtype: int64 r) DataFrame)pandasrr)r8rs rregister_dataframe_accessorrEsH! d ..ra An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_series_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not pandas_obj.dtype == 'int64': ... raise AttributeError("The series must contain integer data only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() ... >>> df = pd.Series([1, 2, 'x']) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: The series must contain integer data only. >>> df = pd.Series([1, 2, 3]) >>> df.int_accessor.sum() 6c$SSKJn [X5$)a Register a custom accessor on Series objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for Series. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single Series object * raises an AttributeError if the Series object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_series_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not pandas_obj.dtype == "int64": ... raise AttributeError("The series must contain integer data only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() >>> df = pd.Series([1, 2, "x"]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: The series must contain integer data only. >>> df = pd.Series([1, 2, 3]) >>> df.int_accessor.sum() 6 r)Series)rrr)r8rs rregister_series_accessorrs@ d ++ra[ An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_index_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(isinstance(x, int) for x in pandas_obj): ... raise AttributeError("The index must only be an integer value") ... self._obj = pandas_obj ... ... def even(self): ... return [x for x in self._obj if x % 2 == 0] >>> df = pd.DataFrame.from_dict( ... {"row1": {"1": 1, "2": "a"}, "row2": {"1": 2, "2": "b"}}, orient="index" ... ) >>> df.index.int_accessor Traceback (most recent call last): ... AttributeError: The index must only be an integer value. >>> df = pd.DataFrame( ... {"col1": [1, 2, 3, 4], "col2": ["a", "b", "c", "d"]}, index=[1, 2, 5, 8] ... ) >>> df.index.int_accessor.even() [2, 8]c$SSKJn [X5$)a} Register a custom accessor on Index objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for Index. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single Index object * raises an AttributeError if the Index object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_index_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(isinstance(x, int) for x in pandas_obj): ... raise AttributeError("The index must only be an integer value") ... self._obj = pandas_obj ... ... def even(self): ... return [x for x in self._obj if x % 2 == 0] >>> df = pd.DataFrame.from_dict( ... {"row1": {"1": 1, "2": "a"}, "row2": {"1": 2, "2": "b"}}, orient="index" ... ) >>> df.index.int_accessor Traceback (most recent call last): ... AttributeError: The index must only be an integer value. >>> df = pd.DataFrame( ... {"col1": [1, 2, 3, 4], "col2": ["a", "b", "c", "d"]}, index=[1, 2, 5, 8] ... ) >>> df.index.int_accessor.even() [2, 8] rr )rr r)r8r s rregister_index_accessorrsH d **r) rjr(rkrgrlrrrYrsrmrr)r8rgriztype[NDFrame | Index]r'Callable[[TypeT], TypeT])r8rgr'r) rX __future__rratypingrrrpandas.util._decoratorsrpandas.util._exceptionsrcollections.abcrpandas._typingr rr pandas.core.genericr rr2rzr|CachedAccessorr_register_df_examplesr_register_series_examplesr_register_index_examplesrr&rrrs+#5($+