j+FxdZddlmZddlZddlmZmZddlZddlm Z ddl m Z erddl m Z ddlmZdd lmZdd lmZGd d ZGd dZdddfd+dZGddZeZd,d#Zd$Ze d%d-d&Zd'Ze d%d-d(Zd)Ze d%d-d*ZdS).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~eZdZUeZded<eZded<ed dZ d dZ d fd Z xZ S) DirNamesMixinset[str] _accessorszfrozenset[str] _hidden_attrsreturnc |j|jzS)z: Delete unwanted __dir__ for this object. )rrselfs BC:\Projects\DSCons\.venv\Lib\site-packages\pandas\core\accessor.py_dir_deletionszDirNamesMixin._dir_deletions#s !333c*fdjDS)z9 Add additional __dir__ for this object. c4h|]}t||S)hasattr).0accessorrs r z/DirNamesMixin._dir_additions...s(TTTXGD(zPandasDelegate.Rs1rT accessorsr!typ overwriteboolaccessor_mappingCallable[[str], str]raise_on_missingcdfd }dfd }|D]_} |st| d|dkr || } n || } |st|| st|| | `dS)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. r1r2c fd}fd}|_|_t||tjS)Nc.|SrA)r9)rr1s r_getterz[PandasDelegate._add_delegate_accessors.._create_delegator_property.._getterks224888rc0||SrA)r=)r new_valuesr1s r_setterz[PandasDelegate._add_delegate_accessors.._create_delegator_property.._setterns224DDDr)fgetfsetdoc)r)propertygetattr__doc__)r1rOrRrIdelegates` r_create_delegator_propertyzJPandasDelegate._add_delegate_accessors.._create_delegator_propertyjs 9 9 9 9 9 E E E E E $G #G H&6&6t&<&<==E rczt}tj|fd}|S)Nc&|jg|Ri|SrA)r?)rr7r8r1s rfzSPandasDelegate._add_delegate_accessors.._create_delegator_method..f}s&,t,TCDCCCFCCCr)rW functoolswraps)r1methodr]rIrYs` r_create_delegator_methodzHPandasDelegate._add_delegate_accessors.._create_delegator_methodzsYX'7'7'='=>>F _V $ $ D D D D% $ DHrNrVr1r2)rWrsetattr) clsrYrErFrGrIrKrZrar1r]s ` ` r_add_delegate_accessorsz&PandasDelegate._add_delegate_accessorsKs>                & &D$ H&6&6t&<&>>>::::  1<!%E&E&E&E&[E&E&E&rr0Fc|SrArrBs rrDrDsqrTrEr!rFr2rGrHrIrJrKc&fd}|S)a Add delegated names to a class using a class decorator. This provides an alternative usage to directly calling `_add_delegate_accessors` below a class definition. Parameters ---------- delegate : object The class to get methods/properties & docstrings. accessors : Sequence[str] List of accessor 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. Returns ------- callable A class decorator. Examples -------- @delegate_names(Categorical, ["categories", "ordered"], "property") class CategoricalAccessor(PandasDelegate): [...] c>||S)N)rGrIrK)re)rdrIrErYrGrKrFs radd_delegate_accessorsz.delegate_names..add_delegate_accessorss9 ##   -- $    rr)rYrErFrGrIrKrks`````` rdelegate_namesrlsCP           "!rc eZdZdZd dZdZdS) Accessora 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``. r1r2rr:c"||_||_dSrA)_name _accessor)rr1rs r__init__zAccessor.__init__s !rc>||jS||SrA)rq)robjrds r__get__zAccessor.__get__s! ;> !~~c"""rNrf)r)r*r+rXrrrurrrrnrnsA&""""#####rrnr1rdtype[NDFrame | Index]rCallable[[TypeT], TypeT]cdfd }|S)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. rr rc tr2tjd|dddtt t t |j|S)Nzregistration of accessor z under name z for type z: is overriding a preexisting attribute with the same name.) stacklevel) rwarningswarn UserWarningrrcrnradd)rrdr1s r decoratorz%_register_accessor..decorators 3    M1H1111%(111+--      T8D(33444 4   r)rr rr r)r1rdrs`` r_register_accessorrs0Z        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.ddlm}t||S)a 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)r1rs rregister_dataframe_accessorrEs'H!     dI . ..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.ddlm}t||S)aj 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)r1rs rregister_series_accessorrs'@ dF + ++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.ddlm}t||S)aQ 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)r1r s rregister_index_accessorrs'H dE * **r) rEr!rFr2rGrHrIrJrKrH)r1r2rdrvrrw)r1r2rrw) rX __future__rr^typingrrr{pandas.util._decoratorsrpandas.util._exceptionsrcollections.abcrpandas._typingr rr pandas.core.genericr rr0rlrnCachedAccessorr_register_df_examplesr_register_series_examplesr_register_index_examplesrrrrrs_#"""""544444,(((((($$$$$$++++++