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These classes (BaseGrouper and BinGrouper) are contained *in* the SeriesGroupBy and DataFrameGroupBy objects. � )� annotationsN)�Generic�Hashable�Iterator�Sequence�overload)�NaT�lib)� ArrayLike�DtypeObj�F� FrameOrSeries�Shape�final)�AbstractMethodError)�cache_readonly)�maybe_cast_pointwise_result�maybe_downcast_to_dtype)�ensure_float64� ensure_int64�ensure_platform_int�is_1d_only_ea_obj� is_bool_dtype�is_categorical_dtype�is_complex_dtype�is_datetime64_any_dtype�is_float_dtype�is_integer_dtype�is_numeric_dtype� is_sparse�is_timedelta64_dtype�needs_i8_conversion)�ExtensionDtype)�isna� maybe_fill)� DatetimeArray�ExtensionArray� PeriodArray�TimedeltaArray)� BooleanDtype)� Float64Dtype� FloatingDtype)� Int64Dtype� _IntegerDtype)�BaseMaskedArray�BaseMaskedDtype)� StringDtype)� DataFrame)�NDFrame)�base�grouper)�CategoricalIndex�Index� MultiIndex� ensure_index)� ArrayManager)�Series)�compress_group_index�decons_obs_group_ids�get_flattened_list�get_group_index�get_group_index_sorter�get_indexer_dictc @ s� e Zd ZdZedddddg�Zddd�d d �Zd d d dddddddd� dddddd�d �Zd d hZd d iZ e e j d!d"�ddd#d$d%�d&d'���Z d(d$d)�d*d+�ZdTd-d$d.�d/d0�Zd1d(d2d3�d4d5�Zd#d#d6�d7d8�Zed#d#d6�d9d:��Zed;d;d6�d<d:��Zd-d-d6�d=d:�Zd$d>�d?d@�ZedAd1d1d(dBdC�dDdE��ZedFd1d1d(dFdC�dGdH��Zed(d1d1d(dId(dJ�dKdL��Zed(d1d1d(dId(dJ�dMdN��ZedOdP�dBd1d1d(d1dBdQ�dRdS��Zd!S )U�WrappedCythonOpz? Dispatch logic for functions defined in _libs.groupby �rank�count�sizeZidxminZidxmax�str)�kind�howc C s || _ || _d S )N)rF rG )�selfrF rG � rI �M/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/core/groupby/ops.py�__init__w s zWrappedCythonOp.__init__Z group_addZ group_prodZ group_minZ group_maxZ group_meanZ group_medianZ group_varZ group_nthZ group_lastZ group_ohlc) �add�prod�min�max�mean�median�var�first�last�ohlcZ group_cumprodZ group_cumsumZ group_cumminZ group_cummaxZ group_rank)�cumprod�cumsum�cummin�cummaxrB )� aggregate� transformrX rY rU � N)�maxsizeznp.dtype�bool)rF rG �dtype� is_numericc C sV |j }| j| | }tt|�}|r&|S |tkrRd|jkrNtd|� d|� d���|S d S )N�objectz2function is not implemented for this dtype: [how->z,dtype->�])�name�_CYTHON_FUNCTIONS�getattr� libgroupbyra Z__signatures__�NotImplementedError)�clsrF rG r_ r` Z dtype_strZftype�frI rI rJ �_get_cython_function� s z$WrappedCythonOp._get_cython_functionz np.ndarray)�valuesr` c C s� | j }| j}|dkrV|r"t|�}ntd|� d|jj� d���ttd|� d��}||fS | �|||j|�}|jjdkr�|dkr�t|�}||fS ) z� Find the appropriate cython function, casting if necessary. 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Returns ------- np.dtype or ExtensionDtype The desired dtype of the result. )rL rW �sumrM )rP rQ rR ) rG r~ r_ r^ �int64� isinstancer) r- r, r* r r r| )rH r_ rG rI rI rJ r� ! s )rt c C s | j | jkS )N)rG �_MASKED_CYTHON_FUNCTIONS)rH rI rI rJ � uses_mask@ s zWrappedCythonOp.uses_maskr& r )rk � min_countrs �comp_idsrt c K s6 t |t�r,| �� r,| j|f|||d�|��S |}t |ttf�r�|j�d�}| j|f|||dd�|��}| j dkrt|S |�d�}t |�||j d�} | S t |t �r�| j|jf|||dd�|��}| j dkr�|S t |�|�S t |j t tf��rF|jdtjd �}| j|f|||dd�|��}| j dk�r$|S | �|j �} | �� } | j|| d�S t |j t��r�|j|j jtjd �}| j|f|||dd�|��}| j dk�r�|S | �|j �} | �� } | j|| d�S t |j t��r"|jttjd �}| j|f|||dd�|��}| j dk�r |S | �|j �} | �� } | j|| d�S td |j � ���dS ) zs If we have an ExtensionArray, unwrap, call _cython_operation, and re-wrap if appropriate. )r� rs r� zM8[ns]N)r� rs r� �mask)rB �i8)r_ r| )Zna_valuez,function is not implemented for this dtype: )r� r. r� � _masked_ea_wrap_cython_operationr% r' Z_ndarray�view�_cython_op_ndim_compatrG �typer_ r( r) r- Zto_numpyr~ �nanr� �construct_array_typeZ_from_sequencer+ Z numpy_dtyper0 ra rg ) rH rk r� rs r� �kwargs� orig_values�npvalues� res_values�resultr_ rh rI rI rJ �_ea_wrap_cython_operationC s� z)WrappedCythonOp._ea_wrap_cython_operationr. c K sh |}|j �� }|j}| j|f||||d�|��} | �|j�} t| t�sJt�| � � } | | j | j dd�|�S )z� Equivalent of `_ea_wrap_cython_operation`, but optimized for masked EA's and cython algorithms which accept a mask. )r� rs r� r� F)�copy) Z_maskr� �_datar� r� r_ r� r/ �AssertionErrorr� �astyper� ) rH rk r� rs r� r� r� r� Zarrr� r_ rh rI rI rJ r� � s z0WrappedCythonOp._masked_ea_wrap_cython_operationznp.ndarray | None)rk r� rs r� r� rt c K sn |j dkrR|d d d �f }| j|f||||d�|��}|jd dkrL|d S |jS | j|f||||d�|��S )Nru )r� rs r� r� r )�ndim�_call_cython_oprx �T) rH rk r� rs r� r� r� Zvalues2d�resrI rI rJ r� � s& z&WrappedCythonOp._cython_op_ndim_compatc K s |}|j }t|�} t|�} | r.|�d�}d} nLt|�rB|�d�}n8t|�rf|tjkrz|jtj dd�}n| rzt |�szt |�}|j }|d k r�|j |jdd�}| �||�} | �|| �\} }| �|j �} ttj| | d��}| jdk�rDtj|tj d�}| jd k�r| |||||| d � n2| jd k�r2| |||||| d � n| |||||� n<| �� �rl| ||||| fd |i|�� n| ||||| f|� | jdk�r�t|j ��r�| �s�td|�}||k }|�� �r�|�d�}tj||< |j }| j| jk�r�| � |j �}t ||�}n|}|S )Nr� TF)r� �C)�order)r_ rZ )rN rO rP )�is_datetimelike)rL )Z datetimeliker� ru r| ) r_ r r! r� r r� r r~ Zuint64r� r r r� Zreshaperx r{ ro r� r$ �emptyrF �zerosrG r� rO �anyr� �cast_blocklistr� r )rH rk r� rs r� r� r� r� r_ r` r� rz rn r r� �counts�cutoffZ empty_groupsZ res_dtype� op_resultrI rI rJ r� s� z WrappedCythonOp._call_cython_op���)r� )rk �axisr� r� rs rt c K s� |j dkrtd��n0|j dkr0|dksDt|��nt|�sD|dksDt�|j}t|�}| �||� t|tj �s�| j |f|||d�|��S | j |f|||dd�|��S )zW Call our cython function, with appropriate pre- and post- processing. � z.number of dimensions is currently limited to 2ru r )r� rs r� N)r� rs r� r� ) r� rg r� r r_ r rq r� r~ �ndarrayr� r� ) rH rk r� r� r� rs r� r_ r` rI rI rJ �cython_operationw s. z WrappedCythonOp.cython_operation)F)�__name__� __module__� __qualname__�__doc__� frozensetr� rK rd r� rv � classmethod� functools� lru_cacherj ro rq r{ r� r r� r� r r� r� r� r� r� rI rI rI rJ rA n sJ "&$ ! % jrA c @ s8 e Zd ZU dZded< d^dddddd dd �d d �Zed d�dd��Zedd�dd��Zdd� Z edd�dd��Z d_dddd �d d �Z e d`ddd d �d d!��Z d"d#� Ze d$d%� �Ze dad&ddd'�d(d)��Zed*d+� �Zed,d�d-d.��Zed/d�d0d1��Zed2d�d3d4��Ze d5d�d6d7��Zed8d�d9d:��Ze edd�d;d<���Zed=d>� �Ze ed?d�d@dA���Ze dBd�dCdD��Ze edd�dEdF���Z ed,d�dGdH��Z edId�dJdK��Z edd�dLdM��Z e dNd�dOdP��Z e dbdRdRdddIdS�dTdU��Z!e dcd5d&ddIdV�dWdX��Z"d5d&d?dY�dZd[�Z#e d5d&d?dY�d\d]��Z$dS )d� BaseGroupera� This is an internal Grouper class, which actually holds the generated groups Parameters ---------- axis : Index groupings : Sequence[Grouping] all the grouping instances to handle in this grouper for example for grouper list to groupby, need to pass the list sort : bool, default True whether this grouper will give sorted result or not group_keys : bool, default True mutated : bool, default False indexer : np.ndarray[np.intp], optional the indexer created by Grouper some groupers (TimeGrouper) will sort its axis and its group_info is also sorted, so need the indexer to reorder r6 r� TFNzSequence[grouper.Grouping]r^ znp.ndarray | None)r� � groupings�sort� group_keys�mutated�indexer�dropnac C sD t |t�st|��|| _t|�| _|| _|| _|| _|| _ || _ d S )N) r� r6 r� r� �list� _groupings�_sortr� r� r� r� )rH r� r� r� r� r� r� r� rI rI rJ rK � s zBaseGrouper.__init__zlist[grouper.Grouping])rt c C s | j S )N)r� )rH rI rI rJ r� � s zBaseGrouper.groupingsr c C s t dd� | jD ��S )Nc s s | ] }|j V qd S )N)rs )�.0�pingrI rI rJ � <genexpr>� s z$BaseGrouper.shape.<locals>.<genexpr>)�tupler� )rH rI rI rJ rx � s zBaseGrouper.shapec C s t | j�S )N)�iter�indices)rH rI rI rJ �__iter__� s zBaseGrouper.__iter__rr c C s t | j�S )N)�lenr� )rH rI rI rJ �nkeys� s zBaseGrouper.nkeysr r z(Iterator[tuple[Hashable, FrameOrSeries]])�datar� rt c c sF | j ||d�}| �� }x*t||�D ] \}}||j|dd�fV q"W dS )z� Groupby iterator Returns ------- Generator yielding sequence of (name, subsetted object) for each group )r� �groupby)�methodN)� _get_splitter�_get_group_keys�zipZ __finalize__)rH r� r� �splitter�keys�key�grouprI rI rJ � get_iterator� s zBaseGrouper.get_iterator� DataSplitterc C s | j \}}}t||||d�S )z� Returns ------- Generator yielding subsetted objects __finalize__ has not been called for the subsetted objects returned. )r� )� group_info� get_splitter)rH r� r� �ids�_rs rI rI rJ r� � s zBaseGrouper._get_splitterc C s | j d jS )z� We are a grouper as part of another's groupings. 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Returns ------- np.ndarray or ExtensionArray r TF)Z try_float)Z numeric_only) r� � _aggregate_series_pure_pythonr� r� r~ r� r� r� �_aggregate_series_fastr Zmaybe_convert_objectsr r_ )rH r rn r r� r� r� rI rI rJ � agg_series� s zBaseGrouper.agg_series)r rn rt c C sT t �|�}| j\}}}t||�}|�|�}|�|�}t�||||�}|�� \}}|S )N)r� Zis_builtin_funcr� r? r� � libreductionZ SeriesGrouper� get_result) rH r rn r� r� rs r� Zsgrouperr� rI rI rJ r - s z"BaseGrouper._aggregate_series_fastc C s� | j \}}}tj|td�}tj|dd�}d}t|||dd�} xRt| �D ]F\} } || �} t�| �} |svt� | | j � d}| j d || < | || < qFW |S )N)r_ �OFr )r� T) r� r~ r� rr r� r� � enumerater Zextract_resultZcheck_result_arrayr_ rx ) rH r rn r� r� rs r� r� Z initializedr� rl r� r� rI rI rJ r @ s z)BaseGrouper._aggregate_series_pure_python)TTFNT)r )r )r )r� )F)%r� r� r� r� �__annotations__rK �propertyr� rx r� r� r� r r� r� r� r� r r� r� r� r� rD r� r� r� r� r� rs r� r� r� r� r r r r rI rI rI rJ r� � sT G 0r� c @ s� e Zd ZU dZded< ded< ded< d1dd �d d �Zed d� �Zedd�dd��Z dd� Z d2ddd�dd�Z edd� �Z ed d � �Z ed d�d d ��Zed!d"� �Zed#d�d$d%��Zed&d�d'd(��Zed)d�d*d+��Zd,d-dd.�d/d0�Zd S )3� BinGrouperaU This is an internal Grouper class Parameters ---------- bins : the split index of binlabels to group the item of axis binlabels : the label list mutated : bool, default False indexer : np.ndarray[np.intp] Examples -------- bins: [2, 4, 6, 8, 10] binlabels: DatetimeIndex(['2005-01-01', '2005-01-03', '2005-01-05', '2005-01-07', '2005-01-09'], dtype='datetime64[ns]', freq='2D') the group_info, which contains the label of each item in grouped axis, the index of label in label list, group number, is (array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4]), array([0, 1, 2, 3, 4]), 5) means that, the grouped axis has 10 items, can be grouped into 5 labels, the first and second items belong to the first label, the third and forth items belong to the second label, and so on z np.ndarray�binsr6 � binlabelsr^ r� FN)r� c C s< t |�| _t|�| _|| _|| _t| j�t| j�ks8t�d S )N)r r r8 r r� r� r� r� )rH r r r� r� rI rI rJ rK s zBinGrouper.__init__c C s dd� t | j| j�D �}|S )z!dict {group name -> group labels}c S s i | ]\}}|t k r||�qS rI )r )r� r� �valuerI rI rJ � <dictcomp>� s z%BinGrouper.groups.<locals>.<dictcomp>)r� r r )rH r� rI rI rJ r� � s zBinGrouper.groupsrr )rt c C s dS )Nru rI )rH rI rI rJ r� � s zBinGrouper.nkeysc C s | S )z� We are a grouper as part of another's groupings. We have a specific method of grouping, so cannot convert to a Index for our grouper. rI )rH rI rI rJ r� � s zBinGrouper._get_grouperr r )r� r� c # s� |dkr� fdd�}n � fdd�}t � j| �}d}x6t| j| j�D ]$\}}|tk rd||||�fV |}qDW ||k r�| jd ||d�fV dS )z� Groupby iterator Returns ------- Generator yielding sequence of (name, subsetted object) for each group r c s � j | |� S )N)�iloc)�start�edge)r� rI rJ �<lambda>� � z)BinGrouper.get_iterator.<locals>.<lambda>c s � j d d �| |�f S )N)r )r r )r� rI rJ r � r r� N)r� r� r� r r r )rH r� r� Zslicer�lengthr r �labelrI )r� rJ r� � s zBinGrouper.get_iteratorc C sT t �t�}d}x@t| j| j�D ].\}}||k r |tk rHtt||��||< |}q W |S )Nr )� collections� defaultdictr� r� r r r �range)rH r� rl r �binrI rI rJ r� � s zBinGrouper.indicesc C s� | j }tj|tjd�}t�tjd| jf �}t|�}|t| j�krVt� t�|�|�}n t� tjdt�|�f |�}t|�||fS )N)r_ r r� ) rs r~ r� r� �diff�r_r r r� �repeat)rH rs r� �repr� rI rI rJ r� � s zBinGrouper.group_infozlist[np.ndarray]c C s2 t jdt �| jdd � | jd d� k�d f gS )Nr ru r� )r~ r Z flatnonzeror )rH rI rI rJ r� � s z BinGrouper.reconstructed_codesc C s0 t | j�dkr*t| jd �r*| jdd � S | jS )Nr ru )r� r r# )rH rI rI rJ r� � s zBinGrouper.result_indexz list[Index]c C s | j gS )N)r )rH rI rI rJ r� � s zBinGrouper.levelszlist[Hashable]c C s | j jgS )N)r rc )rH rI rI rJ r� � s zBinGrouper.nameszlist[grouper.Grouping]c C s | j }tj||dd d�}|gS )NF)Zin_axis�level)r r4 ZGrouping)rH Zlevr� rI rI rJ r� � s zBinGrouper.groupingsr: r )r rn rt c C s t �||| j�}|�� \}}|S )N)r ZSeriesBinGrouperr r )rH r rn Zsbgr� r� rI rI rJ r � s z!BinGrouper._aggregate_series_fast)FN)r )r� r� r� r� r rK r r� r r� r� r� r� r� r� r� r� r� r� r rI rI rI rJ r ^ s$ r rr r^ )r� rt c C sP t | t�r.t|�dkrdS | j| �|| �S t | t�rL| j| �|| �S dS )Nru F)r� r: r� r� �equalsr1 )r r� r� rI rI rJ r� s r� c @ sn e Zd Zddddd�dd�Zedd�d d ��Zedd�d d ��Zd d� Zedd�dd��Zddd�dd�Z dS )r� r r rr )r� rs r� c C s2 || _ t|�| _|| _|| _t|t�s.t|��d S )N)r� r �labelsrs r� r� rr r� )rH r� r" rs r� rI rI rJ rK s zDataSplitter.__init__z np.ndarray)rt c C s | j �| j�S )N)r" r� � _sort_idx)rH rI rI rJ �slabels s zDataSplitter.slabelsc C s t | j| j�S )N)r? r" rs )rH rI rI rJ r# $ s zDataSplitter._sort_idxc c sX | j }| jdkrd S t�| j| j�\}}x*t||�D ] \}}| �|t||��V q4W d S )Nr )r� rs r �generate_slicesr$ r� �_chop�slice)rH r� �starts�endsr �endrI rI rJ r� ) s zDataSplitter.__iter__c C s | j j| j| jd�S )N)r� )r� r� r# r� )rH rI rI rJ r� 6 s zDataSplitter.sorted_datar' r2 )� slice_objrt c C s t | ��d S )N)r )rH r� r+ rI rI rJ r& : s zDataSplitter._chopN)r ) r� r� r� rK r r$ r# r� r� r& rI rI rI rJ r� s r� c @ s e Zd Zdddd�dd�ZdS )�SeriesSplitterr: r' )r� r+ rt c C s> |j �|�}t|��|�}t�|d|j� t�|d|j� |S )N�_flags�_name)r� � get_slicer� � _from_mgrra r� r- r. )rH r� r+ �mgrr rI rI rJ r& ? s zSeriesSplitter._chopN)r� r� r� r& rI rI rI rJ r, > s r, c @ s. e Zd Zddd�dd�Zdddd�d d �Zd S ) r� r r )ri r� c C s& t �| j| j�\}}t�|||||�S )N)r r% r$ rs r Zapply_frame_axis0)rH ri r� r� r( r) rI rI rJ r� M s zFrameSplitter.fast_applyr1 r' )r� r+ rt c C s8 |j j|d| j d�}t|��|�}t�|d|j� |S )Nru )r� r- )r� r/ r� r� r0 ra r� r- )rH r� r+ r1 r rI rI rJ r& R s zFrameSplitter._chopN)r� r� r� r� r& rI rI rI rJ r� L s r� r z np.ndarray)r� r" rs r� rt c C s" t | t�rt}nt}|| |||�S )N)r� r: r, r� )r� r" rs r� �klassrI rI rJ r� a s r� )r )nr� � __future__r r r� �typingr r r r r �numpyr~ Z pandas._libsr r Zpandas._libs.groupbyZ_libsr� rf Zpandas._libs.reductionZ reductionr Zpandas._typingr r r r r r Z pandas.errorsr Zpandas.util._decoratorsr Zpandas.core.dtypes.castr r Zpandas.core.dtypes.commonr r r r r r r r r r r r r r! 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