o
    d                  
   @   s  d dl Zd dlZd dlmZ d dlmZ d dlm	Z	m
Z
 ejddgddd Zejddgdd	d
 Zejddgddd Zejddgddd Zejdd Zejdd Zejdd Zejdd Zejdd Zejdd Zejdd Ze dd Ze dd  Zejee	dd!d" Zejee
dd#d$ Zejee	ee
 dd%d& Zejddgdd'd( Zejdgdd)d* Zejdgdd+d, Zejd-i fd.d/d0ifd.d/d ifd1d/d0ifd1d/d ifd2i fd3i fd4i fgg d5d6d7d8 Z dS )9    N	DataFrame)reduction_kernelstransformation_kernelsTF)paramsc                 C      | j S Nparamrequest r   b/var/www/html/visualizacion-main/env/lib/python3.10/site-packages/pandas/tests/groupby/conftest.pysort      r   c                 C   r   r   r	   r   r   r   r   as_index   r   r   c                 C   r   r   r	   r   r   r   r   dropna   r   r   c                 C   r   r   r	   r   r   r   r   observed   r   r   c                 C   s   | S r   r   ) multiindex_dataframe_random_datar   r   r   mframe    s   r   c                   C   s*   t g dg dtjdtjddS )Nfoobarr   r   r   r   r   r   oner   twothreer   r   r   r      ABCDr   nprandomrandnr   r   r   r   df%   s   

r'   c                   C      t  S r   )tmmakeTimeSeriesr   r   r   r   ts1      r+   c                   C   r(   r   )r)   getTimeSeriesDatar   r   r   r   tsd6   r,   r.   c                 C   s   t | S r   r   )r.   r   r   r   tsframe;   r,   r/   c                   C   s4   t g dg dtjdtjtjddddS )Nr   r   r   float32)dtyper   )r   r$   r%   r&   arrayr   r   r   r   df_mixed_floats@   s   
r3   c                	   C   s:   t g dg dg dtjdtjdtjddS )N)r   r   r   r   r   r   r   r   r   r   r   )r   r   r   r   r   r   r   r   r   r   r   )dullr4   shinyr4   r4   r5   r5   r4   r5   r5   r5      )r   r    r!   r"   EFr#   r   r   r   r   three_groupL   s   


r9   c               	   C   sN   g dg dg dg dg dg dg dg dg} t | g d	d
}|dS )N)r   aa0_at_0)   bb0_at_1)   r:   a1_at_2)   r=   b1_at_3)   cc0_at_4)   r:   a2_at_5)   r:   a3_at_6)   r:   a4_at_7)IndexGroupValue)columnsrL   )r   	set_index)datar'   r   r   r   slice_test_df~   s   

rR   c                 C   s   | j dddS )NrM   F)r   )groupby)rR   r   r   r   slice_test_grouped   s   rT   c                 C   r   )zT
    yields the string names of all groupby reduction functions, one at a time.
    r	   r   r   r   r   reduction_func   s   rU   c                 C   r   )z@yields the string names of all groupby transformation functions.r	   r   r   r   r   transformation_func      rV   c                 C   r   )z5yields both aggregation and transformation functions.r	   r   r   r   r   groupby_func   rW   rX   c                 C   r   )z'parallel keyword argument for numba.jitr	   r   r   r   r   parallel   rW   rY   c                 C   r   )z$nogil keyword argument for numba.jitr	   r   r   r   r   nogil   rW   rZ   c                 C   r   )z'nopython keyword argument for numba.jitr	   r   r   r   r   nopython   rW   r[   meanvarddofr<   stdsumminmax)r\   var_1var_0std_1std_0r`   ra   rb   )r   idsc                 C   r   )z(reductions supported with engine='numba'r	   r   r   r   r   numba_supported_reductions   s   rh   )!numpyr$   pytestpandasr   pandas._testing_testingr)   pandas.core.groupby.baser   r   fixturer   r   r   r   r   r'   r+   r.   r/   r3   r9   rR   rT   sortedrU   rV   rX   rY   rZ   r[   rh   r   r   r   r   <module>   sp    










1





	






