Файловый менеджер - Редактировать - /home/digitalm/venv/lib/python3.7/site-packages/pandas/core/ops/__pycache__/missing.cpython-37.pyc
Назад
B �5�gB � @ sP d Z ddlZddlZddlmZmZmZ ddlm Z dd� Z dd� Z d d � Z dS ) aP Missing data handling for arithmetic operations. In particular, pandas conventions regarding division by zero differ from numpy in the following ways: 1) np.array([-1, 0, 1], dtype=dtype1) // np.array([0, 0, 0], dtype=dtype2) gives [nan, nan, nan] for most dtype combinations, and [0, 0, 0] for the remaining pairs (the remaining being dtype1==dtype2==intN and dtype==dtype2==uintN). pandas convention is to return [-inf, nan, inf] for all dtype combinations. Note: the numpy behavior described here is py3-specific. 2) np.array([-1, 0, 1], dtype=dtype1) % np.array([0, 0, 0], dtype=dtype2) gives precisely the same results as the // operation. pandas convention is to return [nan, nan, nan] for all dtype combinations. 3) divmod behavior consistent with 1) and 2). � N)�is_float_dtype�is_integer_dtype� is_scalar)� roperatorc C s� t | j�r| S t|d�p t|d�}t|�}|s6|s6| S |rDt�|�}t|j�r�|dk�� r�|dkt�| � @ � � }| j }| j ddd�� � } t� | |tj � | �|�} | S )z� If this is a reversed op, then flip x,y If we have an integer value (or array in y) and we have 0's, fill them with np.nan, return the result. Mask the nan's from x. �dtype�typer �float64F)�copy)r r �hasattrr �np�arrayr �any�isnanZravel�shape�astypeZputmask�nanZreshape)�result�x�yZis_variable_typeZis_scalar_type�maskr � r �M/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/core/ops/missing.py� fill_zeros% s r c C s� t |tj�s|S t|�r"t�|�}|dk}t |t�r8|S |�� r�|t�|�@ }|| @ }|| dk@ }tjdd��6 || dk @ || dk@ B }|| dk@ || dk @ B }W dQ R X |�� s�|�� s�|�� r�|j ddd�}tj ||< tj ||< tj ||< |S )am Set results of 0 // 0 to np.nan, regardless of the dtypes of the numerator or the denominator. Parameters ---------- x : ndarray y : ndarray result : ndarray Returns ------- ndarray The filled result. Examples -------- >>> x = np.array([1, 0, -1], dtype=np.int64) >>> x array([ 1, 0, -1]) >>> y = 0 # int 0; numpy behavior is different with float >>> result = x // y >>> result # raw numpy result does not fill division by zero array([0, 0, 0]) >>> mask_zero_div_zero(x, y, result) array([ inf, nan, -inf]) r �ignore)�invalidNr F)r ) � isinstancer Zndarrayr r �boolr ZsignbitZerrstater r �inf) r r r ZzmaskZ zneg_maskZ zpos_maskZnan_maskZ neginf_maskZ posinf_maskr r r �mask_zero_div_zeroM s( " r c C s� | t kr*t|||d �t|d ||�f}n�| tjkrVt|||d �t|d ||�f}n^| tjkrnt|||�}nF| tjkr�t|||�}n.| tjkr�t|||�}n| tj kr�t|||�}|S )a Call fill_zeros with the appropriate fill value depending on the operation, with special logic for divmod and rdivmod. Parameters ---------- op : function (operator.add, operator.div, ...) left : object (np.ndarray for non-reversed ops) right : object (np.ndarray for reversed ops) result : ndarray Returns ------- result : np.ndarray Notes ----- For divmod and rdivmod, the `result` parameter and returned `result` is a 2-tuple of ndarray objects. r � ) �divmodr r r Zrdivmod�operator�floordivZ rfloordiv�modZrmod)�op�left�rightr r r r �dispatch_fill_zeros� s r' ) �__doc__r! �numpyr Zpandas.core.dtypes.commonr r r Zpandas.core.opsr r r r' r r r r �<module> s (?
| ver. 1.4 |
Github
|
.
| PHP 8.3.23 | Генерация страницы: 0.05 |
proxy
|
phpinfo
|
Настройка