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Python nanops.nancov方法代碼示例

本文整理匯總了Python中pandas.core.nanops.nancov方法的典型用法代碼示例。如果您正苦於以下問題:Python nanops.nancov方法的具體用法?Python nanops.nancov怎麽用?Python nanops.nancov使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在pandas.core.nanops的用法示例。


在下文中一共展示了nanops.nancov方法的4個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: cov

# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nancov [as 別名]
def cov(self, other, min_periods=None):
        """
        Compute covariance with Series, excluding missing values.

        Parameters
        ----------
        other : Series
        min_periods : int, optional
            Minimum number of observations needed to have a valid result

        Returns
        -------
        covariance : float

        Normalized by N-1 (unbiased estimator).
        """
        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return np.nan
        return nanops.nancov(this.values, other.values,
                             min_periods=min_periods) 
開發者ID:Frank-qlu,項目名稱:recruit,代碼行數:23,代碼來源:series.py

示例2: cov

# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nancov [as 別名]
def cov(self, other, min_periods=None):
        """
        Compute covariance with Series, excluding missing values

        Parameters
        ----------
        other : Series
        min_periods : int, optional
            Minimum number of observations needed to have a valid result

        Returns
        -------
        covariance : float

        Normalized by N-1 (unbiased estimator).
        """
        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return np.nan
        return nanops.nancov(this.values, other.values,
                             min_periods=min_periods) 
開發者ID:birforce,項目名稱:vnpy_crypto,代碼行數:23,代碼來源:series.py

示例3: cov

# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nancov [as 別名]
def cov(self, other, min_periods=None):
        """
        Compute covariance with Series, excluding missing values

        Parameters
        ----------
        other : Series
        min_periods : int, optional
            Minimum number of observations needed to have a valid result

        Returns
        -------
        covariance : float

        Normalized by N-1 (unbiased estimator).
        """
        this, other = self.align(other, join='inner')
        if len(this) == 0:
            return pa.NA
        return nanops.nancov(this.values, other.values,
                             min_periods=min_periods) 
開發者ID:ktraunmueller,項目名稱:Computable,代碼行數:23,代碼來源:series.py

示例4: test_nancov

# 需要導入模塊: from pandas.core import nanops [as 別名]
# 或者: from pandas.core.nanops import nancov [as 別名]
def test_nancov(self):
        targ0 = np.cov(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.cov(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancov, targ0, targ1)
        targ0 = np.cov(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.cov(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancov, targ0, targ1) 
開發者ID:Frank-qlu,項目名稱:recruit,代碼行數:9,代碼來源:test_nanops.py


注:本文中的pandas.core.nanops.nancov方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台,相關代碼片段篩選自各路編程大神貢獻的開源項目,源碼版權歸原作者所有,傳播和使用請參考對應項目的License;未經允許,請勿轉載。