Python pandas.core.nanops.nancorr() Examples

The following are 26 code examples of pandas.core.nanops.nancorr(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas.core.nanops , or try the search function .
Example #1
Source File: series.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def corr(self, other, method='pearson', min_periods=None):
        """
        Compute correlation with `other` Series, excluding missing values

        Parameters
        ----------
        other : Series
        method : {'pearson', 'kendall', 'spearman'}
            * pearson : standard correlation coefficient
            * kendall : Kendall Tau correlation coefficient
            * spearman : Spearman rank correlation
        min_periods : int, optional
            Minimum number of observations needed to have a valid result


        Returns
        -------
        correlation : float
        """
        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return np.nan
        return nanops.nancorr(this.values, other.values, method=method,
                              min_periods=min_periods)
Example #2
Source File: series.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def corr(self, other, method='pearson', min_periods=None):
        """
        Compute correlation with `other` Series, excluding missing values

        Parameters
        ----------
        other : Series
        method : {'pearson', 'kendall', 'spearman'}
            * pearson : standard correlation coefficient
            * kendall : Kendall Tau correlation coefficient
            * spearman : Spearman rank correlation
        min_periods : int, optional
            Minimum number of observations needed to have a valid result


        Returns
        -------
        correlation : float
        """
        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return np.nan
        return nanops.nancorr(this.values, other.values, method=method,
                              min_periods=min_periods)
Example #3
Source File: series.py    From Computable with MIT License 6 votes vote down vote up 
def corr(self, other, method='pearson',
             min_periods=None):
        """
        Compute correlation with `other` Series, excluding missing values

        Parameters
        ----------
        other : Series
        method : {'pearson', 'kendall', 'spearman'}
            * pearson : standard correlation coefficient
            * kendall : Kendall Tau correlation coefficient
            * spearman : Spearman rank correlation
        min_periods : int, optional
            Minimum number of observations needed to have a valid result


        Returns
        -------
        correlation : float
        """
        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return pa.NA
        return nanops.nancorr(this.values, other.values, method=method,
                              min_periods=min_periods)
Example #4
Source File: series.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def corr(self, other, method='pearson', min_periods=None):
        """
        Compute correlation with `other` Series, excluding missing values

        Parameters
        ----------
        other : Series
        method : {'pearson', 'kendall', 'spearman'}
            * pearson : standard correlation coefficient
            * kendall : Kendall Tau correlation coefficient
            * spearman : Spearman rank correlation
        min_periods : int, optional
            Minimum number of observations needed to have a valid result


        Returns
        -------
        correlation : float
        """
        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return np.nan
        return nanops.nancorr(this.values, other.values, method=method,
                              min_periods=min_periods)
Example #5
Source File: test_nanops.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_nancorr_kendall(self):
        from scipy.stats import kendalltau
        targ0 = kendalltau(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = kendalltau(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
        targ0 = kendalltau(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = kendalltau(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
Example #6
Source File: test_nanops.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_nancorr_spearman(self):
        from scipy.stats import spearmanr
        targ0 = spearmanr(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = spearmanr(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
        targ0 = spearmanr(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = spearmanr(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
Example #7
Source File: test_nanops.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_nancorr_kendall(self):
        from scipy.stats import kendalltau
        targ0 = kendalltau(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = kendalltau(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
        targ0 = kendalltau(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = kendalltau(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
Example #8
Source File: test_nanops.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_nancorr_pearson(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #9
Source File: test_nanops.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_nancorr(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1)
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #10
Source File: test_nanops.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_nancorr_spearman(self):
        tm.skip_if_no_package('scipy.stats')
        from scipy.stats import spearmanr
        targ0 = spearmanr(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = spearmanr(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
        targ0 = spearmanr(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = spearmanr(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
Example #11
Source File: test_nanops.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_nancorr_kendall(self):
        tm.skip_if_no_package('scipy.stats')
        from scipy.stats import kendalltau
        targ0 = kendalltau(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = kendalltau(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
        targ0 = kendalltau(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = kendalltau(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
Example #12
Source File: test_nanops.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_nancorr_pearson(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #13
Source File: test_nanops.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_nancorr(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1)
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #14
Source File: test_nanops.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_nancorr_spearman(self):
        from scipy.stats import spearmanr
        targ0 = spearmanr(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = spearmanr(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
        targ0 = spearmanr(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = spearmanr(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
Example #15
Source File: test_nanops.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_nancorr(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1)
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #16
Source File: test_nanops.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_nancorr_pearson(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #17
Source File: test_nanops.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_nancorr(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1)
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #18
Source File: test_nanops.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_nancorr_spearman(self):
        from scipy.stats import spearmanr
        targ0 = spearmanr(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = spearmanr(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
        targ0 = spearmanr(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = spearmanr(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
Example #19
Source File: test_nanops.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_nancorr_kendall(self):
        from scipy.stats import kendalltau
        targ0 = kendalltau(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = kendalltau(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
        targ0 = kendalltau(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = kendalltau(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
Example #20
Source File: test_nanops.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_nancorr_pearson(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #21
Source File: test_nanops.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_nancorr(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1)
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #22
Source File: test_nanops.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_nancorr_spearman(self):
        from scipy.stats import spearmanr
        targ0 = spearmanr(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = spearmanr(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
        targ0 = spearmanr(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = spearmanr(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='spearman')
Example #23
Source File: test_nanops.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_nancorr_kendall(self):
        from scipy.stats import kendalltau
        targ0 = kendalltau(self.arr_float_2d, self.arr_float1_2d)[0]
        targ1 = kendalltau(self.arr_float_2d.flat, self.arr_float1_2d.flat)[0]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
        targ0 = kendalltau(self.arr_float_1d, self.arr_float1_1d)[0]
        targ1 = kendalltau(self.arr_float_1d.flat, self.arr_float1_1d.flat)[0]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='kendall')
Example #24
Source File: test_nanops.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_nancorr_pearson(self):
        targ0 = np.corrcoef(self.arr_float_2d, self.arr_float1_2d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_2d.flat,
                            self.arr_float1_2d.flat)[0, 1]
        self.check_nancorr_nancov_2d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
        targ0 = np.corrcoef(self.arr_float_1d, self.arr_float1_1d)[0, 1]
        targ1 = np.corrcoef(self.arr_float_1d.flat,
                            self.arr_float1_1d.flat)[0, 1]
        self.check_nancorr_nancov_1d(nanops.nancorr, targ0, targ1,
                                     method='pearson')
Example #25
Source File: series.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 4 votes vote down vote up 
def corr(self, other, method='pearson', min_periods=None):
        """
        Compute correlation with `other` Series, excluding missing values.

        Parameters
        ----------
        other : Series
        method : {'pearson', 'kendall', 'spearman'} or callable
            * pearson : standard correlation coefficient
            * kendall : Kendall Tau correlation coefficient
            * spearman : Spearman rank correlation
            * callable: callable with input two 1d ndarray
                and returning a float
                .. versionadded:: 0.24.0

        min_periods : int, optional
            Minimum number of observations needed to have a valid result

        Returns
        -------
        correlation : float

        Examples
        --------
        >>> histogram_intersection = lambda a, b: np.minimum(a, b
        ... ).sum().round(decimals=1)
        >>> s1 = pd.Series([.2, .0, .6, .2])
        >>> s2 = pd.Series([.3, .6, .0, .1])
        >>> s1.corr(s2, method=histogram_intersection)
        0.3
        """
        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return np.nan

        if method in ['pearson', 'spearman', 'kendall'] or callable(method):
            return nanops.nancorr(this.values, other.values, method=method,
                                  min_periods=min_periods)

        raise ValueError("method must be either 'pearson', "
                         "'spearman', or 'kendall', '{method}' "
                         "was supplied".format(method=method))
Example #26
Source File: series.py    From recruit with Apache License 2.0 4 votes vote down vote up 
def corr(self, other, method='pearson', min_periods=None):
        """
        Compute correlation with `other` Series, excluding missing values.

        Parameters
        ----------
        other : Series
        method : {'pearson', 'kendall', 'spearman'} or callable
            * pearson : standard correlation coefficient
            * kendall : Kendall Tau correlation coefficient
            * spearman : Spearman rank correlation
            * callable: callable with input two 1d ndarray
                and returning a float
                .. versionadded:: 0.24.0

        min_periods : int, optional
            Minimum number of observations needed to have a valid result

        Returns
        -------
        correlation : float

        Examples
        --------
        >>> histogram_intersection = lambda a, b: np.minimum(a, b
        ... ).sum().round(decimals=1)
        >>> s1 = pd.Series([.2, .0, .6, .2])
        >>> s2 = pd.Series([.3, .6, .0, .1])
        >>> s1.corr(s2, method=histogram_intersection)
        0.3
        """
        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return np.nan

        if method in ['pearson', 'spearman', 'kendall'] or callable(method):
            return nanops.nancorr(this.values, other.values, method=method,
                                  min_periods=min_periods)

        raise ValueError("method must be either 'pearson', "
                         "'spearman', or 'kendall', '{method}' "
                         "was supplied".format(method=method))