PEP: use triple-double-quotes rather than triple-single-quotes around doc-strings in cython

     as per PEP

closes #12994

Author: jreback

pandas/algos.pyx

@@ -838,9 +838,9 @@ cdef inline kth_smallest_c(float64_t* a, Py_ssize_t k, Py_ssize_t n):
 
 
 cpdef numeric median(numeric[:] arr):
-    '''
+    """
     A faster median
-    '''
+    """
     cdef Py_ssize_t n = arr.size
 
     if n == 0:
@@ -999,7 +999,7 @@ def roll_mean(ndarray[double_t] input,
 # Exponentially weighted moving average
 
 def ewma(ndarray[double_t] input, double_t com, int adjust, int ignore_na, int minp):
-    '''
+    """
     Compute exponentially-weighted moving average using center-of-mass.
 
     Parameters
@@ -1013,7 +1013,7 @@ def ewma(ndarray[double_t] input, double_t com, int adjust, int ignore_na, int m
     Returns
     -------
     y : ndarray
-    '''
+    """
 
     cdef Py_ssize_t N = len(input)
     cdef ndarray[double_t] output = np.empty(N, dtype=float)
@@ -1061,7 +1061,7 @@ def ewma(ndarray[double_t] input, double_t com, int adjust, int ignore_na, int m
 
 def ewmcov(ndarray[double_t] input_x, ndarray[double_t] input_y,
            double_t com, int adjust, int ignore_na, int minp, int bias):
-    '''
+    """
     Compute exponentially-weighted moving variance using center-of-mass.
 
     Parameters
@@ -1077,7 +1077,7 @@ def ewmcov(ndarray[double_t] input_x, ndarray[double_t] input_y,
     Returns
     -------
     y : ndarray
-    '''
+    """
 
     cdef Py_ssize_t N = len(input_x)
     if len(input_y) != N:
@@ -1761,9 +1761,9 @@ cdef _roll_min_max(ndarray[numeric] a, int window, int minp, bint is_max):
 
 def roll_quantile(ndarray[float64_t, cast=True] input, int win,
                   int minp, double quantile):
-    '''
+    """
     O(N log(window)) implementation using skip list
-    '''
+    """
     cdef double val, prev, midpoint
     cdef IndexableSkiplist skiplist
     cdef Py_ssize_t nobs = 0, i
@@ -1997,12 +1997,12 @@ def groupby_indices(ndarray values):
 @cython.wraparound(False)
 @cython.boundscheck(False)
 def group_labels(ndarray[object] values):
-    '''
+    """
     Compute label vector from input values and associated useful data
 
     Returns
     -------
-    '''
+    """
     cdef:
         Py_ssize_t i, n = len(values)
         ndarray[int64_t] labels = np.empty(n, dtype=np.int64)
@@ -2074,9 +2074,9 @@ def group_nth_object(ndarray[object, ndim=2] out,
                      ndarray[object, ndim=2] values,
                      ndarray[int64_t] labels,
                      int64_t rank):
-    '''
+    """
     Only aggregates on axis=0
-    '''
+    """
     cdef:
         Py_ssize_t i, j, N, K, lab
         object val
@@ -2117,9 +2117,9 @@ def group_nth_bin_object(ndarray[object, ndim=2] out,
                          ndarray[int64_t] counts,
                          ndarray[object, ndim=2] values,
                          ndarray[int64_t] bins, int64_t rank):
-    '''
+    """
     Only aggregates on axis=0
-    '''
+    """
     cdef:
         Py_ssize_t i, j, N, K, ngroups, b
         object val
@@ -2167,9 +2167,9 @@ def group_last_object(ndarray[object, ndim=2] out,
                       ndarray[int64_t] counts,
                       ndarray[object, ndim=2] values,
                       ndarray[int64_t] labels):
-    '''
+    """
     Only aggregates on axis=0
-    '''
+    """
     cdef:
         Py_ssize_t i, j, N, K, lab
         object val
@@ -2209,9 +2209,9 @@ def group_last_bin_object(ndarray[object, ndim=2] out,
                           ndarray[int64_t] counts,
                           ndarray[object, ndim=2] values,
                           ndarray[int64_t] bins):
-    '''
+    """
     Only aggregates on axis=0
-    '''
+    """
     cdef:
         Py_ssize_t i, j, N, K, ngroups, b
         object val

pandas/compat/chainmap_impl.py

@@ -33,7 +33,7 @@ def wrapper(self):
 
 
 class ChainMap(MutableMapping):
-    ''' A ChainMap groups multiple dicts (or other mappings) together
+    """ A ChainMap groups multiple dicts (or other mappings) together
     to create a single, updateable view.
 
     The underlying mappings are stored in a list.  That list is public and can
@@ -43,13 +43,13 @@ class ChainMap(MutableMapping):
     In contrast, writes, updates, and deletions only operate on the first
     mapping.
 
-    '''
+    """
 
     def __init__(self, *maps):
-        '''Initialize a ChainMap by setting *maps* to the given mappings.
+        """Initialize a ChainMap by setting *maps* to the given mappings.
         If no mappings are provided, a single empty dictionary is used.
 
-        '''
+        """
         self.maps = list(maps) or [{}]          # always at least one map
 
     def __missing__(self, key):
@@ -101,10 +101,10 @@ def copy(self):
     __copy__ = copy
 
     def new_child(self, m=None):                # like Django's Context.push()
-        '''
+        """
         New ChainMap with a new map followed by all previous maps. If no
         map is provided, an empty dict is used.
-        '''
+        """
         if m is None:
             m = {}
         return self.__class__(m, *self.maps)

pandas/core/groupby.py

@@ -1566,10 +1566,9 @@ def size(self):
 
     @cache_readonly
     def _max_groupsize(self):
-        '''
+        """
         Compute size of largest group
-
-        '''
+        """
         # For many items in each group this is much faster than
         # self.size().max(), in worst case marginally slower
         if self.indices:

pandas/core/series.py

@@ -1129,15 +1129,15 @@ def to_sparse(self, kind='block', fill_value=None):
                             fill_value=fill_value).__finalize__(self)
 
     def _set_name(self, name, inplace=False):
-        '''
+        """
         Set the Series name.
 
         Parameters
         ----------
         name : str
         inplace : bool
             whether to modify `self` directly or return a copy
-        '''
+        """
         ser = self if inplace else self.copy()
         ser.name = name
         return ser

pandas/index.pyx

@@ -101,9 +101,9 @@ cdef class IndexEngine:
         return val in self.mapping
 
     cpdef get_value(self, ndarray arr, object key, object tz=None):
-        '''
+        """
         arr : 1-dimensional ndarray
-        '''
+        """
         cdef:
             object loc
             void* data_ptr
@@ -119,9 +119,9 @@ cdef class IndexEngine:
             return util.get_value_at(arr, loc)
 
     cpdef set_value(self, ndarray arr, object key, object value):
-        '''
+        """
         arr : 1-dimensional ndarray
-        '''
+        """
         cdef:
             object loc
             void* data_ptr

pandas/indexes/base.py

@@ -2569,10 +2569,10 @@ def _join_level(self, other, level, how='left', return_indexers=False,
         from .multi import MultiIndex
 
         def _get_leaf_sorter(labels):
-            '''
+            """
             returns sorter for the inner most level while preserving the
             order of higher levels
-            '''
+            """
             if labels[0].size == 0:
                 return np.empty(0, dtype='int64')
 

pandas/indexes/multi.py

@@ -1528,7 +1528,7 @@ def get_loc(self, key, method=None):
                                       'currently supported for MultiIndex')
 
         def _maybe_to_slice(loc):
-            '''convert integer indexer to boolean mask or slice if possible'''
+            """convert integer indexer to boolean mask or slice if possible"""
             if not isinstance(loc, np.ndarray) or loc.dtype != 'int64':
                 return loc
 

pandas/io/tests/test_sql.py

@@ -2385,8 +2385,6 @@ def test_uquery(self):
             sys.stdout = sys.__stdout__
 
     def test_keyword_as_column_names(self):
-        '''
-        '''
         df = DataFrame({'From': np.ones(5)})
         sql.to_sql(df, con=self.conn, name='testkeywords', index=False)
 
@@ -2751,8 +2749,6 @@ def test_uquery(self):
             sys.stdout = sys.__stdout__
 
     def test_keyword_as_column_names(self):
-        '''
-        '''
         _skip_if_no_pymysql()
         df = DataFrame({'From': np.ones(5)})
         sql.to_sql(df, con=self.conn, name='testkeywords',

pandas/io/wb.py

@@ -228,8 +228,8 @@ def _get_data(indicator="NY.GNS.ICTR.GN.ZS", country='US',
     return out,"Success"
 
 def get_countries():
-    '''Query information about countries
-    '''
+    """Query information about countries
+    """
     url = 'http://api.worldbank.org/countries/?per_page=1000&format=json'
     with urlopen(url) as response:
         data = response.read()
@@ -243,8 +243,8 @@ def get_countries():
     return data
 
 def get_indicators():
-    '''Download information about all World Bank data series
-    '''
+    """Download information about all World Bank data series
+    """
     url = 'http://api.worldbank.org/indicators?per_page=50000&format=json'
     with urlopen(url) as response:
         data = response.read()

pandas/lib.pyx

@@ -95,15 +95,15 @@ def values_from_object(object o):
     return o
 
 cpdef map_indices_list(list index):
-    '''
+    """
     Produce a dict mapping the values of the input array to their respective
     locations.
 
     Example:
         array(['hi', 'there']) --> {'hi' : 0 , 'there' : 1}
 
     Better to do this with Cython because of the enormous speed boost.
-    '''
+    """
     cdef Py_ssize_t i, length
     cdef dict result = {}
 
@@ -134,7 +134,7 @@ def ismember_nans(float64_t[:] arr, set values, bint hasnans):
 
 
 def ismember(ndarray arr, set values):
-    '''
+    """
     Checks whether
 
     Parameters
@@ -145,7 +145,7 @@ def ismember(ndarray arr, set values):
     Returns
     -------
     ismember : ndarray (boolean dtype)
-    '''
+    """
     cdef:
         Py_ssize_t i, n
         ndarray[uint8_t] result
@@ -160,7 +160,7 @@ def ismember(ndarray arr, set values):
     return result.view(np.bool_)
 
 def ismember_int64(ndarray[int64_t] arr, set values):
-    '''
+    """
     Checks whether
 
     Parameters
@@ -171,7 +171,7 @@ def ismember_int64(ndarray[int64_t] arr, set values):
     Returns
     -------
     ismember : ndarray (boolean dtype)
-    '''
+    """
     cdef:
         Py_ssize_t i, n
         ndarray[uint8_t] result
@@ -404,10 +404,10 @@ def isnullobj2d_old(ndarray[object, ndim=2] arr):
 @cython.wraparound(False)
 @cython.boundscheck(False)
 cpdef ndarray[object] list_to_object_array(list obj):
-    '''
+    """
     Convert list to object ndarray. Seriously can\'t believe I had to write this
     function
-    '''
+    """
     cdef:
         Py_ssize_t i, n = len(obj)
         ndarray[object] arr = np.empty(n, dtype=object)
@@ -542,9 +542,9 @@ def dicts_to_array(list dicts, list columns):
     return result
 
 def fast_zip(list ndarrays):
-    '''
+    """
     For zipping multiple ndarrays into an ndarray of tuples
-    '''
+    """
     cdef:
         Py_ssize_t i, j, k, n
         ndarray[object] result
@@ -959,9 +959,9 @@ cpdef ndarray[object] astype_str(ndarray arr):
     return result
 
 def clean_index_list(list obj):
-    '''
+    """
     Utility used in pandas.core.index._ensure_index
-    '''
+    """
     cdef:
         ndarray[object] converted
         Py_ssize_t i, n = len(obj)
@@ -1325,9 +1325,9 @@ cdef class _PandasNull:
 pandas_null = _PandasNull()
 
 def fast_zip_fillna(list ndarrays, fill_value=pandas_null):
-    '''
+    """
     For zipping multiple ndarrays into an ndarray of tuples
-    '''
+    """
     cdef:
         Py_ssize_t i, j, k, n
         ndarray[object] result