DOC: Fix quotes position in Timestamp and Timedelta

pandas/_libs/tslibs/timedeltas.pyx

@@ -253,8 +253,10 @@ def array_to_timedelta64(object[:] values, unit='ns', errors='raise'):
 
 
 cdef inline int64_t cast_from_unit(object ts, object unit) except? -1:
-    """ return a casting of the unit represented to nanoseconds
-        round the fractional part of a float to our precision, p """
+    """
+	return a casting of the unit represented to nanoseconds
+        round the fractional part of a float to our precision, p
+	"""
     cdef:
         int64_t m
         int p
@@ -482,7 +484,6 @@ cdef inline parse_timedelta_string(object ts):
 
 cdef inline int64_t timedelta_as_neg(int64_t value, bint neg):
     """
-
     Parameters
     ----------
     value : int64_t of the timedelta value
@@ -495,7 +496,6 @@ cdef inline int64_t timedelta_as_neg(int64_t value, bint neg):
 
 cdef inline timedelta_from_spec(object number, object frac, object unit):
     """
-
     Parameters
     ----------
     number : a list of number digits
@@ -739,9 +739,18 @@ cdef _to_py_int_float(v):
 # heavy lifting.
 cdef class _Timedelta(timedelta):
     cdef readonly:
-        int64_t value      # nanoseconds
-        object freq        # frequency reference
-        bint is_populated  # are my components populated
+        int64_t value
+        """
+        nanoseconds
+        """
+        object freq
+        """
+        frequency reference
+        """
+        bint is_populated
+        """
+        are my components populated
+        """
         int64_t _d, _h, _m, _s, _ms, _us, _ns
 
     # higher than np.ndarray and np.matrix
@@ -813,7 +822,9 @@ cdef class _Timedelta(timedelta):
         return timedelta(microseconds=int(self.value) / 1000)
 
     def to_timedelta64(self):
-        """ Returns a numpy.timedelta64 object with 'ns' precision """
+        """
+		Returns a numpy.timedelta64 object with 'ns' precision
+		"""
         return np.timedelta64(self.value, 'ns')
 
     def total_seconds(self):
@@ -823,12 +834,16 @@ cdef class _Timedelta(timedelta):
         return self.value / 1e9
 
     def view(self, dtype):
-        """ array view compat """
+        """
+	array view compat
+	"""
         return np.timedelta64(self.value).view(dtype)
 
     @property
     def components(self):
-        """ Return a Components NamedTuple-like """
+        """
+	Return a Components NamedTuple-like
+	"""
         self._ensure_components()
         # return the named tuple
         return Components(self._d, self._h, self._m, self._s,
@@ -897,6 +912,7 @@ cdef class _Timedelta(timedelta):
         >>> td.asm8
         numpy.timedelta64(42,'ns')
         """
+
         return np.int64(self.value).view('m8[ns]')
 
     @property
@@ -993,15 +1009,13 @@ cdef class _Timedelta(timedelta):
 
     def _repr_base(self, format=None):
         """
-
         Parameters
         ----------
         format : None|all|sub_day|long
 
         Returns
         -------
         converted : string of a Timedelta
-
         """
         cdef object sign, seconds_pretty, subs, fmt, comp_dict
 
@@ -1127,7 +1141,6 @@ class Timedelta(_Timedelta):
     Notes
     -----
     The ``.value`` attribute is always in ns.
-
     """
     def __new__(cls, object value=_no_input, unit=None, **kwargs):
         cdef _Timedelta td_base
@@ -1473,7 +1486,8 @@ cdef _rfloordiv(int64_t value, right):
 cdef _broadcast_floordiv_td64(int64_t value, object other,
                               object (*operation)(int64_t value,
                                                   object right)):
-    """Boilerplate code shared by Timedelta.__floordiv__ and
+    """
+	Boilerplate code shared by Timedelta.__floordiv__ and
     Timedelta.__rfloordiv__ because np.timedelta64 does not implement these.
 
     Parameters

pandas/_libs/tslibs/timestamps.pyx

@@ -59,7 +59,9 @@ def maybe_integer_op_deprecated(obj):
 cdef inline object create_timestamp_from_ts(int64_t value,
                                             npy_datetimestruct dts,
                                             object tz, object freq):
-    """ convenience routine to construct a Timestamp from its parts """
+    """ 
+    onvenience routine to construct a Timestamp from its parts
+    """
     cdef _Timestamp ts_base
     ts_base = _Timestamp.__new__(Timestamp, dts.year, dts.month,
                                  dts.day, dts.hour, dts.min,
@@ -113,7 +115,9 @@ class RoundTo(enum.Enum):
 
 
 cdef inline _npdivmod(x1, x2):
-    """implement divmod for numpy < 1.13"""
+    """
+    implement divmod for numpy < 1.13
+    """
     return np.floor_divide(x1, x2), np.remainder(x1, x2)
 
 
@@ -326,7 +330,9 @@ cdef class _Timestamp(datetime):
                         self.microsecond, self.tzinfo)
 
     cpdef to_datetime64(self):
-        """ Returns a numpy.datetime64 object with 'ns' precision """
+        """
+        Returns a numpy.datetime64 object with 'ns' precision
+        """
         return np.datetime64(self.value, 'ns')
 
     def __add__(self, other):
@@ -413,7 +419,9 @@ cdef class _Timestamp(datetime):
         return datetime.__sub__(self, other)
 
     cdef int64_t _maybe_convert_value_to_local(self):
-        """Convert UTC i8 value to local i8 value if tz exists"""
+        """
+        Convert UTC i8 value to local i8 value if tz exists
+        """
         cdef:
             int64_t val
         val = self.value
@@ -500,7 +508,9 @@ cdef class _Timestamp(datetime):
         return Timedelta(nanoseconds=1)
 
     def timestamp(self):
-        """Return POSIX timestamp as float."""
+        """
+	Return POSIX timestamp as float.
+	"""
         # py27 compat, see GH#17329
         return round(self.value / 1e9, 6)
 
@@ -512,7 +522,8 @@ cdef class _Timestamp(datetime):
 
 
 class Timestamp(_Timestamp):
-    """Pandas replacement for datetime.datetime
+    """
+	Pandas replacement for datetime.datetime
 
     Timestamp is the pandas equivalent of python's Datetime
     and is interchangeable with it in most cases. It's the type used
@@ -1189,7 +1200,9 @@ class Timestamp(_Timestamp):
 
         # replace
         def validate(k, v):
-            """ validate integers """
+            """
+	    validate integers
+	    """
             if not is_integer_object(v):
                 raise ValueError("value must be an integer, received "
                                  "{v} for {k}".format(v=type(v), k=k))

pandas/core/indexes/datetimes.py

@@ -42,8 +42,10 @@
 
 
 def _new_DatetimeIndex(cls, d):
-    """ This is called upon unpickling, rather than the default which doesn't
-    have arguments and breaks __new__ """
+    """
+    This is called upon unpickling, rather than the default which doesn't
+    have arguments and breaks __new__
+    """
 
     # data are already in UTC
     # so need to localize
@@ -397,7 +399,9 @@ def nbytes(self):
 
     @cache_readonly
     def _is_dates_only(self):
-        """Return a boolean if we are only dates (and don't have a timezone)"""
+        """
+        Return a boolean if we are only dates (and don't have a timezone)
+        """
         from pandas.io.formats.format import _is_dates_only
         return _is_dates_only(self.values) and self.tz is None
 
@@ -411,7 +415,9 @@ def __reduce__(self):
         return _new_DatetimeIndex, (self.__class__, d), None
 
     def __setstate__(self, state):
-        """Necessary for making this object picklable"""
+        """
+        Necessary for making this object picklable
+        """
         if isinstance(state, dict):
             super(DatetimeIndex, self).__setstate__(state)
 
@@ -439,13 +445,17 @@ def __setstate__(self, state):
     _unpickle_compat = __setstate__
 
     def _convert_for_op(self, value):
-        """ Convert value to be insertable to ndarray """
+        """
+        Convert value to be insertable to ndarray
+        """
         if self._has_same_tz(value):
             return _to_m8(value)
         raise ValueError('Passed item and index have different timezone')
 
     def _maybe_update_attributes(self, attrs):
-        """ Update Index attributes (e.g. freq) depending on op """
+        """
+        Update Index attributes (e.g. freq) depending on op
+        """
         freq = attrs.get('freq', None)
         if freq is not None:
             # no need to infer if freq is None

pandas/core/indexes/interval.py

@@ -1,4 +1,6 @@
-""" define the IntervalIndex """
+"""
+define the IntervalIndex
+"""
 import textwrap
 import warnings
 
@@ -225,7 +227,9 @@ def _shallow_copy(self, left=None, right=None, **kwargs):
 
     @cache_readonly
     def _isnan(self):
-        """Return a mask indicating if each value is NA"""
+        """
+        Return a mask indicating if each value is NA
+        """
         if self._mask is None:
             self._mask = isna(self.left)
         return self._mask
@@ -381,7 +385,9 @@ def _ndarray_values(self):
         return np.array(self._data)
 
     def __array__(self, result=None):
-        """ the array interface, return my values """
+        """
+        the array interface, return my values
+        """
         return self._ndarray_values
 
     def __array_wrap__(self, result, context=None):
@@ -413,12 +419,16 @@ def astype(self, dtype, copy=True):
 
     @cache_readonly
     def dtype(self):
-        """Return the dtype object of the underlying data"""
+        """
+        Return the dtype object of the underlying data
+        """
         return self._data.dtype
 
     @property
     def inferred_type(self):
-        """Return a string of the type inferred from the values"""
+        """
+        Return a string of the type inferred from the values
+        """
         return 'interval'
 
     @Appender(Index.memory_usage.__doc__)
@@ -718,7 +728,8 @@ def _find_non_overlapping_monotonic_bounds(self, key):
         return start, stop
 
     def get_loc(self, key, method=None):
-        """Get integer location, slice or boolean mask for requested label.
+        """
+        Get integer location, slice or boolean mask for requested label.
 
         Parameters
         ----------
@@ -1014,7 +1025,9 @@ def _format_with_header(self, header, **kwargs):
         return header + list(self._format_native_types(**kwargs))
 
     def _format_native_types(self, na_rep='', quoting=None, **kwargs):
-        """ actually format my specific types """
+        """
+        actually format my specific types
+        """
         from pandas.io.formats.format import IntervalArrayFormatter
         return IntervalArrayFormatter(values=self,
                                       na_rep=na_rep,
@@ -1140,15 +1153,19 @@ def is_all_dates(self):
 
 
 def _is_valid_endpoint(endpoint):
-    """helper for interval_range to check if start/end are valid types"""
+    """
+    helper for interval_range to check if start/end are valid types
+    """
     return any([is_number(endpoint),
                 isinstance(endpoint, Timestamp),
                 isinstance(endpoint, Timedelta),
                 endpoint is None])
 
 
 def _is_type_compatible(a, b):
-    """helper for interval_range to check type compat of start/end/freq"""
+    """
+    helper for interval_range to check type compat of start/end/freq
+    """
     is_ts_compat = lambda x: isinstance(x, (Timestamp, DateOffset))
     is_td_compat = lambda x: isinstance(x, (Timedelta, DateOffset))
     return ((is_number(a) and is_number(b)) or