Merge branch 'master' into BUG-20591

Author: JustinZhengBC

doc/source/whatsnew/v0.24.0.rst

@@ -1077,6 +1077,7 @@ Deprecations
 - Timezone converting a tz-aware ``datetime.datetime`` or :class:`Timestamp` with :class:`Timestamp` and the ``tz`` argument is now deprecated. Instead, use :meth:`Timestamp.tz_convert` (:issue:`23579`)
 - :func:`pandas.types.is_period` is deprecated in favor of `pandas.types.is_period_dtype` (:issue:`23917`)
 - :func:`pandas.types.is_datetimetz` is deprecated in favor of `pandas.types.is_datetime64tz` (:issue:`23917`)
+- Creating a :class:`TimedeltaIndex` or :class:`DatetimeIndex` by passing range arguments `start`, `end`, and `periods` is deprecated in favor of :func:`timedelta_range` and :func:`date_range` (:issue:`23919`)
 
 .. _whatsnew_0240.deprecations.datetimelike_int_ops:
 

pandas/_libs/tslibs/timestamps.pyx

@@ -377,13 +377,15 @@ cdef class _Timestamp(datetime):
             neg_other = -other
             return self + neg_other
 
+        typ = getattr(other, '_typ', None)
+
         # a Timestamp-DatetimeIndex -> yields a negative TimedeltaIndex
-        elif getattr(other, '_typ', None) == 'datetimeindex':
+        if typ in ('datetimeindex', 'datetimearray'):
             # timezone comparison is performed in DatetimeIndex._sub_datelike
             return -other.__sub__(self)
 
         # a Timestamp-TimedeltaIndex -> yields a negative TimedeltaIndex
-        elif getattr(other, '_typ', None) == 'timedeltaindex':
+        elif typ in ('timedeltaindex', 'timedeltaarray'):
             return (-other).__add__(self)
 
         elif other is NaT:

pandas/_version.py

@@ -238,14 +238,14 @@ def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command):
         # tag
         full_tag = mo.group(1)
         if not full_tag.startswith(tag_prefix):
+            fmt = ("tag '{full_tag}' doesn't start with prefix "
+                   "'{tag_prefix}'")
+            msg = fmt.format(full_tag=full_tag, tag_prefix=tag_prefix)
             if verbose:
-                fmt = "tag '{full_tag}' doesn't start with prefix " \
-                      "'{tag_prefix}'"
-                print(fmt.format(full_tag=full_tag, tag_prefix=tag_prefix))
-            pieces["error"] = ("tag '{full_tag}' doesn't start with "
-                               "prefix '{tag_prefix}'".format(
-                                   full_tag, tag_prefix))
+                print(msg)
+            pieces["error"] = msg
             return pieces
+
         pieces["closest-tag"] = full_tag[len(tag_prefix):]
 
         # distance: number of commits since tag

pandas/core/arrays/timedeltas.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 
-from pandas._libs import tslibs
+from pandas._libs import algos, tslibs
 from pandas._libs.tslibs import NaT, Timedelta, Timestamp, iNaT
 from pandas._libs.tslibs.fields import get_timedelta_field
 from pandas._libs.tslibs.timedeltas import (
@@ -24,7 +24,7 @@
 from pandas.core.dtypes.missing import isna
 
 from pandas.core import ops
-from pandas.core.algorithms import checked_add_with_arr
+from pandas.core.algorithms import checked_add_with_arr, unique1d
 import pandas.core.common as com
 
 from pandas.tseries.frequencies import to_offset
@@ -162,15 +162,29 @@ def _simple_new(cls, values, freq=None, dtype=_TD_DTYPE):
         result._freq = freq
         return result
 
-    def __new__(cls, values, freq=None, dtype=_TD_DTYPE):
+    def __new__(cls, values, freq=None, dtype=_TD_DTYPE, copy=False):
 
         freq, freq_infer = dtl.maybe_infer_freq(freq)
 
-        values = np.array(values, copy=False)
-        if values.dtype == np.object_:
-            values = array_to_timedelta64(values)
+        values, inferred_freq = sequence_to_td64ns(
+            values, copy=copy, unit=None)
+        if inferred_freq is not None:
+            if freq is not None and freq != inferred_freq:
+                raise ValueError('Inferred frequency {inferred} from passed '
+                                 'values does not conform to passed frequency '
+                                 '{passed}'
+                                 .format(inferred=inferred_freq,
+                                         passed=freq.freqstr))
+            elif freq is None:
+                freq = inferred_freq
+                freq_infer = False
 
         result = cls._simple_new(values, freq=freq)
+        # check that we are matching freqs
+        if inferred_freq is None and len(result) > 0:
+            if freq is not None and not freq_infer:
+                cls._validate_frequency(result, freq)
+
         if freq_infer:
             result.freq = to_offset(result.inferred_freq)
 
@@ -227,6 +241,21 @@ def _validate_fill_value(self, fill_value):
                              "Got '{got}'.".format(got=fill_value))
         return fill_value
 
+    # monotonicity/uniqueness properties are called via frequencies.infer_freq,
+    #  see GH#23789
+
+    @property
+    def _is_monotonic_increasing(self):
+        return algos.is_monotonic(self.asi8, timelike=True)[0]
+
+    @property
+    def _is_monotonic_decreasing(self):
+        return algos.is_monotonic(self.asi8, timelike=True)[1]
+
+    @property
+    def _is_unique(self):
+        return len(unique1d(self.asi8)) == len(self)
+
     # ----------------------------------------------------------------
     # Arithmetic Methods
 
@@ -283,7 +312,7 @@ def _add_datetimelike_scalar(self, other):
         result = checked_add_with_arr(i8, other.value,
                                       arr_mask=self._isnan)
         result = self._maybe_mask_results(result)
-        return DatetimeArrayMixin(result, tz=other.tz)
+        return DatetimeArrayMixin(result, tz=other.tz, freq=self.freq)
 
     def _addsub_offset_array(self, other, op):
         # Add or subtract Array-like of DateOffset objects

pandas/core/frame.py

@@ -369,6 +369,9 @@ def _constructor_expanddim(self):
         from pandas.core.panel import Panel
         return Panel
 
+    # ----------------------------------------------------------------------
+    # Constructors
+
     def __init__(self, data=None, index=None, columns=None, dtype=None,
                  copy=False):
         if data is None:
@@ -575,6 +578,8 @@ def _get_axes(N, K, index=index, columns=columns):
 
         return create_block_manager_from_blocks([values], [columns, index])
 
+    # ----------------------------------------------------------------------
+
     @property
     def axes(self):
         """
@@ -643,6 +648,9 @@ def _is_homogeneous_type(self):
         else:
             return not self._data.is_mixed_type
 
+    # ----------------------------------------------------------------------
+    # Rendering Methods
+
     def _repr_fits_vertical_(self):
         """
         Check length against max_rows.
@@ -770,6 +778,57 @@ def _repr_html_(self):
         else:
             return None
 
+    @Substitution(header='Write out the column names. If a list of strings '
+                         'is given, it is assumed to be aliases for the '
+                         'column names')
+    @Substitution(shared_params=fmt.common_docstring,
+                  returns=fmt.return_docstring)
+    def to_string(self, buf=None, columns=None, col_space=None, header=True,
+                  index=True, na_rep='NaN', formatters=None, float_format=None,
+                  sparsify=None, index_names=True, justify=None,
+                  max_rows=None, max_cols=None, show_dimensions=False,
+                  decimal='.', line_width=None):
+        """
+        Render a DataFrame to a console-friendly tabular output.
+        %(shared_params)s
+        line_width : int, optional
+            Width to wrap a line in characters.
+        %(returns)s
+        See Also
+        --------
+        to_html : Convert DataFrame to HTML.
+
+        Examples
+        --------
+        >>> d = {'col1': [1, 2, 3], 'col2': [4, 5, 6]}
+        >>> df = pd.DataFrame(d)
+        >>> print(df.to_string())
+           col1  col2
+        0     1     4
+        1     2     5
+        2     3     6
+        """
+
+        formatter = fmt.DataFrameFormatter(self, buf=buf, columns=columns,
+                                           col_space=col_space, na_rep=na_rep,
+                                           formatters=formatters,
+                                           float_format=float_format,
+                                           sparsify=sparsify, justify=justify,
+                                           index_names=index_names,
+                                           header=header, index=index,
+                                           max_rows=max_rows,
+                                           max_cols=max_cols,
+                                           show_dimensions=show_dimensions,
+                                           decimal=decimal,
+                                           line_width=line_width)
+        formatter.to_string()
+
+        if buf is None:
+            result = formatter.buf.getvalue()
+            return result
+
+    # ----------------------------------------------------------------------
+
     @property
     def style(self):
         """
@@ -2051,55 +2110,6 @@ def to_parquet(self, fname, engine='auto', compression='snappy',
                    compression=compression, index=index,
                    partition_cols=partition_cols, **kwargs)
 
-    @Substitution(header='Write out the column names. If a list of strings '
-                         'is given, it is assumed to be aliases for the '
-                         'column names')
-    @Substitution(shared_params=fmt.common_docstring,
-                  returns=fmt.return_docstring)
-    def to_string(self, buf=None, columns=None, col_space=None, header=True,
-                  index=True, na_rep='NaN', formatters=None, float_format=None,
-                  sparsify=None, index_names=True, justify=None,
-                  max_rows=None, max_cols=None, show_dimensions=False,
-                  decimal='.', line_width=None):
-        """
-        Render a DataFrame to a console-friendly tabular output.
-        %(shared_params)s
-        line_width : int, optional
-            Width to wrap a line in characters.
-        %(returns)s
-        See Also
-        --------
-        to_html : Convert DataFrame to HTML.
-
-        Examples
-        --------
-        >>> d = {'col1': [1, 2, 3], 'col2': [4, 5, 6]}
-        >>> df = pd.DataFrame(d)
-        >>> print(df.to_string())
-           col1  col2
-        0     1     4
-        1     2     5
-        2     3     6
-        """
-
-        formatter = fmt.DataFrameFormatter(self, buf=buf, columns=columns,
-                                           col_space=col_space, na_rep=na_rep,
-                                           formatters=formatters,
-                                           float_format=float_format,
-                                           sparsify=sparsify, justify=justify,
-                                           index_names=index_names,
-                                           header=header, index=index,
-                                           max_rows=max_rows,
-                                           max_cols=max_cols,
-                                           show_dimensions=show_dimensions,
-                                           decimal=decimal,
-                                           line_width=line_width)
-        formatter.to_string()
-
-        if buf is None:
-            result = formatter.buf.getvalue()
-            return result
-
     @Substitution(header='Whether to print column labels, default True')
     @Substitution(shared_params=fmt.common_docstring,
                   returns=fmt.return_docstring)
@@ -2158,6 +2168,8 @@ def to_html(self, buf=None, columns=None, col_space=None, header=True,
         if buf is None:
             return formatter.buf.getvalue()
 
+    # ----------------------------------------------------------------------
+
     def info(self, verbose=None, buf=None, max_cols=None, memory_usage=None,
              null_counts=None):
         """