API: to_datetime, required unit with numerical

All numerical types now need a unit in to_datetime call.

* Update tests
* Add bool verification in tslib.pyx
* Bug correction with bool and unit in ['ms', 'us', 's', 'D']
  * to_datetime(True, unit='ms') did run without error
  * to_datetime(True, unit='ms', errors='ignore') returned None

Issue: #15836

Author: atbd

doc/source/whatsnew/v0.21.0.txt

@@ -131,13 +131,89 @@ Other Enhancements
 - :func:`pd.read_sas()` now recognizes much more of the most frequently used date (datetime) formats in SAS7BDAT files (:issue:`15871`).
 - :func:`DataFrame.items` and :func:`Series.items` is now present in both Python 2 and 3 and is lazy in all cases (:issue:`13918`, :issue:`17213`)
 
-
-
 .. _whatsnew_0210.api_breaking:
 
 Backwards incompatible API changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
+.. _whatsnew_0210.api_breaking.pandas_to_datetime:
+
+Numerical values need an explicit unit in pd.to_datetime
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+- :func:`to_datetime` requires an unit with numerical arg (scalar or iterable), if not provided it raises an error (:issue:`15836`)
+For example:
+
+.. ipython:: python
+
+    # Old behaviour:
+    In [1]: pd.to_datetime(42)
+    Out[1]: Timestamp('1970-01-01 00:00:00.000000042')
+
+    # New behaviour
+    In [1]: pd.to_datetime(42)
+    ---------------------------------------------------------------------------
+    ValueError                                Traceback (most recent call last)
+    <ipython-input-1-a8ad7fa1924c> in <module>()
+    ----> 1 pd.to_datetime(42)
+
+    /home/anthony/src/pandas/pandas/core/tools/datetimes.py in to_datetime(arg, errors, dayfirst, yearfirst, utc, box, format, exact, unit, infer_datetime_format, origin)
+        461     elif ((not isinstance(arg, DataFrame)) and
+        462           (check_numerical_arg() and unit is None and format is None)):
+    --> 463         raise ValueError("a unit is required in case of numerical arg")
+        464 
+        465     # handle origin
+
+    ValueError: a unit is required in case of numerical arg
+
+    In [2]: pd.to_datetime(42, unit='ns')
+    Out[2]: Timestamp('1970-01-01 00:00:00.000000042')
+
+Furthermore, this change fixes a bug with boolean values.
+
+.. ipython:: python
+    # Old behaviour
+    In [1]: pd.to_datetime(True, unit='ms')
+    Out[1]: Timestamp('1970-01-01 00:00:00.001000')
+
+    # New behaviour
+    In [2]: pd.to_datetime(True, unit='ms')
+    ---------------------------------------------------------------------------
+    TypeError                                 Traceback (most recent call last)
+    <ipython-input-9-d7a95ef3ecc2> in <module>()
+    ----> 1 pd.to_datetime(True, unit='ms')
+
+    /home/anthony/src/pandas/pandas/core/tools/datetimes.py in to_datetime(arg, errors, dayfirst, yearfirst, utc, box, format, exact, unit, infer_datetime_format, origin)
+        533         result = _convert_listlike(arg, box, format)
+        534     else:
+    --> 535         result = _convert_listlike(np.array([arg]), box, format)[0]
+        536 
+        537     return result
+
+    /home/anthony/src/pandas/pandas/core/tools/datetimes.py in _convert_listlike(arg, box, format, name, tz)
+        374             arg = getattr(arg, 'values', arg)
+        375             result = tslib.array_with_unit_to_datetime(arg, unit,
+    --> 376                                                        errors=errors)
+        377             if box:
+        378                 if errors == 'ignore':
+
+    /home/anthony/src/pandas/pandas/_libs/tslib.pyx in pandas._libs.tslib.array_with_unit_to_datetime()
+       2210 
+       2211 
+    -> 2212 cpdef array_with_unit_to_datetime(ndarray values, unit, errors='coerce'):
+       2213     """
+       2214     convert the ndarray according to the unit
+
+    /home/anthony/src/pandas/pandas/_libs/tslib.pyx in pandas._libs.tslib.array_with_unit_to_datetime()
+       2246             raise TypeError("{0} is not convertible to datetime"
+       2247                             .format(values.dtype))
+    -> 2248 
+       2249         # try a quick conversion to i8
+       2250         # if we have nulls that are not type-compat
+
+    TypeError: bool is not convertible to datetime
+
+Now boolean values raise an error everytime.
 
 .. _whatsnew_0210.api_breaking.deps:
 

pandas/_libs/tslib.pyx

@@ -31,7 +31,7 @@ cdef extern from "Python.h":
 from libc.stdlib cimport free
 
 from util cimport (is_integer_object, is_float_object, is_datetime64_object,
-                   is_timedelta64_object, INT64_MAX)
+                   is_bool_object, is_timedelta64_object, INT64_MAX)
 cimport util
 
 # this is our datetime.pxd
@@ -2242,6 +2242,9 @@ cpdef array_with_unit_to_datetime(ndarray values, unit, errors='coerce'):
     m = cast_from_unit(None, unit)
 
     if is_raise:
+        if np.issubdtype(values.dtype, np.bool_):
+            raise TypeError("{0} is not convertible to datetime"
+                            .format(values.dtype))
 
         # try a quick conversion to i8
         # if we have nulls that are not type-compat
@@ -2277,6 +2280,16 @@ cpdef array_with_unit_to_datetime(ndarray values, unit, errors='coerce'):
             if _checknull_with_nat(val):
                 iresult[i] = NPY_NAT
 
+            elif is_bool_object(val):
+                if is_raise:
+                    raise TypeError(
+                        "{0} is not convertible to datetime"
+                        .format(values.dtype)
+                    )
+                elif is_ignore:
+                    raise AssertionError
+                iresult[i] = NPY_NAT
+
             elif is_integer_object(val) or is_float_object(val):
 
                 if val != val or val == NPY_NAT:
@@ -2320,7 +2333,7 @@ cpdef array_with_unit_to_datetime(ndarray values, unit, errors='coerce'):
             else:
 
                 if is_raise:
-                    raise ValueError("non convertible value {0}"
+                    raise ValueError("non convertible value {0} "
                                      "with the unit '{1}'".format(
                                          val,
                                          unit))
@@ -2344,6 +2357,8 @@ cpdef array_with_unit_to_datetime(ndarray values, unit, errors='coerce'):
 
         if _checknull_with_nat(val):
             oresult[i] = NaT
+        elif is_bool_object(val):
+            oresult[i] = val
         elif is_integer_object(val) or is_float_object(val):
 
             if val != val or val == NPY_NAT:

pandas/core/dtypes/cast.py

@@ -155,7 +155,7 @@ def trans(x):  # noqa
                 if dtype.tz:
                     # convert to datetime and change timezone
                     from pandas import to_datetime
-                    result = to_datetime(result).tz_localize('utc')
+                    result = to_datetime(result, unit='ns').tz_localize('utc')
                     result = result.tz_convert(dtype.tz)
 
     except:
@@ -963,11 +963,13 @@ def maybe_cast_to_datetime(value, dtype, errors='raise'):
                                                                 dtype):
                     try:
                         if is_datetime64:
-                            value = to_datetime(value, errors=errors)._values
+                            value = to_datetime(value, unit='ns',
+                                                errors=errors)._values
                         elif is_datetime64tz:
                             # input has to be UTC at this point, so just
                             # localize
-                            value = (to_datetime(value, errors=errors)
+                            value = (to_datetime(value, unit='ns',
+                                                 errors=errors)
                                      .tz_localize('UTC')
                                      .tz_convert(dtype.tz)
                                      )

pandas/core/indexes/datetimes.py

@@ -277,6 +277,7 @@ def __new__(cls, data=None,
 
         dayfirst = kwargs.pop('dayfirst', None)
         yearfirst = kwargs.pop('yearfirst', None)
+        unit = kwargs.pop('unit', None)
 
         freq_infer = False
         if not isinstance(freq, DateOffset):
@@ -333,7 +334,7 @@ def __new__(cls, data=None,
         if not (is_datetime64_dtype(data) or is_datetimetz(data) or
                 is_integer_dtype(data)):
             data = tools.to_datetime(data, dayfirst=dayfirst,
-                                     yearfirst=yearfirst)
+                                     unit=unit, yearfirst=yearfirst)
 
         if issubclass(data.dtype.type, np.datetime64) or is_datetimetz(data):
 

pandas/core/tools/datetimes.py

@@ -235,7 +235,7 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
         - If True, require an exact format match.
         - If False, allow the format to match anywhere in the target string.
 
-    unit : string, default 'ns'
+    unit : string, default None
         unit of the arg (D,s,ms,us,ns) denote the unit, which is an
         integer or float number. This will be based off the origin.
         Example, with unit='ms' and origin='unix' (the default), this
@@ -342,6 +342,7 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
     pandas.to_timedelta : Convert argument to timedelta.
     """
     from pandas.core.indexes.datetimes import DatetimeIndex
+    from pandas.core.frame import DataFrame
 
     tz = 'utc' if utc else None
 
@@ -451,8 +452,15 @@ def _convert_listlike(arg, box, format, name=None, tz=tz):
             except (ValueError, TypeError):
                 raise e
 
+    def check_numerical_arg():
+        return ((is_scalar(arg) and (is_integer(arg) or is_float(arg))) or
+                (is_numeric_dtype(np.asarray(arg)) and np.asarray(arg).size))
+
     if arg is None:
         return None
+    elif ((not isinstance(arg, DataFrame)) and
+          (check_numerical_arg() and unit is None and format is None)):
+        raise ValueError("a unit is required in case of numerical arg")
 
     # handle origin
     if origin == 'julian':
@@ -479,8 +487,7 @@ def _convert_listlike(arg, box, format, name=None, tz=tz):
 
         # arg must be a numeric
         original = arg
-        if not ((is_scalar(arg) and (is_integer(arg) or is_float(arg))) or
-                is_numeric_dtype(np.asarray(arg))):
+        if not check_numerical_arg():
             raise ValueError(
                 "'{arg}' is not compatible with origin='{origin}'; "
                 "it must be numeric with a unit specified ".format(
@@ -605,7 +612,7 @@ def f(value):
     if len(excess):
         raise ValueError("extra keys have been passed "
                          "to the datetime assemblage: "
-                         "[{excess}]".format(','.join(excess=excess)))
+                         "[{}]".format(','.join(excess)))
 
     def coerce(values):
         # we allow coercion to if errors allows