diff options
Diffstat (limited to 'doc/source')
| -rw-r--r-- | doc/source/dev/development_environment.rst | 2 | ||||
| -rw-r--r-- | doc/source/reference/arrays.datetime.rst | 6 | ||||
| -rw-r--r-- | doc/source/release/1.11.0-notes.rst | 4 | ||||
| -rw-r--r-- | doc/source/user/basics.io.genfromtxt.rst | 20 |
4 files changed, 15 insertions, 17 deletions
diff --git a/doc/source/dev/development_environment.rst b/doc/source/dev/development_environment.rst index 297502b31..c73fb3858 100644 --- a/doc/source/dev/development_environment.rst +++ b/doc/source/dev/development_environment.rst @@ -145,7 +145,7 @@ Running tests Besides using ``runtests.py``, there are various ways to run the tests. Inside the interpreter, tests can be run like this:: - >>> np.test() + >>> np.test() # doctest: +SKIPBLOCK >>> np.test('full') # Also run tests marked as slow >>> np.test('full', verbose=2) # Additionally print test name/file diff --git a/doc/source/reference/arrays.datetime.rst b/doc/source/reference/arrays.datetime.rst index 2225eedb3..9c45e04c7 100644 --- a/doc/source/reference/arrays.datetime.rst +++ b/doc/source/reference/arrays.datetime.rst @@ -368,7 +368,7 @@ times in UTC. By default, creating a datetime64 object from a string or printing it would convert from or to local time:: # old behavior - >>>> np.datetime64('2000-01-01T00:00:00') + >>> np.datetime64('2000-01-01T00:00:00') numpy.datetime64('2000-01-01T00:00:00-0800') # note the timezone offset -08:00 A consensus of datetime64 users agreed that this behavior is undesirable @@ -378,7 +378,7 @@ most use cases, a timezone naive datetime type is preferred, similar to the datetime64 no longer assumes that input is in local time, nor does it print local times:: - >>>> np.datetime64('2000-01-01T00:00:00') + >>> np.datetime64('2000-01-01T00:00:00') numpy.datetime64('2000-01-01T00:00:00') For backwards compatibility, datetime64 still parses timezone offsets, which @@ -393,4 +393,4 @@ As a corollary to this change, we no longer prohibit casting between datetimes with date units and datetimes with timeunits. With timezone naive datetimes, the rule for casting from dates to times is no longer ambiguous. -.. _pandas: http://pandas.pydata.org
\ No newline at end of file +.. _pandas: http://pandas.pydata.org diff --git a/doc/source/release/1.11.0-notes.rst b/doc/source/release/1.11.0-notes.rst index 1a179657b..36cd1d65a 100644 --- a/doc/source/release/1.11.0-notes.rst +++ b/doc/source/release/1.11.0-notes.rst @@ -85,7 +85,7 @@ times in UTC. By default, creating a datetime64 object from a string or printing it would convert from or to local time:: # old behavior - >>>> np.datetime64('2000-01-01T00:00:00') + >>> np.datetime64('2000-01-01T00:00:00') numpy.datetime64('2000-01-01T00:00:00-0800') # note the timezone offset -08:00 @@ -96,7 +96,7 @@ type is preferred, similar to the ``datetime.datetime`` type in the Python standard library. Accordingly, datetime64 no longer assumes that input is in local time, nor does it print local times:: - >>>> np.datetime64('2000-01-01T00:00:00') + >>> np.datetime64('2000-01-01T00:00:00') numpy.datetime64('2000-01-01T00:00:00') For backwards compatibility, datetime64 still parses timezone offsets, which diff --git a/doc/source/user/basics.io.genfromtxt.rst b/doc/source/user/basics.io.genfromtxt.rst index 19e37eabc..3fce6a8aa 100644 --- a/doc/source/user/basics.io.genfromtxt.rst +++ b/doc/source/user/basics.io.genfromtxt.rst @@ -98,13 +98,11 @@ This behavior can be overwritten by setting the optional argument >>> # Without autostrip >>> np.genfromtxt(StringIO(data), delimiter=",", dtype="|U5") array([['1', ' abc ', ' 2'], - ['3', ' xxx', ' 4']], - dtype='|U5') + ['3', ' xxx', ' 4']], dtype='<U5') >>> # With autostrip >>> np.genfromtxt(StringIO(data), delimiter=",", dtype="|U5", autostrip=True) array([['1', 'abc', '2'], - ['3', 'xxx', '4']], - dtype='|U5') + ['3', 'xxx', '4']], dtype='<U5') The ``comments`` argument @@ -127,11 +125,11 @@ marker(s) is simply ignored:: ... 9, 0 ... """ >>> np.genfromtxt(StringIO(data), comments="#", delimiter=",") - [[ 1. 2.] - [ 3. 4.] - [ 5. 6.] - [ 7. 8.] - [ 9. 0.]] + array([[1., 2.], + [3., 4.], + [5., 6.], + [7., 8.], + [9., 0.]]) .. versionadded:: 1.7.0 @@ -376,12 +374,12 @@ single element of the wanted type. In the following example, the second column is converted from as string representing a percentage to a float between 0 and 1:: - >>> convertfunc = lambda x: float(x.strip("%"))/100. + >>> convertfunc = lambda x: float(x.strip(b"%"))/100. >>> data = u"1, 2.3%, 45.\n6, 78.9%, 0" >>> names = ("i", "p", "n") >>> # General case ..... >>> np.genfromtxt(StringIO(data), delimiter=",", names=names) - array([(1.0, nan, 45.0), (6.0, nan, 0.0)], + array([(1., nan, 45.), (6., nan, 0.)], dtype=[('i', '<f8'), ('p', '<f8'), ('n', '<f8')]) We need to keep in mind that by default, ``dtype=float``. A float is |