@@ -525,8 +525,8 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
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'ms', 'us', 'ns']) or plurals of the same
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>>> df = pd.DataFrame({'year': [2015, 2016],
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- 'month': [2, 3],
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- 'day': [4, 5]})
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+ ... 'month': [2, 3],
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+ ... 'day': [4, 5]})
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>>> pd.to_datetime(df)
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0 2015-02-04
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1 2016-03-05
@@ -548,8 +548,7 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
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Passing infer_datetime_format=True can often-times speedup a parsing
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if its not an ISO8601 format exactly, but in a regular format.
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- >>> s = pd.Series(['3/11/2000', '3/12/2000', '3/13/2000']*1000)
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-
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+ >>> s = pd.Series(['3/11/2000', '3/12/2000', '3/13/2000'] * 1000)
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>>> s.head()
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0 3/11/2000
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1 3/12/2000
@@ -558,10 +557,10 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
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4 3/12/2000
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dtype: object
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- >>> %timeit pd.to_datetime(s,infer_datetime_format=True)
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+ >>> %timeit pd.to_datetime(s,infer_datetime_format=True) # doctest: +SKIP
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100 loops, best of 3: 10.4 ms per loop
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- >>> %timeit pd.to_datetime(s,infer_datetime_format=False)
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+ >>> %timeit pd.to_datetime(s,infer_datetime_format=False) # doctest: +SKIP
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1 loop, best of 3: 471 ms per loop
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Using a unix epoch time
@@ -577,10 +576,9 @@ def to_datetime(arg, errors='raise', dayfirst=False, yearfirst=False,
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Using a non-unix epoch origin
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>>> pd.to_datetime([1, 2, 3], unit='D',
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- origin=pd.Timestamp('1960-01-01'))
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- 0 1960-01-02
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- 1 1960-01-03
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- 2 1960-01-04
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+ ... origin=pd.Timestamp('1960-01-01'))
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+ DatetimeIndex(['1960-01-02', '1960-01-03', '1960-01-04'], \
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+ dtype='datetime64[ns]', freq=None)
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"""
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if arg is None :
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return None
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