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doc/source/user_guide/timeseries.rst

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@@ -307,25 +307,25 @@ Epoch timestamps
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~~~~~~~~~~~~~~~~
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pandas supports converting integer or float epoch times to ``Timestamp`` and
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``DatetimeIndex``. The default unit is nanoseconds, since that is how ``Timestamp``
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objects are stored internally. However, epochs are often stored in another ``unit``
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``DatetimeIndex``. The default input_unit is nanoseconds, since that is how ``Timestamp``
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objects are stored internally. However, epochs are often stored in another ``input_unit``
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which can be specified. These are computed from the starting point specified by the
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``origin`` parameter.
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.. ipython:: python
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pd.to_datetime(
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[1349720105, 1349806505, 1349892905, 1349979305, 1350065705], unit="s"
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[1349720105, 1349806505, 1349892905, 1349979305, 1350065705], input_unit="s"
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)
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pd.to_datetime(
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[1349720105100, 1349720105200, 1349720105300, 1349720105400, 1349720105500],
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unit="ms",
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input_unit="ms",
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)
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.. note::
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The ``unit`` parameter does not use the same strings as the ``format`` parameter
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The ``input_unit`` parameter does not use the same strings as the ``format`` parameter
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that was discussed :ref:`above<timeseries.converting.format>`. The
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available units are listed on the documentation for :func:`pandas.to_datetime`.
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