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doc/source/io.rst
@@ -1580,12 +1580,19 @@ You can pass in a URL to a CSV file:
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df = pd.read_csv('https://download.bls.gov/pub/time.series/cu/cu.item',
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sep='\t')
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-S3 URLs are handled as well:
+S3 URLs are handled as well but require installing the `S3Fs
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+<https://pypi.org/project/s3fs/>`_ library:
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.. code-block:: python
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df = pd.read_csv('s3://pandas-test/tips.csv')
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+If your S3 bucket requires cedentials you will need to set them as environment
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+variables or in the ``~/.aws/credentials`` config file, refer to the `S3Fs
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+documentation on credentials
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+<https://s3fs.readthedocs.io/en/latest/#credentials>`_.
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+
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Writing out Data
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''''''''''''''''
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