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doc/source/user_guide/io.rst

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@@ -48,40 +48,39 @@ The pandas I/O API is a set of top level ``reader`` functions accessed like
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Google Colab
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^^^^^^^^^^^^
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Google Colab provides several ways to load data into pandas DataFrames:
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Google Colab provides several ways to load data into pandas DataFrames.
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**Upload files directly**
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.. code-block:: python
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from google.colab import files
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uploaded = files.upload()
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df = pd.read_csv('your_file.csv')
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df = pd.read_csv("your_file.csv")
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**Mount Google Drive**
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.. code-block:: python
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from google.colab import drive
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drive.mount('/content/drive')
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df = pd.read_csv('/content/drive/MyDrive/your_file.csv')
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drive.mount("/content/drive")
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df = pd.read_csv("/content/drive/MyDrive/your_file.csv")
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**URLs work normally**
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.. code-block:: python
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df = pd.read_csv('https://example.com/data.csv')
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df = pd.read_csv("https://example.com/data.csv")
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**Save/download**
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.. code-block:: python
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df.to_csv('/content/drive/MyDrive/output.csv', index=False)
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files.download('output.csv')
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df.to_csv("/content/drive/MyDrive/output.csv", index=False)
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files.download("output.csv")
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Files in ``/content/`` are temporary, so prefer saving to Google Drive if you need persistence.
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For more details on file handling in Colab, see the
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`official Colab IO notebook <https://colab.research.google.com/notebooks/io.ipynb>`_.
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.. note::
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For examples that use the ``StringIO`` class, make sure you import it
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with ``from io import StringIO`` for Python 3.

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