Add Google Colab IO instructions to pandas IO documentation

doc/user_guide/io.rst

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+Loading Data into Pandas in Google Colab
+Mount Google Drive to Access Files:
+This connects your Google Drive storage to the Colab environment so files can be read as if local.
+
+python
+from google.colab import drive
+drive.mount('/content/drive')
+After executing, follow the prompt to authorize access. Your Drive files will appear under /content/drive/.
+
+Locate Your File Path in Drive:
+Use the file explorer pane in Colab to navigate to your file, right-click it, and select "Copy path." The path will be something like /content/drive/MyDrive/path_to_file.csv.
+
+Load the File into a Pandas DataFrame:
+Using pandas, read the data with:
+
+python
+import pandas as pd
+df = pd.read_csv('/content/drive/MyDrive/path_to_file.csv')
+df.head()
+This works similarly for Excel files (pd.read_excel) or JSON files (pd.read_json).
+
+Alternative: Upload Files Directly from Local to Colab:
+If you don't want to use Drive, upload files interactively:
+
+python
+from google.colab import files
+uploaded = files.upload()
+import io
+df = pd.read_csv(io.BytesIO(uploaded['filename.csv']))
+Replace 'filename.csv' with the uploaded file’s name.
+
+Suggested Addition to Pandas Documentation for Google Colab
+A dedicated section on the IO page explaining this process would be useful for users running pandas in Colab, covering Drive mounting, direct uploading, and basic file reading commands.