Log Service - IPython and Jupyter Extensions Supported
Target customers: users who need to use Pandas, Python, IPython, and Jupyter to perform interactive analysis and visualization tasks on large amounts of data stored in Log Service. Users who need to perform Python ETL operations. Features released: 1. You can configure visualization settings based on Ipython or NoteBook. 2. You can use Python magic methods to directly run query and statistics tasks on large amounts of data stored in Log Service. You can specify a time range to run these tasks. 3. You can use magic methods to pull specified data from large amounts of data at the same time (index-independent). 4. You can integrate Pandas DataFrame operations with Log Service. 5. Returned DataFrames are better visualized. 6. You can export data stored in Log Service to Excel files.