IPython/Jupyter notebooks are one of the leading free platforms for data analysis, with many advantages, notably the interactive web-based interface and a large ecosystem of readily available packages for data analysis and visualization. Moreover IPython/Jupyter notebooks are a very handy format for sharing code and data as you will see in the examples.
See also this blog post with examples on how to use Jupyter for querying Apache Impala.
It is of interest to integrate many data sources into Jupyter notebooks to make the platform versatile and to fulfill many different use cases. In this short post you can find examples of how to query data from Oracle using Jupyter notebooks and simple integration with pandas and matplotlib.
|Oracle_IPython_sqlplus||Examples of how to use sqlplus inside Jupyter notebooks. It is based on the use of %%bash cell magic and here documents to wrap up sqlplus inside Jupyter cells.|
|Oracle_IPython_cx_Oracle_pandas||Examples of how to query Oracle from Python using cx_Oracle and how to integrate with pandas and visualization with matplotlib.|
|Oracle_IPython_SQL_magic||Examples of how to query Oracle using %sql line magic (or %%sql cell magic) and of the integration with cx_Oracle and pandas.|
Dependencies and pointers to build a test environment: