This project aims to generate some util notebooks to get data exploration.
It's based on nbconvert and simply offer you a easy way to analise a feature value (or set of them) of a dataset.
In order to install the utility just use pip:
pip install jupyXplorer
We provide you a docker image to get started quickly, take a look at hypnosapos/jupyxplorer at dockerhub and select the best one fit your needs.
Before notebook generation take a look at our config file example (tests/e2e/sample_config.yaml).
jupyxplorer -c config.yaml -o .output
All notebooks will be ready in directory ".output" of the example above.
Once notebooks are generated we can use them in your jupyter to show results of data analysis.
As we said above, you may use a docker container instead:
docker run -it -v </path/my_config.yaml>:/tmp/my_config.yaml </path/output>:/tmp/output hypnosapos/jupyxplorer:latest jupyxplorer -c /tmp/my_config.yaml -o /tmp/output
If you want to use some required files to execute notebooks before generation (-e or --execute argument), provide the value of argument "input-dir" (--input-dir, or the short form -i). Here you have an example:
jupyxplorer -i .input -c config.yaml -o .output -e
The resources under that directory would be particular requirement files for python and local dataset files.
The development lifecycle is managed by a Makefile and CircleCI, where all steps are executed through docker containers.
Type make help
to see all available commands.