This repository shows a Django data analytics stack
- Inject data from csv: see how to inject some data into the database from csv files
- Batch insert data from csv: see how to inject large amounts of data into the database from csv files with a progress bar
- Query data: see how to query the database and get a dataframe
- Compose charts: see how to prototype charts in notebooks from dataframes
- Export and serve charts: see how to create a charts generation pipeline and serve the charts
Clone the repository and install:
make install
This will create a virtualenv locally, create an Sqlite db and run the migrations
Open the notebooks app in a django env:
make notebooks
All the notebooks are located in the notebooks
directory. Note for version control: the
notebooks are paired to .py files that are used for version control. The .ipynb files will
not be pushed to the git repository. See the git workflow section below
To open a notebook from a Python file right click on it and select "Open as a notebook"
Create notebooks and pair them to .py files when you want to share it with git. To pair a notebook see the doc and use the Pair Notebook with percent script command. Once paired a notebook can be commited.
To open the command panel on Jupyterlab use the Ctrl-Shift-C command and type jup
To run the data pipeline and generate the charts:
make pipeline
To run the Django dev server:
make run