Data transformations for data extracted from Qualtrics surveys for SQL / Tableau Ingestion. Three survey are converted to Pandas dataframes, transofrmed wide to long, and merged to a single dataframe.
These datasets are stored in a number of csvs on our team's Google Drive. This repo contains scripts to join these datasets as well as analyses performed with the data.
First, you'll need Python 3.7. We recommend using pyenv to get this (as well as other versions of Python).
Then you'll need Jupyter Notebook. You can find directions on how to get that here. They recommend downloading Anaconda to get it, but we suggest using pip if you're already using pyenv to manage your python versions.
Then you'll want to clone this repo and cd in to it:
git clone https://github.com/GSA/INFORM-Pilot.git
cd INFORM-PilotWe use pipenv for a virtual environment. You can find instructions on installing that here.
Once you've got pipenv installed, you can start up the virtual environment using:
pipenv installNext, activate the Pipenv shell:
pipenv shellThis will spawn a new shell subprocess, which can be deactivated by using exit.
One of the required packages you just installed is ipykernel. We use this to create a kernel that uses our virtual enivronment for the Jupyter Notebook:
ipython kernel install --user --name=wb2At this point, you can start jupyter with jupyter notebook. Open this notebook and select the kernel (wb2) that you just created.
The data files are too large to keep in the repository, so we keep them in our team's google drive.
This is the survey data collectedin Qualtrics, which included study participants. Download the INFORM data here. There's a csv for each survey. Once you've downloaded those files, move them into the data/INFORM-Pilot directory.
This project is licensed under the Creative Commons Zero v1.0 Universal License - see the LICENSE.md file for details