- Clone this repository to your machine from GITHUB to your local environment If you are using Anaconda, open the web interface and navigate to this new repo and open the notebook file, otherwise follow the steps below
- Navigate to this new repository through terminal in MacOs/Linux or command prompt in Windows
- Check to see you are in the correct location using 'ls' if you're on a Mac or Linux, if you are on windows use 'dir' and check to see if the output is the same as the files listed in this repository
- Create a virtual environment within your terminal, you will know this is successful if your terminal or command prompt displays "venv" in parenthesis
- Install the requirements using the command "pip install -r requirements.txt"
- This project was created and executed through the anaconda interpreter, so there will be a large list of packages in the requirements.txt
- Once all required packages are installed, open the .ipynb file
- Read my data into my Jupyter notebook and create a dataframe element to examine my data and its various elements like column titles, null values, data types, and my overall number of rows and columns.
- Clean my data by renaming several columns for visualization later, drop unneeded columns, drop unneeded responses and null values from those columns, create a new column based on specific criteria, and export all these changes to a new spreadsheet.
- Load my new spreadsheet into the notebook and visualize the data using both pie and bar charts.
I believe that a college or university's top goal is to prepare students for their eventual place in their field of choice. Educators must adapt to new and changing job requirements and the knowledge needed to make an impact in the field. For cutting edge fields like medicine and STEM, this dedication to the implementation of emerging technology is paramount. The global pandemic of Covid-19 requires these cutting edge fields to prioritize the training of nurses, biologists, and medical field workers to new methods of stopping transmission and curing patients. My main questions are to see if students of various college majors have a difference in perceived importance of Covid-19 and its preventative measures and to see if there are any significant difference variances in their data. Would a history major have a higher perceived importance of Covid-19 vs a nursing major? Does the biological sex or college grade (Freshman-Graduate) of the student have any impact in their perceived importance of Covid-19?
This project collected anonymous data from students from Union College of various grade levels, biological sex, and college majors and tested to see if there was any relation to the students college major and their perceived importance of Covid-19. Besides the basic demographic questions, most questions asked to the students are based off of the Likert scale that spans from "Not at all important, Slightly important , Somewhat important , Very important and Extremely important" and a few additional questions that ask True/False, Yes/No responses. The question inventory is a custom inventory created by the study's author as there are very few related question inventories at the time of this study's creation.