Visualization ideas for discussion during meeting

[mikelynch416]

Here is an example visualization I came up with to analyze the responses to the survey questions "If you have a mental health issue, do you feel that it interferes with your work when being treated effectively?" and "If you have a mental health issue, do you feel that it interferes with your work when NOT being treated effectively?"

The idea is that we would pass some global data from our dash app to the function which generates these plots and that when a user makes different selections on the dropdown widgets/radio buttons, the global data gets updated and so does the plot.

def plot_work_interfere_bars(global_data): 
    # my understanding is the global_data parameter will not be needed in the dash app
    plot_data = global_data.query('work_interfere_treated != "Not applicable to me" & work_interfere_not_treated != "Not applicable to me"')
    
    treated = alt.Chart(plot_data, title='When Treated').mark_bar(
    ).encode(x=alt.X('work_interfere_treated', sort=['Never', 'Rarely', 'Sometimes', 'Often'], axis=alt.Axis(title='')),
             y=alt.Y('count()', axis=alt.Axis(title='Number of Responses'))
    ).properties(height=200, width=200)
    
    untreated = alt.Chart(plot_data, title='When Untreated').mark_bar(
    ).encode(x=alt.X('work_interfere_not_treated', sort=['Never', 'Rarely', 'Sometimes', 'Often'], axis=alt.Axis(title='')), 
             y=alt.Y('count()', axis=alt.Axis(title='Number of Responses'))
    ).properties(height=200, width=200)
    
    viz = alt.hconcat(treated, untreated, title='Does your mental health issue interfere with your work?'
    ).configure_title(fontSize=20, font='Courier', anchor='middle', color='gray')
    return viz#.to_html()

[d-sel]

That's great! I like the plot, @mikelynch416!

I came up with a plot that specifies responses by gender. The idea is that the user could select between different questions and see if there are differences between responses based on gender.

I did some 'data clean up' in the processing file because there were many different responses, which I will merge with a PR when we finalize the plots we would like to use.

or an alternative: