Hello !
Using the two links here and here, I managed to successfully create functioning drop down menus that are responsive! It was a lot of fun experimenting with ipywidgets and Plotly.
However, I’m having a hard time figuring out how to plot mathematical functions. The graph selected is currently a scatter plot, but ideally, I’d like to have a bar plot (which I know is go.Bar) that shows the different salaries (as it does now) and one other bar that is a different color that represents the mean for that Job Title for that Borough.
Additionally, right after the code runs, I get an empty figure that doesn’t have any of the axis that I created, and doesn’t show any graphical information. This changes once the user selects a criteria, but from my understanding, I made a default selection. Did I make a mistake somewhere?
Here is an image of what I get after running the code:
The code that I used is shown below:
I imported the dataset (linked below) and saved it as pay.
pay['Base Salary'] = pay['Base Salary'].replace(('\,', '\.(.*)'), '', regex = True).astype(np.int64)
pay = pay.where(pay['Pay Basis'] == 'per Annum').dropna(how = 'all', axis = 0)
use_date = widgets.Dropdown(
options = list(pay['Fiscal Year'].unique()),
description = 'Year : ',
value = 2016.0
)
job_list = list(pay['Title Description'].unique())
status_list = list(pay['Leave Status as of June 30'].unique())
container = widgets.HBox(childern = [use_date])
status = widgets.Dropdown(
options = status_list,
value = 'CEASED',
description = 'Status : '
)
title = widgets.Dropdown(
options = job_list,
value = '* ATTENDING DENTIST',
description = 'Job Title: ',
)
filter_list = [i and j and k for i, j, k in zip(pay['Fiscal Year'] == 2016.0,
pay['Leave Status as of June 30'] == 'CEASED',
pay['Title Description'] == '*ATTENDING DENTIST')]
trace1 = go.Scatter(x = pay[filter_list]['Work Location Borough'], y = pay[filter_list]['Base Salary'],
mode = 'markers', marker_size = 10)
g = go.FigureWidget(data = [trace1], layout = go.Layout(width = 750, height = 750, font_size = 12,
title = dict(text = 'NYC Payroll by Borough')))
def validate():
if title.value in pay['Title Description'].unique():
return True
else:
return False
def response(change):
if validate():
if use_date.value:
filter_list = [i and j and k for i, j, k in zip(pay['Fiscal Year'] == use_date.value,
pay['Leave Status as of June 30'] == status.value,
pay['Title Description'] == title.value)]
temp_df = pay[filter_list]
else:
filter_list = [i and j for i,j in zip(pay['Leave Status as of June 30'] == status.value,
pay['Title Description'] == title.value)]
temp_df = pay[filter_list]
with g.batch_update():
g.data[0].x = temp_df['Work Location Borough']
g.data[0].y = temp_df['Base Salary']
g.layout.barmode = 'overlay'
g.layout.xaxis.title = 'Location'
g.layout.yaxis.title = 'Salary'
title.observe(response, names = "value")
status.observe(response, names = "value")
use_date.observe(response, names = "value")
container2 = widgets.HBox([title, status])
widgets.VBox([container, container2, g])
The dataset comes from here.
Any assistance with this would be greatly appreciated.
Thank you!!