Dropdown menu with Multiple Months

📊 Plotly Python
1

Hello everyone,
Intro
I have an array of data frames that I would like to plot individually, but with with the ability to switch from one plot to another. I work with data that is separated by months. I got a large dataframe and created an arrays of data frames that where separated by months. In general I usually have 20 months, and would get complicated if done manually.

My question is I could use a replace this with a for loop?
Traditional Code:

trace1 = Scatter(
    x=month1.Date, y=month1,
    line=Line(
        color='#FFD700',
        width=3
    ),
    name='Start_Date to End_Date'
)

trace2 = Scatter(
    x=month2.Date, y=month2,
    line=Line(
        color='#C0C0C0',
        width=3
    ),
    name='Start_Date to End_Date'
)

trace3 = Scatter(
    x=month3.Date, y=month3,
    line=Line(
        color='#BA8651',
        width=3
    ),
    name='Start_Date to End_Date'
)

trace4 = Scatter(
    x=month4.Date, y=month4,
    line=Line(
        color='#000000',
        width=3
    ),
    name='Start_Date to End_Date'
)

data = Data([trace1, trace2, trace3, trace4])
layout = Layout(
    title='Power Data Interval',
    updatemenus=list([
        dict(
            x=-0.05,
            y=1,
            yanchor='top',
            buttons=list([
                dict(
                    args=['visible', [True, True, True, True]],
                    label='All',
                    method='restyle'
                ),
                dict(
                    args=['visible', [True, False, False, False]],
                    label='Gold',
                    method='restyle'
                ),
                dict(
                    args=['visible', [False, True, False, False]],
                    label='Silver',
                    method='restyle'
                ),
                dict(
                    args=['visible', [False, False, True, False]],
                    label='Bronze',
                    method='restyle'
                ),
                dict(
                    args=['visible', [False, False, False, True]],
                    label='Total',
                    method='restyle'
                )
            ]),
        )
    ]),
)
fig = Figure(data=data, layout=layout)
py.iplot(fig)

With this for loop code:

month = {}  # array of dataframes by months
monthLength = len(month)
trace = {}
for i in range(0, monthLength, 1):
    trace[i] = Scatter(
        x=month[i].Date, y=month[i]['value'],
        line=Line(
            color='#FFD700',
            width=3
        ),
        name='Start_Date to End_Date') # The name of lot is begin and end date of that month Note: the name part is psuedu code but irrelevant


data = Data(trace)
layout = Layout(
    title='Power Data Interval',
    updatemenus=list([  # Not sure how to do update menus with a for loop I only need the race appear when it is clicked on.
        dict(
            x=-0.05,
            y=1,
            yanchor='top',
            buttons=list([
                dict(
                    args=['visible', [True, True, True, True]],
                    label='All',
                    method='restyle'
                ),
                dict(
                    args=['visible', [True, False, False, False]],
                    label='month1',
                    method='restyle'
                ),
                dict(
                    args=['visible', [False, True, False, False]],
                    label='month2',
                    method='restyle'
                ),
                dict(
                    args=['visible', [False, False, True, False]],
                    label='month3',
                    method='restyle'
                ),
                dict(
                    args=['month4', [False, False, False, True]],
                    label='Total',
                    method='restyle'
                )
            ]),
        )
    ]),
)
fig = Figure(data=data, layout=layout)
py.iplot(fig)

I want to automate the drop down list. I would like to know if this the correct approach, or if somebody knows another method.
Thank you for the help