Use plotly to plot multiple pandas column with a dropdown menu to select column

I have a pandas dataframe for which I am trying to a plot bar graph using Plotly with a dropdown menu to select by the stock name column, referring this answer.

But I am unsure how do I add multiple columns to the updatemenus as the names of the columns could vary.

import plotly.graph_objects as go
# plotly setup
fig = go.Figure()

# Add traces, starting from First Column. Each column is a stock data.
for mycolumn in df.columns[1:]:
    fig.add_traces( go.Scatter(x=list(df.Quarters), y=list(df[mycolumn])) )

updatemenus = None

for mycolumn in df.columns[1:]:
    # construct menus
    updatemenus = [{'buttons': 
                    [{'method': 'update',
                      'label' : column, # what?
                      'args'  : [{'y': [values_1, values_1b]},] # what?
                     }
                    'direction': 'down',
                    'showactive': True,}
                  ]

# update layout with buttons, and show the figure
fig.update_layout(updatemenus=updatemenus)
fig.show()

The dataframe for ref:

Quarters	526433	AARTIIND	DEEPAKNTR	GREENPANEL	METROBRAND	MOLDTECH	MUFTI	MUTHOOTFIN	YASHO	ZENTEC
Mar-21				4.6	1.69
Jun-21	2.99	4.55	22.19	2.43		1.16		24.37	10.01	-0.14
Sep-21	3.77	4.14	18.65	5.47	1.89	1.3		24.97	12.44	0
Dec-21	4.3	20.01	17.78	5.14	3.69	0.59		25.91	12.71	-0.02
Mar-22	1.54	5.34	19.59	6.57	2.49	1.67		24.84	11.69	0.42
Jun-22	3.35	3.75	17.2	6.33	3.8	1.1		20.41	16.99	0.94
Sep-22	2.84	3.42	12.79	5.91	2.72	2.43	80.9	22.22	19.61	0.71
Dec-22	2.25	3.77	15.33	3.06	4.22	3.26	60.25	23.11	9.18	1.19
Mar-23	0.25	4.11	17.15	5.62	2.44	3.58	67.43	24.25	13.76	2.54
Jun-23	0.36	1.93	10.99	3.04	3.91	2.21	1.33	25.46	12.97	5.6
Sep-23	-1.59	2.51	15.04	3.34	2.92	2.86	4.35	26.39	10.23	1.82
Dec-23	-0.19	3.42	14.81	2.82	3.52	2.47	2.42	27.49	11.88	3.64
Mar-24	-2.59	3.64	18.61	2.43	6.05	2.26	1.1	28.37	15.74	4.16
Jun-24	2.83	3.78	14.85		3.4	1.81	1.51	28.99	-2.16	9.14

Solution

As mentioned in the linked post:

'y' = [values_1] where values_1 is a list in itself.

So, we need 'y': [df[col]] for each col in df.iloc[:, 1:]. For the label value use col itself. Also make sure only to add a trace for your first column, as this will give us the result for the first selection.

import plotly.graph_objects as go

fig = go.Figure()

# add trace only for first stock
x = df['Quarters']
y = df['526433']
fig.add_traces(go.Scatter(x=x, y=y))

# create `list` with a `dict` for each column
buttons = [{'method': 'update', 'label': col, 'args': [{'y': [df[col]]}]} 
           for col in df.iloc[:, 1:]]

# add menus
updatemenus = [{'buttons': buttons,
                'direction': 'down',
                'showactive': True,}]

# update layout with buttons, and show the figure
fig.update_layout(updatemenus=updatemenus)
fig.show()

Output:

Data used

import pandas as pd
import numpy as np

data = {'Quarters': {0: 'Mar-21', 1: 'Jun-21', 2: 'Sep-21', 3: 'Dec-21', 4: 'Mar-22', 
                     5: 'Jun-22', 6: 'Sep-22', 7: 'Dec-22', 8: 'Mar-23', 9: 'Jun-23', 
                     10: 'Sep-23', 11: 'Dec-23', 12: 'Mar-24', 13: 'Jun-24'}, 
        '526433': {0: np.nan, 1: 2.99, 2: 3.77, 3: 4.3, 4: 1.54, 5: 3.35, 6: 2.84, 
                   7: 2.25, 8: 0.25, 9: 0.36, 10: -1.59, 11: -0.19, 12: -2.59, 13: 2.83}, 
        'AARTIIND': {0: np.nan, 1: 4.55, 2: 4.14, 3: 20.01, 4: 5.34, 5: 3.75, 6: 3.42,
                     7: 3.77, 8: 4.11, 9: 1.93, 10: 2.51, 11: 3.42, 12: 3.64, 13: 3.78}, 
        'METROBRAND': {0: 1.69, 1: np.nan, 2: 1.89, 3: 3.69, 4: 2.49, 5: 3.8, 6: 2.72, 
                       7: 4.22, 8: 2.44, 9: 3.91, 10: 2.92, 11: 3.52, 12: 6.05, 13: 3.4}
       }
df = pd.DataFrame(data)