[Python] plotly histogram with filtering toolbar - python

I'm trying to generate a plotly histogram that can be filtered by values with a df column. Below, in dataset, I want to be able to filter the values in item to show the distribution of values for each unique value.

However, all I am able to display is one single value. I can't change values to show the results of differing items.

dataset = pd.DataFrame(
{'item': ['A', 'A', 'B', 'C', 'D', 'A', 'A', 'B', 'C', 'D', 'A', 'A', 'B', 'C', 'D'],
'value': [27, 33, 3, 26, 8, 27, 3, 13, 16, 2, 27, 17, 12, 6, 28],
}
)

continuous_vars = ["item"]

fig = go.Figure()

fig.add_trace(
go.Histogram(x = dataset.item,
xbins=go.histogram.XBins(size=5), # Change the bin size
marker=go.histogram.Marker(color="orange"), # Change the color
)
)

buttons = []

for col in continuous_vars:
buttons.append(dict(method='restyle',
label=col,
visible=True,
args=[{"x":[dataset[col]],
"type":'histogram'}, [0]],
)
)

updatemenu = []
your_menu = dict()
updatemenu.append(your_menu)

updatemenu[0]['buttons'] = buttons
updatemenu[0]['direction'] = 'down'
updatemenu[0]['showactive'] = True

fig.update_layout(showlegend=False, updatemenus=updatemenu)
fig.show()

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