Piechart dropdown in plotly Python

Question

I have large df like this (those data is just an example):

|Category|Sign|
|-       |-|
|One     |-|
|Two     |+|
|One     |-|
|Two     |-|
|One     |+|

I have to do pie charts with plotly - for each category I have to count '+' and '-' (it's easy and I done it) and then insert a dropdown to choose which one of these (in this case 2) pie plots will be shown. I have something like this:

cat = set(data['Category'])
for c in cat:
    t = data[data['Category'] == c]
    c = t['Sign'].value_counts()
    fig = px.pie(t, values = c.values, names = c.index)
    fig.show()

And now I have no idea how to do this dropdown - could someone help me, please? :) or just guide me how to do it?

Answer 1

• core concept: all traces need to be part of same figure to control with updatemenus
• have generated data as it's simpler to test concept (more categories)
• have created figures for each category in what is the same way you did. However it's more convenient to have them in a dict
• integrate all the figures in the dict into a consolidate figure
• finally build updatemenus to achieve your requirement

import numpy as np
import plotly.express as px

# generate data matching definition in question
data = pd.DataFrame(
    {
        "Category": np.random.choice(["One", "Two", "Three"], 100),
        "Sign": np.random.choice(list("+-"), 100),
    }
)

# simplify - use value_counts() on whole dataframe
df_vc = data.value_counts()
# create a figure for each category
figs = {
    c: px.pie(df_vc.loc[c].reset_index(), values=0, names="Sign").update_traces(
        name=c, visible=False
    )
    for c in df_vc.index.get_level_values("Category").unique()
}

# integrate figures per category into one figure
defaultcat = df_vc.index.get_level_values("Category").unique()[0]
fig = figs[defaultcat].update_traces(visible=True)
for k in figs.keys():
    if k != defaultcat:
        fig.add_traces(figs[k].data)

# finally build dropdown menu
fig.update_layout(
    updatemenus=[
        {
            "buttons": [
                {
                    "label": k,
                    "method": "update",
                    # list comprehension for which traces are visible
                    "args": [{"visible": [kk == k for kk in figs.keys()]}],
                }
                for k in figs.keys()
            ]
        }
    ]
)

supplementary update

• include Categrory combinations in drop down
• extend building of dict to include combinations

import itertools
figs = {
    **{
        c: px.pie(df_vc.loc[c].reset_index(), values=0, names="Sign").update_traces(
            name=c, visible=False
        )
        for c in df_vc.index.get_level_values("Category").unique()
    },
    **{
        f"{a}-{b}": px.pie(
            df_vc.loc[[a, b]].reset_index(), values=0, names="Sign"
        ).update_traces(name=f"{a}-{b}", visible=False)
        for a, b in itertools.combinations(
            df_vc.index.get_level_values("Category").unique(), 2
        )
    },
}