Plotly如何通过多下拉菜单过滤DataFrame并绘制多分组柱状图

• 参考Stack Overflow相关问题进行开发，使用数据集为Tableau公开的Sample Superstore销售数据集
• 我是Plotly新手，当前需求为在原问题基础上新增过滤条件：通过年份和商品类别两个维度过滤数据，绘制各区域每季度的总销售额柱状图
• 目前已成功复现原问题中的折线图效果，但无法实现预期的柱状图效果。需求要求一年4个季度、共4个区域，因此任意过滤状态下需至少展示16根柱子

import plotly.graph_objs as go
import pandas as pd
import numpy as np

file = pd.read_excel(r"Sample - Superstore.xlsx")
sales = file[['Sales','Region', 'Order Date','Category', 'State']]
sales["Quarters"] = sales['Order Date'].apply(lambda x: x.quarter)
sales["Years"] = sales['Order Date'].apply(lambda x: x.year)
df = sales.groupby(['Years','Quarters', 'Region', 'Category'], as_index = False).sum()
df_input = df.copy()

years = df['Years'].unique().tolist()
categories = df['Category'].unique().tolist()
regions = df['Region'].unique().tolist()
quarters = df['Quarters'].unique().tolist()

dfs = {}
for year in years:
    dfs[year]=pd.pivot_table(df[df['Years']==year],
                                    values='Sales',
                                    index=['Quarters','Region'],
                                    columns=['Category'],
                                    aggfunc=np.sum)

# find row and column unions
common_cols = []
common_rows = []
for df in dfs.keys():
    common_cols = sorted(list(set().union(common_cols,list(dfs[df]))))
    common_rows = sorted(list(set().union(common_rows,list(dfs[df].index))))
    
df_common = pd.DataFrame(np.nan, index=common_rows, columns=common_cols)

# reshape each dfs[df] into common dimensions
dfc={}
for df_item in dfs:
    #print(dfs[unshaped])
    df1 = dfs[df_item].copy()
    s=df_common.combine_first(df1)
    df_reshaped = df1.reindex_like(s)
    dfc[df_item]=df_reshaped

# plotly start 
fig = go.Figure()

# for year in all_years:
#     df2 = group_sales.loc[group_sales["Years"] == year]
#     all_quarters =list(sorted(set(df2["Quarters"].astype(str))))
#     all_regions =list(sorted(set(df2["Region"].astype(str))))
    
#     fig.add_trace(go.Bar(x= all_quarters, y=df2.loc[df2["Region"] == all_regions[0]]["Sales"], name=all_regions[0],marker_color='blue',  visible=(year== default_year)))
#     fig.add_trace(go.Bar(x= all_quarters, y= df2.loc[df2["Region"] == all_regions[1]]["Sales"], name=all_regions[1], marker_color='lightblue', visible=( year == default_year)))
#     fig.add_trace(go.Bar(x= all_quarters, y= df2.loc[df2["Region"] == all_regions[2]]["Sales"],name= all_regions[2],marker_color='grey', visible=(year== default_year)))
#     fig.add_trace(go.Bar(x= all_quarters, y= df2.loc[df2["Region"] == all_regions[3]]["Sales"],name=all_regions[3], marker_color='red', visible=(year== default_year)))
#     year_plot_names.extend([year]*4)

print(common_cols)

for col in common_cols:
#     fig.add_trace(go.Bar(x= all_quarters, y=df2.loc[df2["Region"] == all_regions[0]]["Sales"], name=all_regions[0],marker_color='blue',  visible=(year== default_year)))
    fig.add_trace(go.Bar(x= quarters, name= regions[0],marker_color='blue',  visible= True))
    fig.add_trace(go.Bar(x= quarters, name= regions[1],marker_color='lightblue',  visible= True))
    fig.add_trace(go.Bar(x= quarters, name= regions[2],marker_color='grey',  visible= True))
    fig.add_trace(go.Bar(x= quarters, name= regions[3],marker_color='red',  visible= True))
    
#     fig.add_trace(go.Bar(x= regions,marker_color='blue',  visible= True))

#     fig.add_trace(go.Scatter(x=regions,
#                              visible=True,
#                              marker=dict(size=12, line=dict(width=2)),
#                              marker_symbol = 'diamond',name=col
#                   )
#              )

fig.show()
# menu setup    
updatemenu= []

# buttons for menu 1, names
buttons=[]

# create traces for each color: 
# build argVals for buttons and create buttons
for df in dfc.keys():
    argList = []
    
    for col in dfc[df]:
        temp = []
        j = 0

#         for i in range(0,4):
#             temp2 = []
#             for i in range(0,4):
#                 temp2.append(dfc[df][col].values[j])
#                 j+=1
#             temp.append(temp2)
#         argList.append(temp)
        print(dfc[df][col])
        argList.append(dfc[df][col].values)
    argVals = [ {'y':argList}]

    buttons.append(dict(method='update',
                        label=df,
                        visible=True,
                        args=argVals))
print(buttons)

# buttons for menu 2, colors
b2_labels = common_cols

# matrix to feed all visible arguments for all traces
# so that they can be shown or hidden by choice
b2_show = [list(b) for b in [e==1 for e in np.eye(len(b2_labels))]]
buttons2=[]
buttons2.append({'method': 'update',
                 'label': 'All',
                 'args': [{'visible': [True]*len(common_cols)}]})

# create buttons to show or hide
for i in range(0, len(b2_labels)):
    buttons2.append(dict(method='update',
                        label=b2_labels[i],
                        args=[{'visible':b2_show[i]}]
                        )
                   )

# add option for button two to hide all
buttons2.append(dict(method='update',
                        label='None',
                        args=[{'visible':[False]*len(common_cols)}]
                        )
                   )

# some adjustments to the updatemenus
updatemenu=[]
your_menu=dict()
updatemenu.append(your_menu)
your_menu2=dict()
updatemenu.append(your_menu2)
updatemenu[1]
updatemenu[0]['buttons']=buttons
updatemenu[0]['direction']='down'
updatemenu[0]['showactive']=True
updatemenu[1]['buttons']=buttons2
updatemenu[1]['y']=0.6

fig.update_layout(showlegend=False, updatemenus=updatemenu)
fig.update_layout(yaxis=dict(range=[0,df_input['Sales'].max()+0.4]))

# title
fig.update_layout(
    title=dict(
        text= "<i>Filtering with multiple dropdown buttons</i>",
        font={'size':18},
        y=0.9,
        x=0.5,
        xanchor= 'center',
        yanchor= 'top'))

# button annotations
fig.update_layout(
    annotations=[
        dict(text="<i>Year</i>", x=-0.4, xref="paper", y=1.1, yref="paper",
            align="left", showarrow=False, font = dict(size=16, color = 'steelblue')),
        dict(text="<i>Category</i>", x=-0.4, xref="paper", y=0.7, yref="paper",
            align="left", showarrow=False, font = dict(size=16, color = 'steelblue')

                             )
    ])

fig.show()

内容的提问来源于stack exchange，提问作者Andrew Tjen