python - Plotly-Dash：想要两个堆叠的条形图从单个 df 列并排

Question

我正在尝试并排放置两个堆叠的条形图，但无法弄清楚。

这是一个例子df：

Field       Issue

Police      Budget cuts
Research    Budget cuts
Police      Time consuming
Banking     Lack of oversight
Healthcare  Lack of support
Research    Bureaucracy
Healthcare  Bureaucracy
Banking     Mistrust

我想要的是一个堆积条形图，首先是字段。它的高度为 8，由 2 名警察、2 次研究等细分。然后我想要第一个图表旁边的问题堆积条形图。第二个的高度为 8，并由 2 倍预算削减、1 倍耗时、1 倍缺乏监督等因素叠加。

我努力了：

获取所有字段的堆积条形图：

trace1 = go.Bar(
    x = df.Field.unique(),
    y = df.Field.value_counts(),
    name='Total Amount of roles'
)

获得预算削减的堆积条形图（然后复制其他问题）：

trace2 = go.Bar(
    x = df.Field.unique(),
    y = df[df['Issue'] == 'Budget cuts'].Field.value_counts(),
    name='Budget cuts'
)

data = [trace1, trace2]
layout = go.Layout(barmode='stack')

fig = go.Figure(data=data, layout=layout)
py.plot(fig, filename='test.html')

但是上面的代码将两个图叠加到一个上。我想要堆栈的迹线 1 和堆栈的迹线 2。我也希望将其集成到 Dash 中，而不是单独进行，但老实说，这将是次要的。将不胜感激任何帮助！

标签： pythonpython-3.xplotly

Answer 1

编辑 - 在评论中简短对话后，这是我的最新建议：

---

这是一个可能的解决方案，其中每列（字段或问题）堆叠的每个类别的每次出现计数：

阴谋：

代码：

如您所见，它不是很灵活，因为您必须go.Bar为每个类别（银行、警察等）添加一个对象。但如果上面的情节是你要找的，我也会整理出那部分。

# import
import pandas as pd
import numpy as np
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)

#%qtconsole

# sample data
Field = ['Police', 'Research', 'Police', 'Banking', 'Healthcare', 'Research', 'Healthcare', 'Banking']
Issue = ['Budget cuts', 'Budget cuts', 'Time consuming', 'Lack of oversight', 'Lack of support', 'Bureaucracy', 'Bureaucracy', 'Mistrust']

# Put the lists in a pandas dataframe for
# easy grouping and indexing
df = pd.DataFrame([Field, Issue]).T
df.columns = ['Field', 'Issue']
grField = df.groupby('Field').count()
grIssue = df.groupby('Issue').count()
dfgr = pd.concat([grField, grIssue], axis = 1, sort = False)
dfgr = dfgr.T

# Make one go.Bar() object for each category
# for corresponing Field / Issue
trace1 = go.Bar(
    x = ['Issue'],
    #y = [dfgr['Field']],
    y = [dfgr['Banking'].loc['Issue']],
    name='Banking')

trace2 = go.Bar(
    x = ['Issue'],
    #y = [dfgr['Field']],
    y = [dfgr['Healthcare'].loc['Issue']],
    name='Healthcare')

trace3 = go.Bar(
    x = ['Issue'],
    #y = [dfgr['Field']],
    y = [dfgr['Police'].loc['Issue']],
    name='Police')

trace4 = go.Bar(
    x = ['Issue'],
    #y = [dfgr['Field']],
    y = [dfgr['Research'].loc['Issue']],
    name='Research')

trace5 = go.Bar(
    x = ['Field'],
    #y = [dfgr['Field']],
    y = [dfgr['Budget cuts'].loc['Field']],
    name='Budget cuts')

trace6 = go.Bar(
    x = ['Field'],
    #y = [dfgr['Field']],
    y = [dfgr['Bureaucracy'].loc['Field']],
    name='Bureaucracy')

trace7 = go.Bar(
    x = ['Field'],
    #y = [dfgr['Field']],
    y = [dfgr['Lack of oversight'].loc['Field']],
    name='Lack of oversight')

trace7 = go.Bar(
    x = ['Field'],
    #y = [dfgr['Field']],
    y = [dfgr['Lack of oversight'].loc['Field']],
    name='Lack of oversight')

trace8 = go.Bar(
    x = ['Field'],
    #y = [dfgr['Field']],
    y = [dfgr['Lack of support'].loc['Field']],
    name='Lack of support')

trace9 = go.Bar(
    x = ['Field'],
    #y = [dfgr['Field']],
    y = [dfgr['Mistrust'].loc['Field']],
    name='Mistrust')

trace10 = go.Bar(
    x = ['Field'],
    #y = [dfgr['Field']],
    y = [dfgr['Time consuming'].loc['Field']],
    name='Time consuming')

# gather data and set up layout
#data = [trace1, trace2, trace3, trace4, trace5, trace6, trace7, trace8, trace9, trace10]
data = [trace10, trace9, trace8, trace7, trace6, trace5, trace4, trace3, trace2, trace1]
layout = go.Layout(barmode='stack', title = 'Stacked bar chart from single column')

# Build figure
fig = go.Figure(data=data, layout=layout)

# PLot figure
iplot(fig, filename='test.html')