情节：如何使用分组依据创建条形图？

我在处理您的样本数据集时遇到麻烦。PclassSurvived.Pclass并PclassSurvived.CategorySize没有定义，它不是100％清楚，我要在这里完成的任务。但是从您的解释和数据集的结构来看，这似乎可以帮助您：

情节1：

代码1：

# imports
from plotly.subplots import make_subplots
import plotly.figure_factory as ff
import plotly.graph_objs as go
import pandas as pd
import numpy as np

data = dict(Pclass=[1,1,2,2,3,3],
            Survived = [0,1,0,1,0,1],
            CategorySize = [80,136,97,87,372,119] )
df=pd.DataFrame(data)

s0=df.query('Survived==0')
s1=df.query('Survived==1')

#layout = go.Layout(title= 'Pclass-Survived', xaxis = dict(title = 'Pclass'), yaxis = dict(title = 'CategorySize'),barmode='group' )
fig = go.Figure()

data=data['Pclass']

fig.add_trace(go.Bar(x=s0['Pclass'], y = s0['CategorySize'],
                    name='dead'
                    )
             )

fig.add_trace(go.Bar(x=s1['Pclass'], y = s1['CategorySize'],
                    name='alive'
                    )
             )

fig.update_layout(barmode='group')
fig.show()

编辑：您可以使用以下plotly.offline模块生成相同的图：

代码2：

# Import the necessaries libraries
import plotly.offline as pyo
import plotly.graph_objs as go
import pandas as pd

# Set notebook mode to work in offline
pyo.init_notebook_mode()

# data
data = dict(Pclass=[1,1,2,2,3,3],
            Survived = [0,1,0,1,0,1],
            CategorySize = [80,136,97,87,372,119] )
df=pd.DataFrame(data)

# 
s0=df.query('Survived==0')
s1=df.query('Survived==1')

fig = go.Figure()

data=data['Pclass']

fig.add_trace(go.Bar(x=s0['Pclass'], y = s0['CategorySize'],
                    name='dead'
                    )
             )

fig.add_trace(go.Bar(x=s1['Pclass'], y = s1['CategorySize'],
                    name='alive'
                    )
             )

pyo.iplot(fig, filename = 'your-library')

堆叠杆的替代方法：

情节2：

代码3：

# imports
from plotly.subplots import make_subplots
import plotly.figure_factory as ff
import plotly.graph_objs as go
import pandas as pd
import numpy as np

data = dict(Pclass=[1,1,2,2,3,3],
            Survived = [0,1,0,1,0,1],
            CategorySize = [80,136,97,87,372,119] )
df=pd.DataFrame(data)

s0=df.query('Survived==0')
s1=df.query('Survived==1')

#layout = go.Layout(title= 'Pclass-Survived', xaxis = dict(title = 'Pclass'), yaxis = dict(title = 'CategorySize'),barmode='group' )
fig = go.Figure()

data=data['Pclass']

fig.add_trace(go.Bar(x=s0['Pclass'], y = s0['CategorySize'],
                    name='dead'
                    )
             )

fig.add_trace(go.Bar(x=s1['Pclass'], y = s1['CategorySize'],
                    name='alive'
                    )
             )

df_tot = df.groupby('Pclass').sum()

annot1 = [dict(
            x=xi,
            y=yi,
            text=str(yi),
            xanchor='auto',
            yanchor='bottom',
            showarrow=False,
        ) for xi, yi in zip(df_tot.index, df_tot['CategorySize'])]

fig.update_layout(barmode='stack', annotations=annot1)
fig.show()