如何用两个类别绘制条形图？

Question

我有这样的数据

import pandas as pd
df = pd.DataFrame(
dict(
    week=[1, 1, 2, 2, 3, 3] * 2,
    layout=["classic", "classic", "modern", "modern"] * 3,
    response=["conversion", "exit"] * 6,
    cnt=[26, 23, 45, 34, 55, 44, 53, 27, 28, 25, 30, 34],))

我需要像excel一样使用plotly获得这样的条形图：

我不能使用两个类别的主要问题。我的代码：

px.bar(
    data_frame=df,
    x='week',
    y='cnt',
    template='plotly_dark',
    color = 'layout'
)

结果：

但我无法像 excel 示例中那样显示有关“响应”的信息

Answer 1

在我看来，最灵活的方法是使用go.Figure()然后

fig.add_traces(go.Bar(x=dfp['week'], y = dfp['cnt'], name = v))

对于每个值, v,['conversion - classic', 'conversion - modern', 'exit - classic', 'exit - modern']像这样：

fig = go.Figure()
for v in df['value'].unique():
    dfp = df[df['value']==v]
    fig.add_traces(go.Bar(x=dfp['week'], y = dfp['cnt'], name = v))
fig.update_layout(barmode='stack', template='plotly_dark')
fig.show()

阴谋：

据我所知，这应该非常类似于您的 Excel 输出。

完整代码：

import pandas as pd
import plotly.graph_objects as go
import plotly.express as px

df = pd.DataFrame(
dict(
    week=[1, 1, 2, 2, 3, 3] * 2,
    layout=["classic", "classic", "modern", "modern"] * 3,
    response=["conversion", "exit"] * 6,
    cnt=[26, 23, 45, 34, 55, 44, 53, 27, 28, 25, 30, 34],))

df['value'] = df['response'] + ' - ' + df['layout']
df = df.sort_values('value')
# df2 = df.groupby(['value', 'week']).sum().reset_index().sort_values('value')

fig = go.Figure()
for v in df['value'].unique():
    dfp = df[df['value']==v]
    fig.add_traces(go.Bar(x=dfp['week'], y = dfp['cnt'], name = v))
fig.update_layout(barmode='stack', template='plotly_dark')
fig.show()