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Plotly:按值对堆积条形图的 y 轴条进行排序

[英]Plotly: Sorting the y-axis bars of a stacked bar chart by value

I have this code example using plotly that builds a stacked bar chart:我有这个使用 plotly 构建堆积条形图的代码示例:

import plotly.graph_objects as go

x = ['2018-01', '2018-02', '2018-03']

fig = go.Figure(go.Bar(x=x, y=[10, 15, 3], name='Client 1'))
fig.add_trace(go.Bar(x=x, y=[12, 7, 14], name='Client 2'))

fig.update_layout(
    barmode='stack',
    yaxis={'title': 'amount'},
    xaxis={
        'type': 'category',
        'title': 'month',
    },
)
fig.show()

Which outputs the following plot:输出以下图:

在此处输入图片说明

Is there a way to tweak the plotly layout as to order each bar's Y-axis by value?有没有办法调整绘图布局以按值对每个条形的 Y 轴进行排序?
For example in the second bar (2018-02) Client 1 has a higher value for Y, the blue bar should be on top of the red one.例如,在第二个条形 (2018-02) 中,客户端 1 的 Y 值较高,蓝色条形应位于红色条形之上。

In Plotly the traces are always displayed in the order in which they are added to the figure and there isn't a layout option that allows to change this behavior;在 Plotly 中,轨迹总是按照它们添加到图中的顺序显示,并且没有允许更改此行为的布局选项; see, for instance, this answer .例如,请参阅此答案 This means that for each date you would need to add the traces with the smaller values before adding the traces with the larger values.这意味着对于每个日期,您需要先添加具有较小值的跟踪,然后再添加具有较大值的跟踪。 I included an example below based on your code.我根据您的代码在下面包含了一个示例。

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

# data
df = pd.DataFrame({'Date': ['2018-01', '2018-02', '2018-03'],
                   'Client 1': [10, 15, 3],
                   'Client 2': [12, 7, 14],
                   'Client 3': [18, 2, 7]})

# colors
colors = {'Client 1': 'red',
          'Client 2': 'blue',
          'Client 3': 'green'}

# traces
data = []

# loop across the different rows
for i in range(df.shape[0]):

    # for each row, order the columns based on
    # their values from smallest to largest
    ordered_columns = df.columns[1:][np.argsort(df.iloc[i, 1:].values)]

    # add a separate trace for each column,
    # ordered from smallest to largest
    for column in ordered_columns:

        data.append(go.Bar(x=[df['Date'][i]],
                           y=[df[column][i]],
                           marker=dict(color=colors[column]),
                           name=column,
                           legendgroup=column,
                           showlegend=i == 0)) # show the legend only once for each column

# layout
layout = dict(barmode='stack',
              yaxis={'title': 'amount'},
              xaxis={'type': 'category', 'title': 'month'})

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

fig.show()

在此处输入图片说明

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