python - Plotly:如何在带有刻面的图形表达图形中隐藏轴标题？

Question

有没有一种简单的方法可以使用 plotly express 在分面图中隐藏重复的轴标题？我试过设置

visible=True

在下面的代码中，但这也隐藏了 y 轴刻度标签(值)。理想情况下，我想将隐藏重复轴标题设置为一般多面图的默认值(或者甚至更好，只是默认为整个多面图显示单个 x 和 y 轴标题。
下面是测试代码:

import pandas as pd
import numpy as np
import plotly.express as px
import string

# create a dataframe
cols = list(string.ascii_letters)
n = 50

df = pd.DataFrame({'Date': pd.date_range('2021-01-01', periods=n)})

# create data with vastly different ranges
for col in cols:
    start = np.random.choice([1, 10, 100, 1000, 100000])
    s = np.random.normal(loc=0, scale=0.01*start, size=n)
    df[col] = start + s.cumsum()

# melt data columns from wide to long
dfm = df.melt("Date")

fig = px.line(
    data_frame=dfm,
    x = 'Date',
    y = 'value',
    facet_col = 'variable',
    facet_col_wrap=6,
    facet_col_spacing=0.05,
    facet_row_spacing=0.035,
    height = 1000,
    width = 1000,
    title = 'Value vs. Date'
)

fig.update_yaxes(matches=None, showticklabels=True, visible=True)
fig.update_annotations(font=dict(size=16))
fig.for_each_annotation(lambda a: a.update(text=a.text.split("=")[-1]))

最终代码(接受的答案)。注意 plotly >= 4.9

import pandas as pd
import numpy as np
import plotly.express as px
import string
import plotly.graph_objects as go

# create a dataframe
cols = list(string.ascii_letters)
n = 50

df = pd.DataFrame({'Date': pd.date_range('2021-01-01', periods=n)})

# create data with vastly different ranges
for col in cols:
    start = np.random.choice([1, 10, 100, 1000, 100000])
    s = np.random.normal(loc=0, scale=0.01*start, size=n)
    df[col] = start + s.cumsum()

# melt data columns from wide to long
dfm = df.melt("Date")

fig = px.line(
    data_frame=dfm,
    x = 'Date',
    y = 'value',
    facet_col = 'variable',
    facet_col_wrap=6,
    facet_col_spacing=0.05,
    facet_row_spacing=0.035,
    height = 1000,
    width = 1000,
    title = 'Value vs. Date'
)

fig.update_yaxes(matches=None, showticklabels=True, visible=True)
fig.update_annotations(font=dict(size=16))
fig.for_each_annotation(lambda a: a.update(text=a.text.split("=")[-1]))

# hide subplot y-axis titles and x-axis titles
for axis in fig.layout:
    if type(fig.layout[axis]) == go.layout.YAxis:
        fig.layout[axis].title.text = ''
    if type(fig.layout[axis]) == go.layout.XAxis:
        fig.layout[axis].title.text = ''
        
# keep all other annotations and add single y-axis and x-axis title:
fig.update_layout(
    # keep the original annotations and add a list of new annotations:
    annotations = list(fig.layout.annotations) + 
    [go.layout.Annotation(
            x=-0.07,
            y=0.5,
            font=dict(
                size=16, color = 'blue'
            ),
            showarrow=False,
            text="single y-axis title",
            textangle=-90,
            xref="paper",
            yref="paper"
        )
    ] +
    [go.layout.Annotation(
            x=0.5,
            y=-0.08,
            font=dict(
                size=16, color = 'blue'
            ),
            showarrow=False,
            text="Dates",
            textangle=-0,
            xref="paper",
            yref="paper"
        )
    ]
)

fig.show()

Answer 1

这个答案有五个部分:

隐藏子 plotly 标题(虽然不是 100% 确定你想这样做......)

使用 fig.layout[axis].tickfont = dict(color = 'rgba(0,0,0,0)') 隐藏 y 轴刻度值

使用 go.layout.Annotation(xref="paper", yref="paper") 设置单轴标签

plotly 图

最后完整的代码片段

这里非常重要的一点是，您可以编辑使用 px 生成的任何元素。函数使用 plotly.graph_object引用文献，例如 go.layout.XAxis .

1.隐藏子 plotly 标题
如果您对设置 fig 的方式感到满意，你可以只包括

for anno in fig['layout']['annotations']:
    anno['text']=''
    
fig.show()

2.隐藏yaxis文本
您可以在循环中使用以下内容将 yaxis tickfont 设置为透明

fig.layout[axis].tickfont = dict(color = 'rgba(0,0,0,0)')

该确切的行包含在下面的代码段中，它还删除了每个子图的 y 轴标题。
3. 单轴标签
删除轴标签和包含单个标签需要做更多的工作，但这里有一个非常灵活的设置，可以完全满足您的需要，如果您想以任何方式编辑新标签，则可以做更多:

# hide subplot y-axis titles and x-axis titles
for axis in fig.layout:
    if type(fig.layout[axis]) == go.layout.YAxis:
        fig.layout[axis].title.text = ''
    if type(fig.layout[axis]) == go.layout.XAxis:
        fig.layout[axis].title.text = ''
        
# keep all other annotations and add single y-axis and x-axis title:
fig.update_layout(
    # keep the original annotations and add a list of new annotations:
    annotations = list(fig.layout.annotations) + 
    [go.layout.Annotation(
            x=-0.07,
            y=0.5,
            font=dict(
                size=16, color = 'blue'
            ),
            showarrow=False,
            text="single y-axis title",
            textangle=-90,
            xref="paper",
            yref="paper"
        )
    ] +
    [go.layout.Annotation(
            x=0.5,
            y=-0.08,
            font=dict(
                size=16, color = 'blue'
            ),
            showarrow=False,
            text="Dates",
            textangle=-0,
            xref="paper",
            yref="paper"
        )
    ]
)

fig.show()

4. plotly

5.完整代码:

import pandas as pd
import numpy as np
import plotly.express as px
import string
import plotly.graph_objects as go

# create a dataframe
cols = list(string.ascii_letters)
cols[0]='zzz'
n = 50

df = pd.DataFrame({'Date': pd.date_range('2021-01-01', periods=n)})

# create data with vastly different ranges
for col in cols:
    start = np.random.choice([1, 10, 100, 1000, 100000])
    s = np.random.normal(loc=0, scale=0.01*start, size=n)
    df[col] = start + s.cumsum()

# melt data columns from wide to long
dfm = df.melt("Date")

fig = px.line(
    data_frame=dfm,
    x = 'Date',
    y = 'value',
    facet_col = 'variable',
    facet_col_wrap=6,
    #facet_col_spacing=0.05,
    #facet_row_spacing=0.035,
    height = 1000,
    width = 1000,
    title = 'Value vs. Date'
)

fig.update_yaxes(matches=None, showticklabels=True, visible=True)
fig.update_annotations(font=dict(size=16))
fig.for_each_annotation(lambda a: a.update(text=a.text.split("=")[-1]))

# subplot titles
for anno in fig['layout']['annotations']:
    anno['text']=''

# hide subplot y-axis titles and x-axis titles
for axis in fig.layout:
    if type(fig.layout[axis]) == go.layout.YAxis:
        fig.layout[axis].title.text = ''
    if type(fig.layout[axis]) == go.layout.XAxis:
        fig.layout[axis].title.text = ''
        
# keep all other annotations and add single y-axis and x-axis title:
fig.update_layout(
    # keep the original annotations and add a list of new annotations:
    annotations = list(fig.layout.annotations) + 
    [go.layout.Annotation(
            x=-0.07,
            y=0.5,
            font=dict(
                size=16, color = 'blue'
            ),
            showarrow=False,
            text="single y-axis title",
            textangle=-90,
            xref="paper",
            yref="paper"
        )
    ] +
    [go.layout.Annotation(
            x=0.5,
            y=-0.08,
            font=dict(
                size=16, color = 'blue'
            ),
            showarrow=False,
            text="Dates",
            textangle=-0,
            xref="paper",
            yref="paper"
        )
    ]
)


fig.show()