Plotly:如何自定义 3D 散点图的符号?

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【中文标题】Plotly:如何自定义 3D 散点图的符号?【英文标题】:Plotly: How to customize the symbols of a 3D scatter plot? 【发布时间】:2021-01-11 09:45:31 【问题描述】:

在下面的例子中:

import plotly.express as px
df = px.data.iris()
fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
                    color='petal_length', symbol='species')
fig.show()

symbol 由圆形、菱形和正方形表示的'species' 决定。当样本量变大并且样本点涂抹图时,这可能不是很清楚。我们如何自定义符号,例如使用圆形、方形和十字(或其他对比形状的组合)?


更新:

我将代码应用于另一个数据集和代码:

fig = px.scatter_3d(df8, x='X', y='Y', z='Z',
                    color='P', symbol='C')

# specify trace names and symbols in a dict
symbols = 'True': 'cross',
           'False':'circle-open'

# set all symbols in fig
for i, d in enumerate(fig.data):
    fig.data[i].marker.symbol = symbols[fig.data[i].name]

fig.show()

其中C 有两个值:TrueFalse。但是它发现了错误:

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-183-ea1e2ec7dd8e> in <module>
     36 # set all symbols in fig
     37 for i, d in enumerate(fig.data):
---> 38     fig.data[i].marker.symbol = symbols[fig.data[i].name]
     39 
     40 fig.show()

KeyError: 'P, True'

更新:

可重现的例子:

'ID': 0: '672590',
  1: '672120',
  2: '672090',
  3: '672349',
  4: '672453',
  5: '672560',
  6: '672051',
  7: '880505',
  8: '672593',
  9: '880097',
  10: '891458',
  11: '672091',
  12: '672569',
  13: '672603',
  14: '790030',
  15: '672350',
  16: '673480',
  17: 'I00042',
  18: '880297',
  19: '894620',
 'X': 0: 0.20111215435497176,
  1: 0.21248998904335528,
  2: 0.2086689759935364,
  3: 0.22337836085443835,
  4: 0.17847099434376115,
  5: 0.24827331723865761,
  6: 0.14411891907440183,
  7: 0.20863940038267367,
  8: 0.166299824101773,
  9: 0.20548401328860527,
  10: 0.18007828100726822,
  11: 0.21887731187605308,
  12: 0.1971207940494219,
  13: 0.19247420041228508,
  14: 0.21605657330040987,
  15: 0.15779241902165092,
  16: 0.22536060645732897,
  17: 0.19268784843224268,
  18: 0.2400112771421119,
  19: 0.22548124117213691,
 'Y': 0: 2473.923076923077,
  1: 2031.1538461538462,
  2: 2383.1923076923076,
  3: 1830.7692307692307,
  4: 1780.2307692307693,
  5: 1194.8461538461538,
  6: 1641.0,
  7: 1563.3076923076924,
  8: 1246.2307692307693,
  9: 931.6153846153846,
  10: 1207.076923076923,
  11: 799.6538461538462,
  12: 560.8461538461538,
  13: 1158.076923076923,
  14: 1221.6923076923076,
  15: 3030.076923076923,
  16: 1178.076923076923,
  17: 552.3846153846154,
  18: 1380.3076923076924,
  19: 1027.5384615384614,
 'Z': 0: 385.84615384615387,
  1: 288.46153846153845,
  2: 281.9230769230769,
  3: 273.61538461538464,
  4: 252.0,
  5: 231.69230769230768,
  6: 213.30769230769232,
  7: 203.3846153846154,
  8: 191.07692307692307,
  9: 189.46153846153845,
  10: 181.07692307692307,
  11: 176.76923076923077,
  12: 173.30769230769232,
  13: 169.6153846153846,
  14: 166.15384615384616,
  15: 165.30769230769232,
  16: 160.53846153846155,
  17: 159.84615384615384,
  18: 159.0,
  19: 145.3846153846154,
 'C': 0: True,
  1: True,
  2: True,
  3: True,
  4: True,
  5: True,
  6: True,
  7: True,
  8: True,
  9: True,
  10: True,
  11: False,
  12: False,
  13: True,
  14: True,
  15: True,
  16: True,
  17: False,
  18: True,
  19: True,
 'P': 0: 'P',
  1: 'P',
  2: 'P',
  3: 'P',
  4: 'P',
  5: 'X',
  6: 'P',
  7: 'P',
  8: 'P',
  9: 'P',
  10: 'P',
  11: 'P',
  12: 'P',
  13: 'P',
  14: 'P',
  15: 'P',
  16: 'P',
  17: 'X',
  18: 'P',
  19: 'P'

【问题讨论】:

@nilsinlabore 我的建议对你有什么效果? 嗨@vestland 感谢您的精彩回答,并为迟到的回复道歉。你能看看问题更新吗? @嗨!让我们把这个移到chat 你有没有得到任何数据样本? @vestland 请查看问题更新,谢谢! 【参考方案1】:

答案:

# specify trace names and symbols in a dict
symbols = 'setosa': 'cross',
           'versicolor':'circle-open',
           'virginica':'diamond-open'

# set all symbols in fig
for i, d in enumerate(fig.data):
    fig.data[i].marker.symbol = symbols[fig.data[i].name]

详情:

在这种情况下,您可以手动设置任何标记符号,例如:

fig.data[<i>].marker.symbol = <symbol>

其中&lt;i&gt; 是一个整数索引,用于指定您要更改的轨迹,而 3D 散布对象的 &lt;symbol&gt; 属性是一个枚举,可以指定为以下枚举值之一:

['circle', 'circle-open', 'square', 'square-open',
'diamond', 'diamond-open', 'cross', 'x']

示例 1 - 单个跟踪:

fig.data[2].marker.symbol = 'circle-open'
fig.show()

情节1:

示例 2 - 多个跟踪:

为了让事情更加动态,您可以使用以下方法检索所有跟踪名称:

['setosa', 'versicolor', 'virginica']

然后您可以指定自己的名称和符号字典,并使用以下方法为所有跟踪设置所有符号:

# specify trace names and symbols in a dict
symbols = 'setosa': 'cross',
           'versicolor':'circle-open',
           'virginica':'diamond-open'

# set all symbols in fig
for i, d in enumerate(fig.data):
    fig.data[i].marker.symbol = symbols[fig.data[i].name]

fig.show()

情节2:

完整代码:

import plotly.express as px
df = px.data.iris()
fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
                    color='petal_length', symbol='species')
#fig.show()

# specify trace names and symbols in a dict
symbols = 'setosa': 'cross',
           'versicolor':'circle-open',
           'virginica':'diamond-open'

# set all symbols in fig
for i, d in enumerate(fig.data):
    fig.data[i].marker.symbol = symbols[fig.data[i].name]

fig.show()

编辑:OP 对附录的回答

这里发生的是您使用color='P', symbol='C'px.scatter3d 中分配颜色和符号。这会对现在的跟踪名称产生影响,例如,'name': 'P, True'。这会导致以下问题:

for i, d in enumerate(fig.data):
    fig.data[i].marker.symbol = symbols[fig.data[i].name]

根据您定义的符号字典判断:

# specify trace names and symbols in a dict
symbols = 'True': 'cross',
           'False':'circle-open'

您似乎只想通过'name': 'P, True' 的最后一部分来区分您的符号,即TrueFalse。您可以通过在symbols[fig.data[i].name.split(', ')[1]] 中指定符号字典来对符号字典进行子集化,从而获得:

带有数据示例的完整代码:

import pandas as pd
import plotly.express as px

df8 = pd.DataFrame('ID': 0: '672590',
  1: '672120',
  2: '672090',
  3: '672349',
  4: '672453',
  5: '672560',
  6: '672051',
  7: '880505',
  8: '672593',
  9: '880097',
  10: '891458',
  11: '672091',
  12: '672569',
  13: '672603',
  14: '790030',
  15: '672350',
  16: '673480',
  17: 'I00042',
  18: '880297',
  19: '894620',
 'X': 0: 0.20111215435497176,
  1: 0.21248998904335528,
  2: 0.2086689759935364,
  3: 0.22337836085443835,
  4: 0.17847099434376115,
  5: 0.24827331723865761,
  6: 0.14411891907440183,
  7: 0.20863940038267367,
  8: 0.166299824101773,
  9: 0.20548401328860527,
  10: 0.18007828100726822,
  11: 0.21887731187605308,
  12: 0.1971207940494219,
  13: 0.19247420041228508,
  14: 0.21605657330040987,
  15: 0.15779241902165092,
  16: 0.22536060645732897,
  17: 0.19268784843224268,
  18: 0.2400112771421119,
  19: 0.22548124117213691,
 'Y': 0: 2473.923076923077,
  1: 2031.1538461538462,
  2: 2383.1923076923076,
  3: 1830.7692307692307,
  4: 1780.2307692307693,
  5: 1194.8461538461538,
  6: 1641.0,
  7: 1563.3076923076924,
  8: 1246.2307692307693,
  9: 931.6153846153846,
  10: 1207.076923076923,
  11: 799.6538461538462,
  12: 560.8461538461538,
  13: 1158.076923076923,
  14: 1221.6923076923076,
  15: 3030.076923076923,
  16: 1178.076923076923,
  17: 552.3846153846154,
  18: 1380.3076923076924,
  19: 1027.5384615384614,
 'Z': 0: 385.84615384615387,
  1: 288.46153846153845,
  2: 281.9230769230769,
  3: 273.61538461538464,
  4: 252.0,
  5: 231.69230769230768,
  6: 213.30769230769232,
  7: 203.3846153846154,
  8: 191.07692307692307,
  9: 189.46153846153845,
  10: 181.07692307692307,
  11: 176.76923076923077,
  12: 173.30769230769232,
  13: 169.6153846153846,
  14: 166.15384615384616,
  15: 165.30769230769232,
  16: 160.53846153846155,
  17: 159.84615384615384,
  18: 159.0,
  19: 145.3846153846154,
 'C': 0: True,
  1: True,
  2: True,
  3: True,
  4: True,
  5: True,
  6: True,
  7: True,
  8: True,
  9: True,
  10: True,
  11: False,
  12: False,
  13: True,
  14: True,
  15: True,
  16: True,
  17: False,
  18: True,
  19: True,
 'P': 0: 'P',
  1: 'P',
  2: 'P',
  3: 'P',
  4: 'P',
  5: 'X',
  6: 'P',
  7: 'P',
  8: 'P',
  9: 'P',
  10: 'P',
  11: 'P',
  12: 'P',
  13: 'P',
  14: 'P',
  15: 'P',
  16: 'P',
  17: 'X',
  18: 'P',
  19: 'P')

fig = px.scatter_3d(df8, x='X', y='Y', z='Z',
                    color='P', symbol='C')

# specify trace names and symbols in a dict
symbols = 'True': 'cross',
           'False':'circle-open'

# set all symbols in fig
for i, d in enumerate(fig.data):
    fig.data[i].marker.symbol = symbols[fig.data[i].name.split(', ')[1]]

fig.show()

【讨论】:

您能否分享一些您的解决方案所基于的文档?我尝试使用谷歌搜索,但在 px.scatter_3d 上找不到太多信息。非常感谢!

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