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：True 或False。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<i> 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 <symbol> 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' 在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True 或False。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！以上是关于Plotly：如何自定义 3D 散点图的符号？的主要内容，如果未能解决你的问题，请参考以下文章
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