AttributeError：“str”对象在 Seaborn、散点图中没有属性“view”

Posted 2023-02-16

【中文标题】AttributeError：“str”对象在 Seaborn、散点图中没有属性“view”

【英文标题】：AttributeError: 'str' object has no attribute 'view' in Seaborn , Scatterplot

【发布时间】：2019-05-30 13:09:28

【问题描述】：

我在 Seaborn 中遇到了一个奇怪的异常。

对于一个可重现的例子：

toy_data.to_json()
'"X":"0":0.12765045,"1":0.0244816152,"2":0.1263715245,"3":0.0246376768,"4":0.1108581319,"5":0.1406719382,"6":0.1358105564,"7":0.1245863432,"8":0.1175445352,"9":0.1188479018,"10":0.1113148159,"11":0.117455495,"12":0.110555662,"13":0.1328567106,"14":0.103064284,"15":0.1119474442,"16":0.119390455,"17":0.1246727756,"18":0.1117827155,"19":0.1169972547,"Y":"0":0.1241083714,"1":0.1394242378,"2":0.1225010796,"3":0.0077080173,"4":0.1198371354,"5":0.0029026989,"6":0.1259473297,"7":0.0,"8":0.0,"9":0.1214620231,"10":0.1204110739,"11":0.0,"12":0.1194570059,"13":0.0014971676,"14":0.1184584731,"15":0.1212061305,"16":0.1221438778,"17":0.0,"18":0.1209991075,"19":0.0,"Label":"0":"17","1":"3","2":"17","3":"0","4":"14","5":"21","6":"16","7":"23","8":"20","9":"15","10":"14","11":"20","12":"14","13":"22","14":"13","15":"14","16":"15","17":"23","18":"14","19":"20","Probability":"0":1.0,"1":1.0,"2":1.0,"3":1.0,"4":1.0,"5":1.0,"6":1.0,"7":1.0,"8":1.0,"9":1.0,"10":1.0,"11":1.0,"12":1.0,"13":1.0,"14":1.0,"15":1.0,"16":1.0,"17":1.0,"18":0.9101796407,"19":1.0'

toy_data.head()
       X           Y    Label   Probability
0   0.127650    0.124108    17  1.0
1   0.024482    0.139424    3   1.0
2   0.126372    0.122501    17  1.0
3   0.024638    0.007708    0   1.0
4   0.110858    0.119837    14  1.0

sns.scatterplot(x = toy_data.X, y = toy_data.Y, hue = toy_data.Label.values, alpha = 0.5)

AttributeError: 'str' object has no attribute 'view'

此语法的类似异常：

sns.scatterplot(x = 'X', y = 'Y', data = toy_data, hue = 'Label', alpha = 0.5)

【问题讨论】：

检查这个：github.com/mwaskom/seaborn/issues/1515

您应该将'Label' 列更改为数字。这样大概就可以了。除非它们确实是分类的。

【参考方案1】：

这是 seaborn 的一个特殊问题，颜色 palette 需要等于标签的数量

sns.scatterplot(x = toy_data.X, y = toy_data.Y, hue = toy_data.Label, alpha = 0.5,
                palette=sns.color_palette("Set1", toy_data.Label.nunique()) )

如果没有，seaborn 将应用数值函数将hue 类别的数量映射到默认的palette 四种颜色。这就是为什么当值是 string

时会出现错误的原因

【讨论】：

恕我直言，这应该是公认的答案，因为它不会强制色调为数字（考虑真正的分类数据，例如邮政编码）。以防万一还不够清楚：我们需要做的就是添加带有自定义颜色数量的调色板参数。

【参考方案2】：

如前所述，您的标签列是一个对象。它必须是一个数字（int 或 float）。

toy_data.info()

<class 'pandas.core.frame.DataFrame'>
Index: 20 entries, 0 to 9
Data columns (total 4 columns):
X              20 non-null float64
Y              20 non-null float64
Label          20 non-null object
Probability    20 non-null float64
dtypes: float64(3), object(1)
memory usage: 800.0+ bytes

这样做：

toy_data.loc[:,'Label'] = toy_data.Label.astype(np.float)

将其更改为浮动。

然后你的命令：

sns.scatterplot(x = toy_data.X, y = toy_data.Y, hue = toy_data.label.values, alpha = 0.5)

应该可以。

我正在使用这个命令来生成数据框

dict = "X":"0":0.12765045,"1":0.0244816152,"2":0.1263715245,"3":0.0246376768,"4":0.1108581319,"5":0.1406719382,"6":0.1358105564,"7":0.1245863432,"8":0.1175445352,"9":0.1188479018,"10":0.1113148159,"11":0.117455495,"12":0.110555662,"13":0.1328567106,"14":0.103064284,"15":0.1119474442,"16":0.119390455,"17":0.1246727756,"18":0.1117827155,"19":0.1169972547,"Y":"0":0.1241083714,"1":0.1394242378,"2":0.1225010796,"3":0.0077080173,"4":0.1198371354,"5":0.0029026989,"6":0.1259473297,"7":0.0,"8":0.0,"9":0.1214620231,"10":0.1204110739,"11":0.0,"12":0.1194570059,"13":0.0014971676,"14":0.1184584731,"15":0.1212061305,"16":0.1221438778,"17":0.0,"18":0.1209991075,"19":0.0,"Label":"0":"17","1":"3","2":"17","3":"0","4":"14","5":"21","6":"16","7":"23","8":"20","9":"15","10":"14","11":"20","12":"14","13":"22","14":"13","15":"14","16":"15","17":"23","18":"14","19":"20","Probability":"0":1.0,"1":1.0,"2":1.0,"3":1.0,"4":1.0,"5":1.0,"6":1.0,"7":1.0,"8":1.0,"9":1.0,"10":1.0,"11":1.0,"12":1.0,"13":1.0,"14":1.0,"15":1.0,"16":1.0,"17":1.0,"18":0.9101796407,"19":1.0
toy_data = pd.DataFrame(dict)

您需要 numpy import numpy as np 将值转换为浮点数

【讨论】：

不，色调变量可以是分类或数字。请参阅此处的文档seaborn.pydata.org/generated/seaborn.scatterplot.html