AttributeError：'str'对象在Seaborn，Scatterplot中没有属性'view'

Question

我在Seaborn遇到一个奇怪的例外。

有关可重现的示例：

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'

与此语法类似的例外情况：

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

Answer 1

如图所示，列Label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

执行以下操作：

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

将其更改为浮动。

然后输入命令：

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

应该工作。

我正在使用此命令生成数据帧

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才能将值转换为浮点数

Answer 2

这是seaborn特有的问题，其中颜色palette需要等于标签数

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()) )

否则，seaborn将应用数值函数将hue类的数量映射为默认的{strong>四种颜色的palette。这就是为什么当值为字符串

时会出错的原因