加载SK到癌症数据集熊猫DataFrame

Question

我想加载sklearn.dataset，并根据密钥（target_names，目标& DESCR）缺少一列。我尝试了各种方法来包含最后一列，但有错误。

import numpy as np 
import pandas as pd 
from sklearn.datasets import load_breast_cancer 

cancer = load_breast_cancer() 
print cancer.keys() 

键是[ 'target_names'， '数据'， '目标'， 'DESCR'， 'feature_names']

data = pd.DataFrame(cancer.data, columns=[cancer.feature_names]) 
print data.describe() 

与上面的代码，它只返回30列，当我需要31列。将scikit-learn数据集加载到pandas DataFrame中的最佳方式是什么？

Answer 1

如果你想有一个target列，你需要添加它，因为它不在cancer.data。 cancer.target的列有0或1，并且cancer.target_names有标签。我希望以下是你想要的：

import numpy as np 
import pandas as pd 
from sklearn.datasets import load_breast_cancer 

cancer = load_breast_cancer() 
print cancer.keys() 

data = pd.DataFrame(cancer.data, columns=[cancer.feature_names]) 
print data.describe() 

data = data.assign(target=pd.Series(cancer.target)) 
print data.describe() 

# In case you want labels instead of numbers. 
data.replace(to_replace={'target': {0: cancer.target_names[0]}}, inplace=True) 
data.replace(to_replace={'target': {1: cancer.target_names[1]}}, inplace=True) 
print data.shape # data.describe() won't show the "target" column here because I converted its value to string. 

Answer 2

这也适用，也使用pd.Series。

import numpy as np 
import pandas as pd 
from sklearn.datasets import load_breast_cancer 

cancer = load_breast_cancer() 
print cancer.keys() 

data = pd.DataFrame(cancer.data, columns=[cancer.feature_names]) 
data['Target'] = pd.Series(data=cancer.target, index=data.index) 

print data.keys() 
print data.shape 

Answer 3

另一种选择，而是一个班轮，创建数据框，包括功能和目标变量是：

import pandas as pd 
import numpy as np 
from sklearn.datasets import load_breast_cancer 

cancer = load_breast_cancer() 
df = pd.DataFrame(np.c_[cancer['data'], cancer['target']], 
        columns= np.append(cancer['feature_names'], ['target']))