将SKLearn癌症数据集加载到Pandas DataFrame中

Question

我正在尝试加载一个sklearn.dataset，并根据键(target_names、target & DESCR)缺少一列。我尝试过各种方法来包含最后一栏，但是有错误。

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

 cancer = load_breast_cancer()
 print cancer.keys()

这些键是‘target_name’，'data'，'target'，'DESCR'，'feature_names‘

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

使用上面的代码，当我需要31列时，它只返回30列。什么是最好的方式加载科学知识-学习数据集到熊猫DataFrame。

Answer 1

另一个选项，但只有一个线性，创建包含特性和目标变量的数据文件是：

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']))

Answer 2

如果您想要有一个target列，就需要添加它，因为它不在cancer.data中。cancer.target有带有0或1的列，而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 3

这也是工作的，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