pandas 熊猫属性错误：找不到属性“因子”
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pandas attribute error : no attribute 'Factor' found
提问by Yantra
I'm trying to run code provided by yhat in their article about random forests in Python, but I keep getting following error message:
我正在尝试运行 yhat在他们关于 Python 中的随机森林的文章中提供的代码，但我不断收到以下错误消息：
File "test_iris_with_rf.py", line 11, in <module>
df['species'] = pd.Factor(iris.target, iris.target_names)
AttributeError: 'module' object has no attribute 'Factor'
Code:
代码：
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier
import pandas as pd
import numpy as np
iris = load_iris()
df = pd.DataFrame(iris.data, columns=iris.feature_names)
print df
print iris.target_names
df['is_train'] = np.random.uniform(0, 1, len(df)) <= .75
df['species'] = pd.Factor(iris.target, iris.target_names)
df.head()
回答by David Robinson
In newer versions of pandas, the Factoris called Categoricalinstead. Change your line to:
在较新版本的Pandas中，改为Factor调用Categorical。将您的线路更改为：
df['species'] = pd.Categorical.from_codes(iris.target, iris.target_names)
回答by Andrew Rosenfeld
Categorical variables seems to be one of the more active areas of development in pandas, so I believe it's changed yet again in pandas 0.15.0 :
分类变量似乎是 pandas 中更活跃的发展领域之一，所以我相信它在 pandas 0.15.0 中再次发生了变化：
df['species'] = pd.Categorical.from_codes(iris.target, iris.target_names)
(I lacked sufficient reputation to add this as a comment on David Robinson's answer)
（我缺乏足够的声誉来将其添加为对大卫罗宾逊回答的评论）
回答by S?ren
def factor(series):
#input should be a pandas series object
dic = {}
for i,val in enumerate(series.value_counts().index):
dic[val] = i
return [ dic[val] for val in series.values ]
