如何对 pandas 列中的列表执行“一次热编码"? [英] How do I perform One Hot Encoding on lists in a pandas column?

问题描述

假设我有一个数据框，其中的一列是一个列表(值和长度未知)，例如:

Suppose I have a dataframe of which one column is a list (of a unknown values and length) for example:

df = pd.DataFrame(
 {'messageLabels': [['Good', 'Other', 'Bad'],['Bad','Terrible']]}
)

我遇到了这个解决方案，但这不是我想要的. 如何最好地提取包含多列列表或元组的Pandas列

I came across this solution but it isnt what I am looking for. How best to extract a Pandas column containing lists or tuples into multiple columns

理论上，最终的df看起来像

in theory the resulting df would look like

messageLabels             | Good| Other| Bad| Terrible
--------------------------------------------------------
['Good', 'Other', 'Bad']  | True| True |True| False
--------------------------------------------------------
['Bad','Terrible']        |False|False |True| True

见上文

推荐答案

另一种方法是使用apply和Series构造函数:

Another way is to use the apply and the Series constructor:

In [11]: pd.get_dummies(df.messageLabels.apply(lambda x: pd.Series(1, x)) == 1)
Out[11]:
    Good  Other   Bad  Terrible
0   True   True  True     False
1  False  False  True      True

其中

In [12]: df.messageLabels.apply(lambda x: pd.Series(1, x))
Out[12]:
   Good  Other  Bad  Terrible
0   1.0    1.0  1.0       NaN
1   NaN    NaN  1.0       1.0

---

要获得所需的输出，请执行以下操作:

---

To get your desired output:

In [21]: res = pd.get_dummies(df.messageLabels.apply(lambda x: pd.Series(1, x)) == 1)

In [22]: df[res.columns] = res

In [23]: df
Out[23]:
        messageLabels   Good  Other   Bad  Terrible
0  [Good, Other, Bad]   True   True  True     False
1     [Bad, Terrible]  False  False  True      True

这篇关于如何对 pandas 列中的列表执行“一次热编码"?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！