python - 在 Python DataFrame 上应用 lambda

Question

我有一个像

这样的 Python Pandas DataFrame

>>> df
  classification like 
0         flower    1 
1         flower    0 
2         flower    0 
3      adventure    1 
4      adventure    1 

我想创建一个像这样的输出DataFrame

>>> df
  classification like  liked
0         flower    1  True
1         flower    0  False
2         flower    0  False
3      adventure    1  True
4      adventure    1  True

我在输入 DataFrame 上“应用”Python lambda 函数，如下所示:

>>> df['like'].apply(lambda x: x == 1)

但是我在“喜欢”栏下得到的都是“假”

>>> df
  classification like  liked
0         flower    1  False
1         flower    0  False
2         flower    0  False
3      adventure    1  False
4      adventure    1  False

任何快速建议都会有所帮助。

>>> df['like'].astype(int)
0    1
1    0
2    0
3    1
4    1
Name: like, dtype: int32

@杰斯雷尔

>>> df['liked'] = df['like'].astype(bool)
>>> df
  classification like  liked
0         flower    1   True
1         flower    0   True
2         flower    0   True
3      adventure    1   True
4      adventure    1   True

@jezrael : DTypes

>>> df.dtypes
classification    object
like              object
liked               bool
dtype: object

Answer 1

将整数列转换为 bool 值:

print (type(df.loc[0, 'like']))
<class 'numpy.int64'>

df['liked'] = df['like'].astype(bool)

或分配与 1 的比较:

df['liked'] = df['like'] == 1

如果 1 是字符串，通过字符串 '1' 比较:

print (type(df.loc[0, 'like']))
<class 'str'>

df['liked'] = df['like'] == '1'
print (df)
  classification like  liked
0         flower    1   True
1         flower    0  False
2         flower    0  False
3      adventure    1   True
4      adventure    1   True