使用pandas时,为什么会出现AttributeError？

Question

如何根据条件将NaN值转换为分类值.我在尝试转换Nan值时遇到错误.

category           gender     sub-category    title

health&beauty      NaN         makeup         lipbalm

health&beauty      women       makeup         lipstick

NaN                NaN         NaN            lipgloss

我的DataFrame看起来像这样.我将性别中的NaN值转换为分类值的功能如下所示

def impute_gender(cols):
    category=cols[0]
    sub_category=cols[2]
    gender=cols[1]
    title=cols[3]
    if title.str.contains('Lip') and gender.isnull==True:
        return 'women'
df[['category','gender','sub_category','title']].apply(impute_gender,axis=1)

如果我运行代码我会收到错误

----> 7     if title.str.contains('Lip') and gender.isnull()==True:
      8         print(gender)
      9 

AttributeError: ("'str' object has no attribute 'str'", 'occurred at index category')

完整数据集 - https://github.com/lakshmipriya04/py-sample

Answer 1

这里要注意的一些事情 -

1. 如果您只使用两列,则调用apply超过4列是浪费
2. apply一般来说,呼叫是浪费的,因为它很慢并且不会给您带来任何矢量化优势
3. 在应用中,您正在处理标量,因此您不像对象那样使用.str访问器pd.Series.title.contains就足够了.或者更诡异,"lip" in title.
4. gender.isnull是完全错误的,gender是一个标量,它没有isnull属性

选项1
np.where

m = df.gender.isnull() & df.title.str.contains('lip')
df['gender'] = np.where(m, 'women', df.gender)

df
        category gender sub-category     title
0  health&beauty  women       makeup   lipbalm
1  health&beauty  women       makeup  lipstick
2            NaN  women          NaN  lipgloss

这不仅快速,而且更简单.如果您担心区分大小写,可以使您的contains检查区不敏感 -

m = df.gender.isnull() & df.title.str.contains('lip', flags=re.IGNORECASE)

选项2
另一种选择是使用pd.Series.mask/ pd.Series.where-

df['gender'] = df.gender.mask(m, 'women')

要么,

df['gender'] = df.gender.where(~m, 'women')

df
        category gender sub-category     title
0  health&beauty  women       makeup   lipbalm
1  health&beauty  women       makeup  lipstick
2            NaN  women          NaN  lipgloss

在mask隐式应用的新的价值基础上提供的面具列.

Answer 2

或者只使用loc作为@ COLDSPEED答案的选项3

cond = (df['gender'].isnull()) & (df['title'].str.contains('lip'))
df.loc[cond, 'gender'] = 'women'


    category        gender  sub-category    title
0   health&beauty   women   makeup          lipbalm
1   health&beauty   women   makeup          lipstick
2   NaN             women       NaN         lipgloss