英文:
AttributeError: 'NoneType' object has no attribute 'split' in Python
问题
以下是您运行时出现错误的命令：
start = datetime.now()
df_no_dup["tag_count"] = df_no_dup["Tags"].apply(lambda text: len(text.split(" ")))
# 添加一个新的特征：每个问题的标签数量
print("运行此单元格所花费的时间：", datetime.now() - start)
df_no_dup.head()
这是我收到的错误消息：
----> 3 df_no_dup["tag_count"] = df_no_dup["Tags"].apply(lambda text: len(text.split(" ")))
4 # 添加一个新的特征：每个问题的标签数量
5 print("运行此单元格所花费的时间：", datetime.now() - start)
AttributeError: 'NoneType' object has no attribute 'split'
英文:
Here are my commands that I get an error when I run:
start = datetime.now()
df_no_dup["tag_count"] = df_no_dup["Tags"].apply(lambda text: len(text.split(" ")))
# adding a new feature number of tags per question
print("Time taken to run this cell :", datetime.now() - start)
df_no_dup.head()
This is the error message I got:
----> 3 df_no_dup["tag_count"] = df_no_dup["Tags"].apply(lambda text: len(text.split(" ")))
4 # adding a new feature number of tags per question
5 print("Time taken to run this cell :", datetime.now() - start)
AttributeError: 'NoneType' object has no attribute 'split'
答案1
得分: 0
如果您确定您正在处理的值都是字符串，那么您可以做出判断。
from datetime import datetime
# 获取当前时间
start = datetime.now()
# 使用lambda函数计算每个问题中标签的数量，并将结果存储在新列"tag_count"中
df_no_dup["tag_count"] = df_no_dup["Tags"].apply(lambda text: len(text.split(" ")) if text else 0)
# 打印运行时间
print("运行此代码块所用时间：", datetime.now() - start)
# 显示DataFrame的前几行
df_no_dup.head()
英文:
If you are sure that the values you are dealing with are all strings then you can make a judgment
from datetime import datetime
start = datetime.now()
df_no_dup["tag_count"] = df_no_dup["Tags"].apply(lambda text: len(text.split(" ") if text else 0))
# adding a new feature number of tags per question
print("Time taken to run this cell :", datetime.now() - start)
df_no_dup.head()
答案2
得分: 0
df_no_dup["Tags"]的值为None。只需添加一个if条件来保护它。
start = datetime.now()
if df_no_dup["Tags"] is not None:
df_no_dup["tag_count"] = df_no_dup["Tags"].apply(lambda text: len(text.split(" ")))
# 添加一个新特征，每个问题的标签数量
print("运行此单元格所花费的时间：", datetime.now() - start)
df_no_dup.head()
英文:
df_no_dup["Tags"] is having None value. Just add an if clause to guard it.
start = datetime.now()
if df_no_dup["Tags"] is not None:
df_no_dup["tag_count"] = df_no_dup["Tags"].apply(lambda text: len(text.split(" ")))
# adding a new feature number of tags per question
print("Time taken to run this cell :", datetime.now() - start)
df_no_dup.head()
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