AttributeError: 'int' object has no attribute 'on'
时间: 2023-09-20 18:08:41 浏览: 42
This error occurs when you try to access an attribute or method of an integer object that does not exist. For example, if you try to call the "on" method on an integer object, you will receive this error message.
Here's an example of code that could cause this error:
```
num = 5
num.on()
```
In this case, "num" is an integer object with the value of 5. However, there is no "on" method available for integers, so Python raises an AttributeError.
To fix this error, you need to ensure that you are using the correct data types and that the attributes or methods you are trying to access actually exist for those data types.
相关问题
AttributeError: int object has no attribute int
抱歉,根据提供的引用内容,无法回答“AttributeError: int object has no attribute int”的问题。但是,根据错误信息“AttributeError: 'int' object has no attribute 'encode'”和“AttributeError: 'int' object has no attribute 'endswith'”,可以得出结论:在代码中,将整数类型的变量当作字符串类型来使用了,而整数类型没有“encode”或“endswith”等字符串类型的属性,因此会出现“AttributeError”错误。
解决这个问题的方法是,检查代码中是否有将整数类型的变量当作字符串类型来使用的情况,如果有,需要将其转换为字符串类型后再进行操作。可以使用str()函数将整数类型的变量转换为字符串类型,例如:
```python
num = 123
str_num = str(num)
```
AttributeError: list object has no attribute iloc
`iloc` is a method provided by Pandas DataFrame and Series objects to access data using integer-based indexing. It seems that you are using it with a list object which does not have this attribute.
To resolve this error, you should check if you are working with a Pandas DataFrame or Series object when trying to use `iloc`. If you are working with a list object, you can access its elements using integer-based indexing directly, without using `iloc`.
Here is an example:
```python
my_list = [1, 2, 3, 4, 5]
print(my_list[0]) # Output: 1
print(my_list[1:3]) # Output: [2, 3]
```
If you are working with a Pandas DataFrame or Series object, make sure to use the correct syntax for `iloc`. Here is an example:
```python
import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]})
print(df.iloc[0]) # Output: a 1\nb 4\nName: 0, dtype: int64
print(df.iloc[0, 1]) # Output: 4
```
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