AttributeError: 'list' object has no attribute 'addend'. Did you mean: 'append'?

AttributeError: 'list' object has no attribute 'addend'. 这个错误是因为在列表对象上调用了一个不存在的方法'addend'。根据错误提示，你可能想使用的是'append'方法。'append'方法用于在列表的末尾添加一个元素。

正确的用法是使用'append'方法来添加元素到列表中，例如：

my_list = []
my_list.append(10)

这样就可以将元素10添加到my_list列表的末尾。

相关问题

AttributeError: DataFrame object has no attribute append . Did you mean: _append ?

This error occurs when you try to call the `append` method on a Pandas DataFrame object, but the object does not have an `append` attribute.

One possible reason for this error is that you are trying to append a DataFrame to another DataFrame using the `append` method, but you are not using it correctly. In Pandas, the `append` method does not modify the original DataFrame, but instead it returns a new DataFrame that contains the rows from both DataFrames. Therefore, you need to assign the result of the `append` method to a new variable or to the original DataFrame, like this:

df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df2 = pd.DataFrame({'A': [5, 6], 'B': [7, 8]})
df3 = df1.append(df2)

In this example, `df3` will contain the rows from both `df1` and `df2`.

If you are still getting the AttributeError, it's possible that the DataFrame object you are trying to append to does not have an `append` attribute. In this case, you can try using the `_append` attribute instead, which is a private method that is used internally by Pandas. However, be aware that using private methods may not be supported in future versions of Pandas and may cause unexpected behavior.

df1._append(df2)

AttributeError: 'DataFrame' object has no attribute 'append'. Did you mean: '_append'?

This error occurs because the `DataFrame` object in pandas does not have an `append` method. Instead, you can use the `concat` method to concatenate two or more dataframes vertically. Here is an example:

import pandas as pd

# create two dataframes
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df2 = pd.DataFrame({'A': [7, 8, 9], 'B': [10, 11, 12]})

# concatenate vertically
df_combined = pd.concat([df1, df2])

print(df_combined)

This will output:

   A   B
0  1   4
1  2   5
2  3   6
0  7  10
1  8  11
2  9  12

Note that the index of the resulting dataframe is not reset. If you want to reset the index, you can add the `ignore_index=True` parameter to the `concat` method.