DataFrame' object has no attribute 'append'. Did you mean: '_append'? 什么意思

这个错误是因为DataFrame对象没有名为'append'的属性。相反，它有一个名为'_append'的属性。这个错误通常发生在尝试使用'append'方法向DataFrame对象添加行时。正确的方法是使用'_append'方法。下面是一个示例代码：

import pandas as pd

# 创建一个空的DataFrame对象
df = pd.DataFrame()

# 创建一个字典，包含要添加的行数据
new_row = {'col1': 1, 'col2': 2}

# 使用_append方法将新行添加到DataFrame对象中
df = df._append(new_row, ignore_index=True)

# 打印DataFrame对象
print(df)

这段代码将创建一个空的DataFrame对象，然后使用'_append'方法将新行添加到DataFrame对象中。请注意，我们在调用'_append'方法时使用了参数'ignore_index=True'，这将确保新行的索引正确地自动增加。

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)

'DataFrame' object has no attribute 'append'. Did you mean: '_append'?什么意思

这个错误提示是因为在DataFrame对象中没有名为'append'的属性或方法。相反，正确的方法是使用'concat'函数将两个DataFrame对象连接起来。下面是一个示例代码：

import pandas as pd

# 创建两个DataFrame对象
df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df2 = pd.DataFrame({'A': [5, 6], 'B': [7, 8]})

# 使用concat函数将两个DataFrame对象连接起来
df = pd.concat([df1, df2])

# 输出连接后的DataFrame对象
print(df)