list.append出错AttributeError: 'DataFrame' object has no attribute 'append'

在Pandas中，DataFrame对象没有append()方法。如果您想将行添加到DataFrame中，可以使用concat()方法或append()方法。下面是两种解决方案：

1.使用concat()方法将行添加到DataFrame中：

import pandas as pd

# 创建一个空的DataFrame
df = pd.DataFrame(columns=['A', 'B'])
# 创建要添加的行
new_row = pd.DataFrame({'A': [1], 'B': [2]})

# 使用concat()方法将新行添加到DataFrame中
df = pd.concat([df, new_row], ignore_index=True)

# 打印DataFrame
print(df)

2.使用append()方法将行添加到DataFrame中：

import pandas as pd

# 创建一个空的DataFrame
df = pd.DataFrame(columns=['A', 'B'])

# 创建要添加的行
new_row = pd.DataFrame({'A': [1], 'B': [2]})

# 使用append()方法将新行添加到DataFrame中
df = df.append(new_row, ignore_index=True)

# 打印DataFrame
print(df)

相关问题

AttributeError: DataFrame object has no attribute append

AttributeError: 'DataFrame' object has no attribute 'append' 错误通常发生在使用DataFrame对象的append方法时。这个错误的原因是因为在pandas的较新版本中，DataFrame对象已经不再具有append方法。

解决这个问题的方法是使用concat函数来连接两个DataFrame对象。concat函数可以在行或列方向上合并数据。如果想要在行方向上合并两个DataFrame对象，可以使用concat函数的axis参数设置为0。例如：

import pandas as pd

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

result = pd.concat([df1, df2], axis=0)

在这个例子中，df1和df2是两个DataFrame对象，通过concat函数，我们将它们在行方向上合并为一个新的DataFrame对象result。<span class="em">1</span><span class="em">2</span><span class="em">3</span><span class="em">4</span>

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)