df3.append(df4).shape遇到问题'DataFrame' object has no attribute 'append'
时间: 2024-06-12 17:01:52 浏览: 13
这个问题的报错信息"DataFrame' object has no attribute 'append'"意味着您正在尝试使用DataFrame对象的append方法,但是该对象并没有该方法。这可能是由于您正在使用的pandas版本太旧导致的。在新版本的pandas中,建议使用concat方法来实现DataFrame的连接操作。您可以使用以下语句将两个DataFrame对象连接起来:
```python
new_df = pd.concat([df3, df4], axis=0, ignore_index=True)
```
其中,pd是pandas的别名,axis参数指定按照行连接(axis=0)或按照列连接(axis=1),ignore_index参数为True时,会重置新DataFrame的索引。如果您希望按照列连接两个DataFrame对象,则需要将axis参数设置为1。
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)
```
python报错dataframe object has no attribute append
这个错误是因为DataFrame对象没有append方法,所以无法直接调用。相反,您可以使用concat方法将两个DataFrame对象连接在一起。例如:
```python
import pandas as pd
df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df2 = pd.DataFrame({'A': [5, 6], 'B': [7, 8]})
df3 = pd.concat([df1, df2], ignore_index=True)
print(df3)
```
这将输出以下结果:
```
A B
0 1 3
1 2 4
2 5 7
3 6 8
```
在这个示例中,我们使用concat方法将df1和df2连接在一起,并将结果存储在df3中。请注意,我们设置了ignore_index参数为True,这样就可以重新索引结果DataFrame的行。