import pandas as pd df=pd.read_csv('H:/analysis_results/root_global_results_HN.csv') group_data=df.groupby(df['folder'].str[:-2]) result=group_data.agg({'volume':['mean','std'], 'convex_volume':['mean','std'], 'surface_area':['mean','std'], 'length':['mean','std'], 'max_width':['mean','std'], 'max_depth':['mean','std']} ) result.columns = ['_'.join(col).strip() for col in result.columns.values] result['folder'] = result.index result = result[['folder', 'volume_mean', 'volume_std', 'convex_volume_mean', 'convex_volume_std', 'surface_area_mean', 'surface_area_std', 'length_mean', 'length_std', 'max_width_mean', 'max_width_std', 'max_depth_mean', 'max_depth_std']] result = result.sort_values(by='folder') result_path='H:/analysis_results/mean_std_HN.csv' result.to_csv(result_path,index=False)运行时,出现错误'folder' is both an index level and a column label, which is ambiguous.,如何解决
时间: 2023-12-30 17:03:45 浏览: 21
这个错误是因为在使用 groupby 之后, 'folder' 列被作为索引使用了,但是在之后的代码中又被当作一个列来使用,这就导致了歧义性的问题。解决方法是在 groupby 之前先将 'folder' 列设置为普通列,可以使用 reset_index() 函数来实现,代码如下:
```
import pandas as pd
df=pd.read_csv('H:/analysis_results/root_global_results_HN.csv')
df = df.reset_index() # 将索引列转换为普通列
group_data = df.groupby(df['folder'].str[:-2])
result = group_data.agg({'volume':['mean','std'],
'convex_volume':['mean','std'],
'surface_area':['mean','std'],
'length':['mean','std'],
'max_width':['mean','std'],
'max_depth':['mean','std']} )
result.columns = ['_'.join(col).strip() for col in result.columns.values]
result['folder'] = result.index
result = result[['folder', 'volume_mean', 'volume_std', 'convex_volume_mean', 'convex_volume_std',
'surface_area_mean', 'surface_area_std', 'length_mean', 'length_std', 'max_width_mean',
'max_width_std', 'max_depth_mean', 'max_depth_std']]
result = result.sort_values(by='folder')
result_path='H:/analysis_results/mean_std_HN.csv'
result.to_csv(result_path,index=False)
```
在这个代码中,通过 reset_index() 函数将索引列转换为普通列,避免了 'folder' 列被当作索引的问题,从而解决了歧义性问题。