pandas "groupby" 在 headers 中制作了一个无法访问或删除的关卡
pandas "groupby" produced a level in headers that is unable to access or delete
df_india = pd.read_csv('fakepath\file.csv')
df_india.head()
清理后数据框如下所示
df_india.head(5)
因为我想按州分组
df_india = df_india.groupby(by=['State']).sum()
df_india.head(5)
Here comes the unnecessary level, but i am unable to access or remove
the 'State' level. I want both the columns on the same level as
headers for the dataFrame
我尝试重置索引,然后 headers 看起来像一个级别 headers。
df_india.reset_index().head(2)
但仍然无法访问'State'列
df_india['State']
只需在 groupby()
方法中使用 as_index
参数并将其设置为等于 False
:-
df_india = df_india.groupby(by=['State'],as_index=False).sum()
现在写:-
df_india['State']
使用reset_index()
时需要重新分配dataframe
df = df_india.reset_index()
或者您可以在调用 reset_index()
时使用 inplace=True
df_india.reset_index(inplace=True)
df_india = pd.read_csv('fakepath\file.csv')
df_india.head()
清理后数据框如下所示
df_india.head(5)
因为我想按州分组
df_india = df_india.groupby(by=['State']).sum()
df_india.head(5)
Here comes the unnecessary level, but i am unable to access or remove the 'State' level. I want both the columns on the same level as headers for the dataFrame
我尝试重置索引,然后 headers 看起来像一个级别 headers。
df_india.reset_index().head(2)
但仍然无法访问'State'列
df_india['State']
只需在 groupby()
方法中使用 as_index
参数并将其设置为等于 False
:-
df_india = df_india.groupby(by=['State'],as_index=False).sum()
现在写:-
df_india['State']
使用reset_index()
df = df_india.reset_index()
或者您可以在调用 reset_index()
inplace=True
df_india.reset_index(inplace=True)