Python 将数据帧的默认索引更改为列

Python 将数据帧的默认索引更改为列,python,pandas,Python,Pandas,我试图通过将新的索引列设置为响应者来将我的数据帧(stack overflow's survey of 2019)的默认索引从0-98854更改为1-101548。然后,与使用默认索引相比,我将使用此索引以更高的精度访问单个行 第一次尝试:我尝试使用df.reset\u index(drop=True)重置索引,但似乎不起作用 第二次尝试:我也尝试过使用df.set_index('responder',inplace=True)但它也不起作用——默认索引首先显示,我无法按标签搜索(例如df.lo

我试图通过将新的索引列设置为响应者来将我的数据帧(stack overflow's survey of 2019)的默认索引从0-98854更改为1-101548。然后,与使用默认索引相比,我将使用此索引以更高的精度访问单个行

第一次尝试:我尝试使用
df.reset\u index(drop=True)
重置索引,但似乎不起作用

第二次尝试:我也尝试过使用
df.set_index('responder',inplace=True)
但它也不起作用——默认索引首先显示,我无法按标签搜索(例如
df.loc['3']
-
keyrerror:'3'

数据帧预览:

    Respondent Hobby OpenSource             Country  ... Dependents MilitaryUS                         SurveyTooLong     SurveyEasy      
0               1   Yes         No               Kenya  ...        Yes        NaN  The survey was an appropriate length      Very easy      
1               3   Yes        Yes      United Kingdom  ...        Yes        NaN  The survey was an appropriate length  Somewhat easy      
2               4   Yes        Yes       United States  ...        NaN        NaN                                   NaN            NaN      
3               5    No         No       United States  ...         No         No  The survey was an appropriate length  Somewhat easy      
4               7   Yes         No        South Africa  ...        Yes        NaN  The survey was an appropriate length  Somewhat easy      
...           ...   ...        ...                 ...  ...        ...        ...                                   ...            ...      
98850      101513   Yes        Yes       United States  ...        NaN        NaN                                   NaN            NaN      
98851      101531    No        Yes               Spain  ...        NaN        NaN                                   NaN            NaN      
98852      101541   Yes        Yes               India  ...        NaN        NaN                                   NaN            NaN      
98853      101544   Yes         No  Russian Federation  ...        NaN        NaN                                   NaN            NaN      
98854      101548   Yes        Yes            Cambodia  ...        NaN        NaN                                   NaN            NaN    
df.set\u索引('responder',inplace=True)
应该可以工作。没有理由不应该
df.loc['3']
不起作用,因为您的索引是int,而不是字符串。尝试
df.loc[3]

df.set\u index('responder',inplace=True)
应该可以工作,你能提供一个没有工作的地方吗?