如何在数据框中引入新的索引值？

Question

I have the following dataframe, which the print(df_74034.head(10)) is:

                          HumExamRoom                      HumTechRoom Machine  TempExamRoom TempTechRoom
                                   NaN  2017-08-18\t09:22:33\t65.9   74034           NaN          NaN
                                   NaN  2017-10-03\t11:08:26\t60.5   74034           NaN          NaN
2018-02-17\t01:45:24          NaN                             69.7   74034           NaN          NaN
2018-02-17\t01:45:55          NaN                             67.5   74034           NaN          NaN
2018-02-17\t01:46:29          NaN                             65.4   74034           NaN          NaN
2018-02-17\t01:47:20          NaN                             63.3   74034           NaN          NaN
2018-02-17\t01:48:35          NaN                             61.3   74034           NaN          NaN
2018-02-17\t01:49:08          NaN                             63.4   74034           NaN          NaN
2018-02-17\t01:49:31          NaN                             65.5   74034           NaN          NaN
2018-02-17\t01:49:55          NaN                             67.6   74034           NaN          NaN

(The first two rows got a little messy) As you can see, the first two cells in the index have no values at all because their values are in the second column, which is probably a fault of my code - which I don't want to change anymore. Therefore, I would like to introduce the values 2017-08-18\\t09:22:33\\t and `2017-08-18\\t09:22:33\\t' in the index cells, respectively, and sort it. In order to sort I also have to change it to its correct date/time format.

I've already tried df_74034.index.insert(0, '2017-08-18\\t09:22:33') but it didn't work. I appretiate for the help!

Answer 1

You can perform it in other way -

df = dataframe name which in your case is df_74034.

1. You may try df.reset_index() which will place the current index values with integer number and will create column of your existing index value.
2. Create a new column of the values you want to set as index. Lets say name of the column is ABC
3. Then, you can use df.set_index('ABC',inplace=True) which will create a new index with values those are in ABC column.

I hope it may be helpful to some extend.