I have a pandas data frame which is a result of pivoting. It has multiple indices. I want to get a "normal" data frame out of this pivoted df...so that I can do some normal operations on the new df.

Here is an example: My pivoted data frame looks like this:

```
                      feature_value
feature_type          f1  f2  f3  f4  f5
time         name
2016-05-10   Clay     0   1   30   4  40
2016-05-10   John     0   4   10   4  66
2016-05-10   Mary     0   1   40   4  46
2016-05-10   Boby     2   0   30   4  59
2016-05-10   Lucy     5   8   20   4  41

```

The following is what I want as a new df:

```
time         name     f1  f2  f3  f4  f5
2016-05-10   Clay     0   1   30   4  40
2016-05-10   John     0   4   10   4  66
2016-05-10   Mary     0   1   40   4  46
2016-05-10   Boby     2   0   30   4  59
2016-05-10   Lucy     5   8   20   4  41

```

How can I do this?

The pivoted\_df.to\_dict() looks like this:

```
{('feature_value', 'f1'): {(Timestamp('2016-05-10'), 'Clay'): 0, (Timestamp('2016-05-10'), 'John'): 0, (Timestamp('2016-05-10'), 'Mary'): 0, (Timestamp('2016-05-10'), 'Boby'): 2, (Timestamp('2016-05-10'), 'Lucy'): 5}, ('feature_value', 'f2'): {(Timestamp('2016-05-10'), 'Clay'): 1, (Timestamp('2016-05-10'), 'John'): 4, (Timestamp('2016-05-10'), 'Mary'): 1, (Timestamp('2016-05-10'), 'Boby'): 0, (Timestamp('2016-05-10'), 'Lucy'): 8}, ('feature_value', 'f3'): {(Timestamp('2016-05-10'), 'Clay'): 30, (Timestamp('2016-05-10'), 'John'): 10, (Timestamp('2016-05-10'), 'Mary'): 40, (Timestamp('2016-05-10'), 'Boby'): 30, (Timestamp('2016-05-10'), 'Lucy'): 20}, ('feature_value', 'f4'): {(Timestamp('2016-05-10'), 'Clay'): 4, (Timestamp('2016-05-10'), 'John'): 4, (Timestamp('2016-05-10'), 'Mary'): 4, (Timestamp('2016-05-10'), 'Boby'): 4, (Timestamp('2016-05-10'), 'Lucy'): 4}, ('feature_value', 'f5'): {(Timestamp('2016-05-10'), 'Clay'): 40, (Timestamp('2016-05-10'), 'John'): 66, (Timestamp('2016-05-10'), 'Mary'): 46, (Timestamp('2016-05-10'), 'Boby'): 59, (Timestamp('2016-05-10'), 'Lucy'): 41}}

```