Merge two MultiIndex levels into one in Pandas

I have a Pandas data frame which is MultiIndexed. The second level contains a year ([2014,2015]) and the third contains the month number ([1, 2, .., 12]). I would like to merge these two into a single level like - [1/2014, 2/2014 ..., 6/2015]. How could this be done?

I'm new to Pandas. Searched a lot but could not find any similar question/solution.

Edit: I found a way to avoid having to do this altogether with the answer to this question. I should have been creating my data frame that way. This seems to be the way to go for indexing by DateTime.

Solution

Consider the pd.MultiIndex and pd.DataFrame, mux and df

mux = pd.MultiIndex.from_product([list('ab'), [2014, 2015], range(1, 3)])

df = pd.DataFrame(dict(A=1), mux)

print(df)

          A
a 2014 1  1
       2  1
  2015 1  1
       2  1
b 2014 1  1
       2  1
  2015 1  1
       2  1

We want to reassign to the index a list if lists that represent the index we want.

I want the 1st level the same
```
df.index.get_level_values(0)
```
I want the new 2nd level to be a string concatenation of the current 2nd and 3rd levels but reverse the order
```
df.index.map('{0[2]}/{0[1]}'.format)
```

df.index = [df.index.get_level_values(0), df.index.map('{0[2]}/{0[1]}'.format)]

print(df)

          A
a 1/2014  1
  2/2014  1
  1/2015  1
  2/2015  1
b 1/2014  1
  2/2014  1
  1/2015  1
  2/2015  1