pandas: convert index type in multiindex dataframe

I find the current pandas implementation a bit cumbersome, so I use this:

df1.index = pd.MultiIndex.from_tuples([(ix[0], str(ix[1])) for ix in df1.index.tolist()])

There was change in pandas and old way doesn't work properly.

For me this worked.

level_to_change = 1
df.index = df.index.set_levels(df.index.levels[level_to_change].astype(int), level=level_to_change)

Very late to the party, but if you also want to maintain the names on your multi-index levels, I'd suggest the following:

df_ts.index = pd.MultiIndex.from_frame(
    pd.DataFrame(index=df_ts.index)
    .reset_index().astype(int)
    )

Similarly if you have multi-index columns, you can use:

df_ts.columns = pd.MultiIndex.from_frame(
        pd.DataFrame(index=df_ts.columns)
        .reset_index().astype(int)
        )

IIUC you need the last level of Multiindex. You could access it with levels:

df1.index.levels[-1].astype(str)

In [584]: df1.index.levels[-1].astype(str)
Out[584]: Index(['1', '2', '3', '4', '96', '99'], dtype='object', name='Values')

EDIT

You could set your inner level with set_levels method of multiIndex:

idx = df1.index
df1.index = df1.index.set_levels([idx.levels[:-1], idx.levels[-1].astype(str)])