Basic indexing on axis with MultiIndex - python-3.x

Question

This is my multiIndex dataframe gotten from groupby where I have 2 indexes [ 'YearMonth', 'product_id'] and column name ['count'] I've tried examples from documentation and other stackoverflow suggestions but still cannot index product_id == 6818 for each YearMonth index column.
df = df.groupby(['YearMonth','product_id'])[['count']].sum()
df.head(5)
Out[54]:
count
YearMonth product_id
2017-05-01 6818 3
7394 1 7394 1
8369 1 8369 1
8504 1 8504 1
8666 1 8666 1
In [55]:
df.columns
Out[55]:
Index(['count'], dtype='object')
In [56]:
df.index.names
Out[56]:
FrozenList(['YearMonth', 'product_id'])
In [59]:
df.loc[('2017-05-01',0),'count']
I've tried: simple indexing df['YearMonth'] but it only works with columns not indexes
df.loc\ix\iloc as was given in this stackoverflow question
df.loc[('2017-05-01',0)]
Always I get KeyError such as KeyError: ('2017-05-01', 0) , KeyError: 'YearMonth'
as well as I did a try to unstack method df.unstack(level=0) and did the same manipulations as written above
May someone explain what am I missing? Thanks in advance

Answer 1

Your sample DF doesn't look "healthy" - i have fixed it so it looks like as follows now:
In [121]: df
Out[121]:
count
YearMonth product_id
2017-05-01 6818 3
7394 1
8369 1
8504 1
8666 1
Option 1:
In [122]: df.loc[pd.IndexSlice[:, 6818], :]
Out[122]:
count
YearMonth product_id
2017-05-01 6818 3
Option 2: works for named indices
In [145]: df.query("product_id in [6818]")
Out[145]:
count
YearMonth product_id
2017-05-01 6818 3
Option 3:
In [146]: df.loc[(slice(None), 6818), :]
Out[146]:
count
YearMonth product_id
2017-05-01 6818 3