How to iterate over Pandas Series generated from groupby().size()

Question

How do you iterate over a Pandas Series generated from a .groupby('...').size() command and get both the group name and count.

As an example if I have:

foo -1     7  0    85  1    14  2     5 

how can I loop over them so the that each iteration I would have -1 & 7, 0 & 85, 1 & 14 and 2 & 5 in variables?

I tried the enumerate option but it doesn't quite work. Example:

for i, row in enumerate(df.groupby(['foo']).size()):     print(i, row) 

it doesn't return -1, 0, 1, and 2 for i but rather 0, 1, 2, 3.

Answer 1

Update:

Given a pandas Series:

s = pd.Series([1,2,3,4], index=['a', 'b', 'c', 'd'])  s #a    1 #b    2 #c    3 #d    4 #dtype: int64 

You can directly loop through it, which yield one value from the series in each iteration:

for i in s:     print(i) 1 2 3 4 

If you want to access the index at the same time, you can use either items or iteritems method, which produces a generator that contains both the index and value:

for i, v in s.items():     print('index: ', i, 'value: ', v) #index:  a value:  1 #index:  b value:  2 #index:  c value:  3 #index:  d value:  4  for i, v in s.iteritems():     print('index: ', i, 'value: ', v) #index:  a value:  1 #index:  b value:  2 #index:  c value:  3 #index:  d value:  4 

---

Old Answer:

You can call iteritems() method on the Series:

for i, row in df.groupby('a').size().iteritems():     print(i, row)  # 12 4 # 14 2 

According to doc:

Series.iteritems()

Lazily iterate over (index, value) tuples

Note: This is not the same data as in the question, just a demo.