Sorting the grouped data as per group size in Pandas

I have two columns in my dataset, col1 and col2. I want group the data as per col1 and then sort the data as per the size of each group. That is, I want to display groups in ascending order of their size.

I have written the code for grouping and displaying the data as follows:

grouped_data = df.groupby('col1')
"""code for sorting comes here"""
for name,group in grouped_data:
          print (name)
          print (group)

Before displaying the data, I need to sort it as per group size, which I am not able to do.

For Pandas 0.17+, use sort_values:

df.groupby('col1').size().sort_values(ascending=False)

For pre-0.17, you can use size().order():

df.groupby('col1').size().order(ascending=False)

You can use python's sorted:

In [11]: df = pd.DataFrame([[1, 2], [1, 4], [5, 6]], index=['a', 'b', 'c'], columns=['A', 'B'])

In [12]: g = df.groupby('A')

In [13]: sorted(g,  # iterates pairs of (key, corresponding subDataFrame)
                key=lambda x: len(x[1]),  # sort by number of rows (len of subDataFrame)
                reverse=True)  # reverse the sort i.e. largest first
Out[13]: 
[(1,    A  B
     a  1  2
     b  1  4),
 (5,    A  B
     c  5  6)]

Note: as an iterator g, iterates over pairs of the key and the corresponding subframe:

In [14]: list(g)  # happens to be the same as the above...
Out[14]:
[(1,    A  B
     a  1  2
     b  1  4,
 (5,    A  B
     c  5  6)]