numpy - Python Pandas: remove entries based on the number of occurrences

Question

I'm trying to remove entries from a data frame which occur less than 100 times. The data frame data looks like this:

pid   tag
1     23    
1     45
1     62
2     24
2     45
3     34
3     25
3     62

Now I count the number of tag occurrences like this:

bytag = data.groupby('tag').aggregate(np.count_nonzero)

But then I can't figure out how to remove those entries which have low count...

Answer 1

New in 0.12, groupby objects have a filter method, allowing you to do these types of operations:

In [11]: g = data.groupby('tag')

In [12]: g.filter(lambda x: len(x) > 1)  # pandas 0.13.1
Out[12]:
   pid  tag
1    1   45
2    1   62
4    2   45
7    3   62

The function (the first argument of filter) is applied to each group (subframe), and the results include elements of the original DataFrame belonging to groups which evaluated to True.

Note: in 0.12 the ordering is different than in the original DataFrame, this was fixed in 0.13+:

In [21]: g.filter(lambda x: len(x) > 1)  # pandas 0.12
Out[21]: 
   pid  tag
1    1   45
4    2   45
2    1   62
7    3   62