熊猫 - 按组成员编号排序

Question

When faced with large numbers of groups, any graph you might make is apt to be useless due to having too many lines and an unreadable legend. In these cases, being able to find the groups that have the most and least information in them is very useful. However, while x.size() tells you the group membership (after having used groupby ), there is no way I can find to re-sort the dataframe using this information, so that you can then use limiting looping to only graph the first x groups.

Answer 1

You can use transform to get the counts and sort on that column:

df = pd.DataFrame({'A': list('aabababc'), 'B': np.arange(8)})
df
Out: 
   A  B
0  a  0
1  a  1
2  b  2
3  a  3
4  b  4
5  a  5
6  b  6
7  c  7

---

df['counts'] = df.groupby('A').transform('count')
df
Out: 
   A  B  counts
0  a  0       4
1  a  1       4
2  b  2       3
3  a  3       4
4  b  4       3
5  a  5       4
6  b  6       3
7  c  7       1

Now you can sort by counts :

df.sort_values('counts')
Out: 
   A  B  counts
7  c  7       1
2  b  2       3
4  b  4       3
6  b  6       3
0  a  0       4
1  a  1       4
3  a  3       4
5  a  5       4

In one line:

df.assign(counts = df.groupby('A').transform('count')).sort_values('counts')