Pandas：如何在组内进行值计数

Question

I have the following dataframe. I want to group by a and b first. Within each group, I need to do a value count based on c and only pick the one with most counts. If there are more than one c values for one group with the most counts, just pick any one.

a    b    c
1    1    x
1    1    y
1    1    y
1    2    y
1    2    y
1    2    z
2    1    z
2    1    z
2    1    a
2    1    a

The expected result would be

a    b    c
1    1    y
1    2    y
2    1    z

What is the right way to do it? It would be even better if I can print out each group with c's value counts sorted as an intermediate step.

Answer 1

group the original dataframe by ['a', 'b'] and get the .max() should work

df.groupby(['a', 'b'])['c'].max()

you can also aggregate 'count' and 'max' values

df.groupby(['a', 'b'])['c'].agg({'max': max, 'count': 'count'}).reset_index()

Answer 2

You are looking for .value_counts() :

df.groupby(['a', 'b'])['c'].value_counts()

a  b  c
1  1  y    2
      x    1
   2  y    2
      z    1
2  1  a    2
      z    2
Name: c, dtype: int64

Answer 3

Try:

df=df.groupby(["a", "b", "c"])["c"].count().sort_values(ascending=False).reset_index(name="dropme").drop_duplicates(subset=["a", "b"], keep="first").drop("dropme", axis=1)

Outputs:

   a  b  c
0  2  1  z
2  1  2  y
3  1  1  y