有没有一种更简单的方法来用python进行分组和计数？

Question

I am grouping and counting a set of data.

df = pd.DataFrame({'key': ['A', 'B', 'A'],
                   'data': np.ones(3,)})
df.groupby('key').count()

outputs

    data
key 
A   2
B   1

The piece of code above works though, I wonder if there is a simpler one.

'data': np.ones(3,) seems to be a placeholder and indispensable.

pd.DataFrame(['A', 'B', 'A']).groupby(0).count()

outputs

A
B

My question is, is there a simpler way to do this, produce the count of 'A' and 'B' respectively, without something like 'data': np.ones(3,) ?

It doesn't have to be a pandas method, numpy or python native function are also appreciated.

Answer 1

Use a Series instead.

>>> import pandas as pd
>>> 
>>> data = ['A', 'A', 'A', 'B', 'C', 'C', 'D', 'D', 'D', 'D', 'D']
>>> 
>>> pd.Series(data).value_counts()
D    5
A    3
C    2
B    1
dtype: int64

Answer 2

Use a defaultdict :

from collections import defaultdict

data = ['A', 'A', 'B', 'A', 'C', 'C', 'A']

d = defaultdict(int)

for element in data:
    d[element] += 1

d  # output: defaultdict(int, {'A': 4, 'B': 1, 'C': 2})

Answer 3

There's not any grouping , just counting, so you can use

from collections import Counter
counter(['A', 'B', 'A'])