Python 计算列的唯一值并存储在新列中
打印df: 我想看看freq的每个值被存储了多少次。期望输出:Python 计算列的唯一值并存储在新列中,python,pandas,Python,Pandas,打印df: 我想看看freq的每个值被存储了多少次。期望输出: freq id 11 a 11 b 10 c 9 d 1 e 1 f 解决方案: data = [ [11, 'a'], [11, 'b'], [10, 'c'], [9, 'd'], [1, 'e'], [1, 'f'] ] column_name = ['freq', 'record
freq id
11 a
11 b
10 c
9 d
1 e
1 f
解决方案:
data = [
[11, 'a'],
[11, 'b'],
[10, 'c'],
[9, 'd'],
[1, 'e'],
[1, 'f']
]
column_name = ['freq', 'recordings']
df = pd.DataFrame(data, columns=column_name)
输出:
from collections import Counter
Counter(df.freq)
df.groupby'freq',如_index=False,sort=False.count?SC的一般规则是至少提供一个尝试,说明您试图如何解决您的问题。
data = [
[11, 'a'],
[11, 'b'],
[10, 'c'],
[9, 'd'],
[1, 'e'],
[1, 'f']
]
column_name = ['freq', 'recordings']
df = pd.DataFrame(data, columns=column_name)
from collections import Counter
Counter(df.freq)
Counter({11: 2, 10: 1, 9: 1, 1: 2})