如何根据列的百分位数从DataFrame中采样？

给定这样的数据集：

import pandas as pd
rows = [{'key': 'ABC', 'freq': 100}, {'key': 'DEF', 'freq': 60},
{'key': 'GHI', 'freq': 50}, {'key': 'JKL', 'freq': 40},
{'key': 'MNO', 'freq': 13}, {'key': 'PQR', 'freq': 11},
{'key': 'STU', 'freq': 10}, {'key': 'VWX', 'freq': 10},
{'key': 'YZZ', 'freq': 3}, {'key': 'WHYQ', 'freq': 3},
{'key': 'HOWEE', 'freq': 2}, {'key': 'DUH', 'freq': 1},
{'key': 'HAHA', 'freq': 1}]
df = pd.DataFrame(rows)
df['percent'] = df['freq'] / sum(df['freq'])


[出去]：

key freq percent
0 ABC 100 0.328947
1 DEF 60 0.197368
2 GHI 50 0.164474
3 JKL 40 0.131579
4 MNO 13 0.042763
5 PQR 11 0.036184
6 STU 10 0.032895
7 VWX 10 0.032895
8 YZZ 3 0.009868
9 WHYQ 3 0.009868
10 HOWEE 2 0.006579
11 DUH 1 0.003289
12 HAHA 1 0.003289


目标是

1. 从频率的前 50-100 个百分位数中选择 1 个示例


2. 从 10-50 个百分位数中选择 2 个示例，然后


3. 从 <10 个百分位数中选择 4 个示例

在这种情况下，合适的答案是：

1. 从中选择 1 ['ABC', 'DEF']


2. 从中选择 2 ['GHI', 'JKL', 'MNO', 'PQR']


3. 从中选出 4 个 ['VWX', 'STU', 'YZZ', 'WHYQ', 'HOWEE', 'HAHA', 'DUH']

我试过这个：

import random
import pandas as pd
rows = [{'key': 'ABC', 'freq': 100}, {'key': 'DEF', 'freq': 60},
{'key': 'GHI', 'freq': 50}, {'key': 'JKL', 'freq': 40},
{'key': 'MNO', 'freq': 13}, {'key': 'PQR', 'freq': 11},
{'key': 'STU', 'freq': 10}, {'key': 'VWX', 'freq': 10},
{'key': 'YZZ', 'freq': 3}, {'key': 'WHYQ', 'freq': 3},
{'key': 'HOWEE', 'freq': 2}, {'key': 'DUH', 'freq': 1},
{'key': 'HAHA', 'freq': 1}]
df = pd.DataFrame(rows)
df['percent'] = df['freq'] / sum(df['freq'])
bin_50_100 = []
bin_10_50 = []
bin_10 = []
total_percent = 1.0
for idx, row in df.sort_values(by=['freq', 'key'], ascending=False).iterrows():
if total_percent > 0.5:
bin_50_100.append(row['key'])
elif 0.1 bin_10_50.append(row['key'])
else:
bin_10.append(row['key'])
total_percent -= row['percent']
print(random.sample(bin_50_100, 1))
print(random.sample(bin_10_50, 2))
print(random.sample(bin_10, 4))


[出去]：

['DEF']
['MNO', 'PQR']
['HOWEE', 'WHYQ', 'HAHA', 'DUH']


但是有没有更简单的方法来解决这个问题？

回答