收集通过随机抽样其他数据帧构建的数据帧的摘要统计信息

Question

我的目标是通过从其他数据帧中随机抽样来构建一个数据帧，收集新数据帧的汇总统计信息，然后将这些统计信息附加到列表中。理想情况下，我可以反复n次地遍历这个过程（例如bootstrap）。你知道吗

dfposlist = [OFdf, Firstdf, Seconddf, Thirddf, CFdf, RFdf, Cdf, SSdf]

OFdf.head()
    playerID    OPW         POS salary
87  bondsba01   62.061290   OF  8541667
785 ramirma02   35.785630   OF  13050000
966 walkela01   30.644305   OF  6050000
859 sheffga01   29.090699   OF  9916667
357 gilesbr02   28.160054   OF  7666666

列表中的所有数据帧都有相同的头。我想做的事情是这样的：

teamdist = []
for df in dfposlist:
    frames = [df.sample(n=1)]
team = pd.concat(frames)

teamopw = team['OPW'].sum()
teamsal = team['salary'].sum()
teamplayers = team['playerID'].tolist()

teamdic = {'Salary':teamsal, 'OPW':teamopw, 'Players':teamplayers}
teamdist.append(teamdic)

我想要的输出是这样的：

teamdist = [{'Salary':4900000, 'OPW':78.452, 'Players':[bondsba01, etc, etc]}]

但是由于某些原因，所有像teamopw = team['OPW'].sum()这样的求和操作都不能按我所希望的方式工作，只返回team['OPW']中的元素

print(teamopw)
0.17118131814601256
38.10700006434629
1.5699939126695253
32.9068837019903
16.990760776263674
18.22428871113601
13.447706356730897

有什么建议可以让它工作吗？谢谢！你知道吗

编辑：工作方案如下。我不确定这是不是最适合Python的方式，但它是有效的。你知道吗

teamdist = []
team = pd.concat([df.sample(n=1) for df in dfposlist])

teamopw = team[['OPW']].values.sum()
teamsal = team[['salary']].values.sum()
teamplayers = team['playerID'].tolist()

teamdic = {'Salary':teamsal, 'OPW':teamopw, 'Players':teamplayers}
teamdist.append(teamdic)

Answer 1

此处（随机数据）：

import pandas as pd
import numpy as np

dfposlist = dict(zip(range(10),
                     [pd.DataFrame(np.random.randn(10, 5),
                                   columns=list('abcde'))
                     for i in range(10)]))
for df in dfposlist.values():
    df['f'] = list('qrstuvwxyz')

teamdist = []
team = pd.concat([df.sample(n=1) for df in dfposlist.values()])
print(team.info())

teamdic = team[['a', 'c', 'e']].sum().to_dict()
teamdic['f'] = team['f'].tolist()
teamdist.append(teamdic)
print(teamdist)

# Output:
## team.info():
<class 'pandas.core.frame.DataFrame'>
Int64Index: 10 entries, 1 to 6
Data columns (total 6 columns):
a    10 non-null float64
b    10 non-null float64
c    10 non-null float64
d    10 non-null float64
e    10 non-null float64
f    10 non-null object
dtypes: float64(5), object(1)
memory usage: 560.0+ bytes
None

## teamdist:
[{'a': -3.5380097363724601,
  'c': 2.0951152809401776,
  'e': 3.1439230427971863,
  'f': ['r', 'w', 'z', 'v', 'x', 'q', 't', 'q', 'v', 'w']}]