如何解决我可以动态选择应用于熊猫重采样器对象的方法吗？
我正在尝试创建一个对<?php echo "ssqqss>>>";
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中的时间序列数据进行重新采样的函数。我想根据我要发送的数据类型指定发生聚合的类型（例如，对于某些数据，采用每个bin的总和是适当的，而对于其他数据，则需要采用均值，等等。）。例如这样的数据：
pandas我可以拥有这样的功能
import pandas as pd
import numpy as np
dr = pd.date_range('01-01-2020','01-03-2020',freq='1H')
df = pd.DataFrame(np.random.rand(len(dr)),index=dr)
对于少量的聚合方法来说，这很好，但是如果我想从all of the possible choices中进行选择，这似乎很乏味。
我希望使用def process(df,freq='3H',method='sum'):
r = df.resample(freq)
if method == 'sum':
r = r.sum()
elif method == 'mean':
r = r.mean()
#...
#more options
#...
return r
来实现something like this post（在“使其正常工作：泛化方法调用”下）。但是，我找不到执行此操作的方法：
getattr我了解了def process2(df,method='sum'):
r = df.resample(freq)
foo = getattr(r,method)
return r.foo()
#fails with:
#AttributeError: 'DatetimeIndexResampler' object has no attribute 'foo'
def process3(df,method)
return foo(r)
#fails with:
#TypeError: __init__() missing 1 required positional argument: 'obj'
失败的原因（调用process2寻找r.foo()的方法foo()，而不是变量r）。但是我不知道为什么foo会失败。
我知道另一种方法是将函数传递给参数process3，然后将method传递给apply上的那些函数。我的倾向是这样做效率会降低吗？而且它仍然不允许我直接访问内置的Resample方法。
是否有一种可行的，更简洁的方法来实现这一目标？谢谢！
解决方法
尝试.resample().apply(method)
但是除非您打算在函数内部计划更多的计算，否则仅硬编码此行可能会更容易。
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