Python 对 Pandas 数据框中的所有值求和的最佳方法是什么？
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What's the best way to sum all values in a Pandas dataframe?
提问by Bill
I figured out these two methods. Is there a better one?
我想出了这两种方法。有没有更好的？
>>> import pandas as pd
>>> df = pd.DataFrame({'A': [5, 6, 7], 'B': [7, 8, 9]})
>>> print df.sum().sum()
42
>>> print df.values.sum()
42
Just want to make sure I'm not missing something more obvious.
只是想确保我没有遗漏更明显的东西。
回答by piRSquared
Updated for Pandas 0.24+
为 Pandas 0.24+ 更新
df.to_numpy().sum()
Prior to Pandas 0.24+
在 Pandas 0.24+ 之前
df.values
Is the underlying numpy array
是底层的numpy数组
df.values.sum()
Is the numpy sum method and is faster
是 numpy sum 方法并且速度更快
回答by Raven
Adding some numbers to support this:
添加一些数字来支持这一点：
import numpy as np, pandas as pd
import timeit
df = pd.DataFrame(np.arange(int(1e6)).reshape(500000, 2), columns=list("ab"))
def pandas_test():
return df['a'].sum()
def numpy_test():
return df['a'].to_numpy().sum()
timeit.timeit(numpy_test, number=1000) # 0.5032469799989485
timeit.timeit(pandas_test, number=1000) # 0.6035906639990571
So we get a 20% performance on my machine just for Series summations!
所以我们在我的机器上获得了 20% 的性能，仅用于系列求和！
