添加两个带有NaN的序列 [英] Adding two Series with NaNs

问题描述

我正在通过"Python进行数据分析"，但我不了解特定的功能.添加两个熊猫系列对象将自动对齐索引数据，但是如果一个对象不包含该索引，则将其返回为NaN.例如书中的内容:

I'm working through the "Python For Data Analysis" and I don't understand a particular functionality. Adding two pandas series objects will automatically align the indexed data but if one object does not contain that index it is returned as NaN. For example from book:

a = Series([35000,71000,16000,5000],index=['Ohio','Texas','Oregon','Utah'])
b = Series([NaN,71000,16000,35000],index=['California', 'Texas', 'Oregon', 'Ohio'])

结果:

    In [63]: a
    Out[63]: Ohio          35000
             Texas         71000
             Oregon        16000
             Utah           5000
    In [64]: b
    Out[64]: California      NaN
             Texas         71000
             Oregon        16000
             Ohio          35000

当我将它们加在一起时，我得到了...

When I add them together I get this...

    In [65]: a+b
    Out[65]: California       NaN
             Ohio           70000
             Oregon         32000
             Texas         142000
             Utah             NaN

那么，为什么犹他州的价值是NaN而不是500?看来500 + NaN = 500.是什么赋予了?我丢失了一些东西，请解释.

So why is the Utah value NaN and not 500? It seems that 500+NaN=500. What gives? I'm missing something, please explain.

更新:

    In [92]: # fill NaN with zero
             b = b.fillna(0)
             b
    Out[92]: California        0
             Texas         71000
             Oregon        16000
             Ohio          35000

    In [93]: a
    Out[93]: Ohio      35000
             Texas     71000
             Oregon    16000
             Utah       5000

    In [94]: # a is still good
             a+b
    Out[94]: California       NaN
             Ohio           70000
             Oregon         32000
             Texas         142000 
             Utah             NaN

推荐答案

Pandas不假定500 + NaN = 500，但是很容易要求它这样做:a.add(b, fill_value=0)

Pandas does not assume that 500+NaN=500, but it is easy to ask it to do that: a.add(b, fill_value=0)

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