Python：在 Pandas 系列上使用 lambda 函数，如果……否则
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Python: using lambda function on Pandas Series, if.. else
提问by Quantatia
I am trying to apply a filter on a series of values stored in a pandas series object. The desired output is the value itself if it meets the criterion otherwise zero. I can only get it to half work:
我正在尝试对存储在 Pandas 系列对象中的一系列值应用过滤器。如果满足标准，则所需的输出是值本身，否则为零。我只能让它工作一半：
criterion = testdata.map(lambda x: x < 30 or x > 60)
testdata[criterion] =
Date
2015-01-05 62.358615
2015-01-06 64.349507
2015-01-13 61.726110
2015-01-14 63.574864
2015-01-15 66.020421
2015-01-16 63.041819
2015-01-20 61.458298
Name: rsi, dtype: float64
where:
在哪里：
testdata =
Date
2014-12-29 45.821073
2014-12-30 48.946830
2014-12-31 57.737593
2015-01-02 55.424047
2015-01-05 62.358615
2015-01-06 64.349507
2015-01-07 59.452935
2015-01-08 51.182115
2015-01-09 55.044419
2015-01-12 59.365017
2015-01-13 61.726110
2015-01-14 63.574864
2015-01-15 66.020421
2015-01-16 63.041819
2015-01-20 61.458298
2015-01-21 54.432635
2015-01-22 46.985675
2015-01-23 49.740981
2015-01-26 45.102370
2015-01-27 49.800855
Name: rsi, dtype: float64
but the following gives me quite a different result. Clearly I am not understanding what is happening in the background to produce this result:
但以下给了我完全不同的结果。显然，我不明白在后台发生了什么来产生这个结果：
criterion2 = testdata.map(lambda x: x if (x < 30 or x > 60) else 0)
testdata[criterion2]
results in:
结果是：
rsi
0.000000 NaN
0.000000 NaN
0.000000 NaN
0.000000 NaN
62.358615 NaN
64.349507 NaN
0.000000 NaN
0.000000 NaN
0.000000 NaN
0.000000 NaN
61.726110 NaN
63.574864 NaN
66.020421 NaN
63.041819 NaN
61.458298 NaN
0.000000 NaN
0.000000 NaN
0.000000 NaN
0.000000 NaN
0.000000 NaN
Name: rsi, dtype: float64
I am looking for same formatting as the first output except with zeros for where the conditions are not met. Please help.
我正在寻找与第一个输出相同的格式，除了不满足条件的零。请帮忙。
回答by eumiro
Your
您的
testdata.map(lambda x: x if (x < 30 or x > 60) else 0)
already returns what you want.
已经返回你想要的。
