Python: using lambda function on Pandas Series, if.. else

Question

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:

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:

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:

criterion2 = testdata.map(lambda x: x if (x < 30 or x > 60) else 0) 
testdata[criterion2]

results in:

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.

Solution

Your

testdata.map(lambda x: x if (x < 30 or x > 60) else 0)

already returns what you want.