Creating a 2D python array to store data

Question

Looking for a way to store this code in a 2D array in python. I've tried making a 1D array and then turning it into a 2D array but my code is still cumbersome and not working. The gap between 4 and 6 is not a typo. Any help would be greatly appreciated.

recno1inds11 = nonzero(data11[:,1]==no1)[0]
recno2inds11 = nonzero(data11[:,1]==no2)[0]
recno3inds11 = nonzero(data11[:,1]==no3)[0]
recno4inds11 = nonzero(data11[:,1]==no4)[0]

recno6inds11 = nonzero(data11[:,1]==no6)[0]
recno7inds11 = nonzero(data11[:,1]==no7)[0]
recno8inds11 = nonzero(data11[:,1]==no8)[0]
recno9inds11 = nonzero(data11[:,1]==no9)[0]
recno10inds11 = nonzero(data11[:,1]==no10)[0]
recno11inds11 = nonzero(data11[:,1]==no11)[0]
recno12inds11 = nonzero(data11[:,1]==no12)[0]
recno13inds11 = nonzero(data11[:,1]==no13)[0]
recno14inds11 = nonzero(data11[:,1]==no14)[0]
recno15inds11 = nonzero(data11[:,1]==no15)[0] 
recno16inds11 = nonzero(data11[:,1]==no16)[0]
recno17inds11 = nonzero(data11[:,1]==no17)[0]
recno18inds11 = nonzero(data11[:,1]==no18)[0]
recno19inds11 = nonzero(data11[:,1]==no19)[0]
recno20inds11 = nonzero(data11[:,1]==no20)[0]
recno21inds11 = nonzero(data11[:,1]==no21)[0] 
recno22inds11 = nonzero(data11[:,1]==no22)[0]
recno23inds11 = nonzero(data11[:,1]==no23)[0]
recno24inds11 = nonzero(data11[:,1]==no24)[0]
recno25inds11 = nonzero(data11[:,1]==no25)[0]
recno26inds11 = nonzero(data11[:,1]==no26)[0]
recno27inds11 = nonzero(data11[:,1]==no27)[0]
recno28inds11 = nonzero(data11[:,1]==no28)[0]
recno29inds11 = nonzero(data11[:,1]==no29)[0]
recno30inds11 = nonzero(data11[:,1]==no30)[0]

abarnert · Accepted Answer · 2013-08-21 00:35:50Z

Normally, you don't want to have 30 separate variables like this, you want to have an array of 30 values.

And if you had that, this would be a one-liner; you could need to transpose the right-hand array into the second axis, then use the == operator.

>>> data11 = np.array([[1,2,3],[4,5,6],[7,8,9]])
>>> data11[:,1]
array([2, 5, 8])
>>> no1to5 = np.array([1, 2, 3, 4, 5])
>>> data11[:,1] == no1to5.reshape((5,1))
array([[False, False, False],
       [ True, False, False],
       [False, False, False],
       [False, False, False],
       [False,  True, False]], dtype=bool)

Of course you can also apply nonzero, grab the first axis, … whatever you want to do, you can vectorize it as long as you have a vector in the first place, instead of a big collection of separate values that are only related by the meta-information in the variable names you happen to have bound them to.

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