I am trying to assign new values to an array based on whether or not the stored value is <3. Coming from an R background this is how I would do it, but this gives me a syntax error in Python. What am I doing wrong, and what is the Python approach?
eurx=[1,2,3,4,5,6,7,'a',8]
sma50=3
tw=eurx
tw[eurx<sma50]=-1
tw[eurx>=sma50]=1
tw[(tw!=1)||(tw!=-1)]=0
print(tw)
GOAL:
-1
-1
1
1
1
1
1
0
1
This is "too much R". A pythonic way would be to use functional filtering:
>>> map(lambda i: -2*int(i<sma50)+1 if type(i) == int else 0, eurx)
[-1, -1, 1, 1, 1, 1, 1, 0, 1]
Or just a simple for-loop with a few ifs:
>>> for i in eurx:
... if type(i) != int:
... print 0
... else:
... print -2*int(i<sma50)+1
...
-1
-1
1
1
1
1
1
0
1
In general: don't try to guess the syntax. It's very simple, just read through some tutorials (e.g. https://docs.python.org/3/tutorial/introduction.html#first-steps-towards-programming)
Edit: the int conversion hack works as follows: you know you can convert bool to int, right?
>>> int(True)
1
>>> int(False)
0
If i<sma50 evaluates to True, int(i<sma50) will be 1. So yor numbers now are converted to ones if i is smaller than sma50 and to zeros otherwise. But apparently you want the values (-1, 1) instead of (1, 0). Just apply the transform -2x+1 and you're done!
if to get the same result without the bool-to-int conversion hack.
map with a lambda, you might as well use a list comprehension. The second example doesn't return or define anything, it just prints elements.Your desired syntax is pretty close to what you'd write in numpy.
The heterogeneous list doesn't make it easy, but here's an example:
>>> import numpy as np
>>> eurx=[1,2,3,4,5,6,7,'a',8]
>>> sma50 = 3
>>> tw = np.array([i if isinstance(i, int) else np.nan for i in eurx])
>>> tw
array([ 1., 2., 3., 4., 5., 6., 7., nan, 8.])
>>> tw[tw < sma50] = -1
__main__:1: RuntimeWarning: invalid value encountered in less
>>> tw[tw >= sma50] = 1
__main__:1: RuntimeWarning: invalid value encountered in greater_equal
>>> tw
array([ -1., -1., 1., 1., 1., 1., 1., nan, 1.])
>>> tw[np.isnan(tw)] = 0
>>> tw
array([-1., -1., 1., 1., 1., 1., 1., 0., 1.])
tw=eurx