[Solved] Detect sign changes in an array [closed]

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This is a simple code that resolve your problem/exemple:

l = [ 1, 2, 6, -3, -2, -5, 6, 7, 1, -1, -3]
for i in range(0, len(l)-1):
    p = l[i] * l[i+1]
    if p > 0:
        print('ok')
    elif l[i+1] < 0:
        print('sell')
    else:
        print('buy')

And if you want a new column in your dataframe, this is an example for you:

d = {'col1': range(11), 'col2': [ 1, 2, 6, -3, -2, -5, 6, 7, 1, -1, -3]}
df = pd.DataFrame(data=d)
df['shift_col'] = df.col2.shift(-1)

df
col1    col2    shift_col
0   0   1   2.0
1   1   2   6.0
2   2   6   -3.0
3   3   -3  -2.0
4   4   -2  -5.0
5   5   -5  6.0
6   6   6   7.0
7   7   7   1.0
8   8   1   -1.0
9   9   -1  -3.0
10  10  -3  NaN

and this is a our simple function in the previous example:

def compare(line):
    p = line.col2 * line.shift_col
    if p > 0:
        return 'ok'
    elif line.shift_col < 0:
        return 'sell'
    else:
        return 'buy'
        
df['order'] = df.apply(compare, axis=1)

Finaly, this will be the result:

col1    col2    shift_col   order
0   0   1   2.0 ok
1   1   2   6.0 ok
2   2   6   -3.0    sell
3   3   -3  -2.0    ok
4   4   -2  -5.0    ok
5   5   -5  6.0 buy
6   6   6   7.0 ok
7   7   7   1.0 ok
8   8   1   -1.0    sell
9   9   -1  -3.0    ok
10  10  -3  NaN buy

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solved Detect sign changes in an array [closed]