Change function to match for loop

Question

I am trying to re-write this for loop into a function to make it applicable to different time series. It is pretty straightforward but for some reason there are errors with the function. The goal is to subtract the current value with its preceding one:

# time series
p = np.array([2,5,7,23,78,2,14,7,3])

diff = [np.float(p[0])]
one_year = 1
for i in range(1,len(p)):
    value = p[i] - p[i - one_year] 
    diff.append(value)

print(diff)
[2.0, 3, 2, 16, 55, -76, 12, -7, -4]

This is the function I want to make, and I keep getting this error about appending values:

def differing(data,time_interval):
    diff = [data[0]]
    for i in range(1,len(data)):
        value = data[i] - data[i - time_interval] 
        diff = diff.append(value)
    return diff

test = differing(p,1)

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-410-5287a79bf3fd> in <module>
----> 1 test = differing(p,1)

<ipython-input-391-8787130f5f66> in differing(data, time_interval)
      3     for i in range(1,len(data)):
      4         value = data[i] - data[i - time_interval]
----> 5         diff = diff.append(value)
      6         #output = np.array(diff.append(value))
      7     return diff

AttributeError: 'NoneType' object has no attribute 'append'

How do I fix this?

Asked By: wabash

||

Source

Answer 1

append doesn’t return the modified list, it modifies it in place. This means that

diff = diff.append(value)

will be assigning None to diff, causing your problem.

You just need

diff.append(value)

as you had in the original loop.

Answered By: Kemp

Change function to match for loop

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