How to loop through indices in Python?

Question

I'm trying to run a for loop in python that looks like this:

data = np.linspace(0.5, 50, 10)

output = []
for i in data:
  x = data[i] - data[i+1]
  output.append(data)

but I keep getting the error:

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

For reference I want the code to do the following:

x1 = x = data[0] - data[1]
x2 = x = data[1] - data[2] ...

and output it to the list.

Any help would be really appreciated

for i in data loops over the elements. You probably want for i,el in enumerate(data) — code11
– code11, Commented Mar 10, 2022 at 21:16

hpaulj · Accepted Answer · 2022-03-10 22:05:16Z

5

There are several things going on here:

You are iterating over the actual elements, not their index. To iterate over the indexes you can do something like this for index in range(len(data) - 1)).
As shown above, you want to iterrate until len(data) - 1 in order to avoid getting out of bounds.
It seems that you are calculating x but eventually append data instead.
To achive readable code, it is important to give variables meaningful names (i and x are not meaningfull).

data = np.linspace(0.5, 50, 10)

output = []
for index in range(len(data) - 1):
  result = data[index] - data[index + 1]
  output.append(result)

edited Mar 10, 2022 at 22:05

hpaulj

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answered Mar 10, 2022 at 21:22

user3980558

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user17242583 · Accepted Answer · 2022-03-10 21:22:32Z

0

for i in data: loops directly over data, thus i will be each element in data, not its index. If you need the index, use enumerate():

output = []
for i, elem in enumerate(data):
  x = data[i] - data[i+1]
  output.append(data)

However, that won't work, due to an out-of-bounds error that will occur at the very end. Instead, you can use built-in numpy functionality:

output = data[:-1] - data[1:]
print(output)

Output:

array([-5.5, -5.5, -5.5, -5.5, -5.5, -5.5, -5.5, -5.5, -5.5])

Or possible solutions:

np.full(9, -5.5)

np.ones(9) * -5.5

answered Mar 10, 2022 at 21:22

user17242583

Comments

mozway · Accepted Answer · 2022-03-10 21:48:21Z

0

IIUC, you want to calculate the successive differences, but reversed. You can use numpy.diff

np.diff(data[::-1])[::-1]

Other option, shift the array by taking a slice of all but the last/first element and subtract:

data[:-1] - data[1:]

Output: array([-5.5, -5.5, -5.5, -5.5, -5.5, -5.5, -5.5, -5.5, -5.5])

answered Mar 10, 2022 at 21:48

mozway

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