Removing values >0 in data set

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I have a data set which is a list of lists, looking like this:

[[-0.519418066, -0.680905835],
[0.895518429, -0.654813183],
[0.092350219, 0.135117023],
[-0.299403315, -0.568458405],....]

its shape is (9760,) and I am trying to remove all entries where the value of the first number in each entry is greater than 0, so in this example the 2nd and 3rd entries would be removed to leave

[[-0.519418066, -0.680905835],
[-0.299403315, -0.568458405],....]

So far I have written:

for x in range(9670):
for j in filterfinal[j][0]:
    if filterfinal[j][0] > 0:
        np.delete(filterfinal[j])

this returns: TypeError: list indices must be integers or slices, not list

Thanks in advance for any help on this problem!

You can use numpy's boolean indexing:

>>> x = np.random.randn(10).reshape((5,2))
array([[-0.46490993,  0.09064271],
       [ 1.01982349, -0.46011639],
       [-0.40474591, -1.91849573],
       [-0.69098115,  0.19680831],
       [ 2.00139248, -1.94348869]])

>>> x[x[:,0] > 0]
array([[ 1.01982349, -0.46011639],
       [ 2.00139248, -1.94348869]])

Some explanation: x[:,0] selects the first column of your array. x > 0 will return an array of the same shape where each value is replaced by the result of the element-wise comparison (i.e., is the value > 0 or not?) So, x[:,0] > 0 will give you an array of shape (n,1) with True or False values depending on the first value of your row.

You can then pass this array of booleans as an index to your original array, where it will return you an array of only the indexes that are True. By passing in a boolean array of shape (n,1), you select per row.

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You are talking about "shape", so I assume that you are using numpy. Also, you are mentioning np in your example code, so you are able to apply element wise operations together with boolean indexing

array = np.array([[-0.519418066, -0.680905835],
                  [0.895518429, -0.654813183],
                  [0.092350219, 0.135117023],
                  [-0.299403315, -0.568458405]])

filtered = array[array[:, 0] < 0]

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Use a list comprehension:

lol = [[-0.519418066, -0.680905835],[0.895518429, -0.654813183],[0.092350219, 0.135117023],[-0.299403315, -0.568458405]]

filtered_lol = [l for l in lol if l[0] <= 0]

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You can use a list comprehension that unpacks the first item from each sub-list and retains only those with the first item <= 0 (assuming your list of lists is stored as variable l):

[l for a, _ in l if a <= 0]

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You can go through this in a for loop and making a new list without the positives like so:

new_list = []
for item in old_list:
    if item[0] < 0:
        new_list.append(item)

But I'd prefer to instead use the in built filter function if you are comfortable with it and do something like:

def is_negative(number):
    return number < 0

filtered_list = filter(is_negative, old_list)

This is similar to a list comprehension - or just using a for loop. However it returns a generator instead so you never have to hold two lists in memory making the code more efficient.

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Comments
  • what have you tried - the simple way to start is using for loops, nothing wrong with that. Also StackOverflow is not supposed to be a place to get code written for you - it's somewhere you bring code you wrote that doesn't work and ask for help fixing it.
  • sorry I havent been using stack overflow for very long I will edit with the code I have written