I'm have a 585L, 2L numpy array in Python. The data is organized like in this example.
0,0
1,0
2,1
3,0
4,0
5,1
...
I would like to create an array deleting all the lines where 0 is present on the seconds column. Thus, the final result pretended is:
2,1
5,1
I have read some related examples but I'm still struggling with this.
Since you mention your structure being a numpy array, rather than a list, I would use numpy logical indexing to select only the values you care for.
>>> import numpy as np
>>> x = [[0,0], [1,0], [2,1], [3,0], [4,0], [5,1]] # Create dummy list
>>> x = np.asarray(x) # Convert list to numpy array
>>> x[x[:, 1] != 0] # Select out items whose second column don't contain zeroes
array([[2, 1],
[5, 1]])
here is my answer if your list like this [[0,0],[2,1],[4,3],[2,0]] if your list structure isnt like this please tell me
my answer prints the list whose second column num dont equal to 0
print [x for x in your_list if x[1] != 0] #your_list is the variable of the list
You could use an list comprehension. These are described on the Python Data Structures page (Python 2, Python 3).
If your array is:
x = [[0,0],
[1,0],
[2,1],
[3,0],
[4,0],
[5,1]]
Then the following command
[y for y in x if y[1] != 0]
Would return the desired result of:
[[2, 1], [5, 1]]
Edit: I overlooked that it was a numpy array. Taking that into account, JoErNanO's answer is better.
