循环嵌套问题值n

Question

我有一个dataframe，它有两个相关的列（实际上有>；2，但不认为这很重要），其中一个列中有重复的列。你知道吗

重复项在列HAB_slice['Radial Position']中，增量为0.1。你知道吗

理想情况下，我想说，如果HAB_slice['Radial Position']中的两个值彼此相等，求出它们之间的绝对值差，并将它们相加到一个运行总数中。你知道吗

当前代码如下所示：

    possible_pos = np.linspace(0, 1, 1 / stepsize+1) 
    center_sum = 0
    for i in range(0, len(possible_pos)): 
        temp = HAB_slice[HAB_slice['Radial Position']==possible_pos[i]]
        if len(temp) == 2:
            center_sum += np.abs(temp['I'].diff().values[1])
    print center_sum

虽然它确实返回一个值并且不会抛出错误，但center\u sum的值与我手动计算时的值不同。我认为这只是一些错误的筑巢，但我是相当新的循环和不太确定。你知道吗

错误示例：以下数据在该代码中产生一个中心和=0，但如果手动计算径向位置相等时I中的绝对值差，则等于0.0045878。你知道吗

I           Radial Position
0.14289522  1
0.14298554  0.9
0.1430356   0.8
0.1430454   0.7
0.1430552   0.6
0.14266456  0.5
0.14227392  0.4
0.14234106  0.3
0.14286598  0.2
0.1433909   0.1
0.14309062  0
0.14279034  0.1
0.14271344  0.2
0.14285992  0.3
0.1430064   0.4
0.14327248  0.5
0.14353856  0.6
0.14356664  0.7
0.14335672  0.8
0.1431468   0.9
0.14338368  1

编辑：我已经用示例代码简化了一些东西，试图让它工作起来。你知道吗

test1 = [[0.14309062,0],[0.1433909,0.1], [0.14286598,0.2], [0.14234106,0.3], 
[0.14279034,0.1], [0.14271344,0.2], [0.14285992,0.3]]
'''
test2 = [[0.14289522,1],[0.14298554,0.9],[0.1430356,0.8],[0.1430454,0.7],
[0.1430552,0.6],[0.14266456,0.5],[0.14227392,0.4],[0.14234106,0.3],
[0.14286598,0.2],[0.1433909,0.1],[0.14309062,0],[0.14279034,0.1],
[0.14271344,0.2],[0.14285992,0.3],[0.1430064,0.4],[0.14327248,0.5],
[0.14353856,0.6],[0.14356664,0.7],[0.14335672,0.8],[0.1431468,0.9],
[0.14338368,1]]
'''
stepsize = 0.1
possible_pos = np.linspace(0, 1, 1 / stepsize+1) 
HAB_slice = pd.DataFrame(test1)
HAB_slice.columns = ['I', 'Radial Position']

Answer 1

请尝试以下代码。应该有用。你知道吗

possible_pos = np.linspace(0, 1, 1 / stepsize+1) 
center_sum = 0

for i in range(0, len(possible_pos)):

    # retriving index position of the step value 
    indices = [i for i, x in enumerate(HAB_slice['Radial Position']) if x == possible_pos[i]]

    # if multiple value exist for the postion
    if len(indices) > 1:
        values = [x for i, x in enumerate(HAB_slice['I']) if i in indices]
        center_sum += np.abs(np.diff(values))

    # if single value exist for the position
    elif len(indices) == 1:
        center_sum += HAB_slice['I'][indices[0]]

    # if no value exist for the position
    else: continue  

print center_sum