列中的值基于其他列中的值和 append 到 df - python

Question

I have a df that looks like this: df here

The column Count gives values that are either 0 or stretches of higher numbers separated by zeros eg 0,0,0,0,4,4,4,4,4,4,0,0,0,0,0,0,6,6,6,6,6,6,6,0,0,0,0.

I would like to sum the values of the column "angle_1frame_abs" for each stretch and add it as new column to the df eg

Count: 0,0,0,0,4,4,4,4,4,4,...

angle_1frame_abs: 2,1,3,4,2,2,2,3,4,3,...

new column: 10,10,10,10,16,16,16,16,16,16,...

Thank you all!

Answer 1

Seems what you need is to divide your df into segments with the same consecutive value of Count , and sum over the angle_1frame_abs within each segment, and copy the sum of each segment to each row of the segment.

In your case we cannot use Count as the key for groupby , so we need a new one:

new_key = (df['Count'].diff().abs() > 0).cumsum()

Using the new key, we can do the sum:

the_sum = df.groupby( new_key )['angle_1frame_abs'].sum()

And copy the summation results back to the table by the new key

df['NewColumn'] = new_key.map(the_sum)

Note that we use diff() to find out the boundary of segments, and used abs() > 0 to convert boundary values to True/False or 1/0 , then use cumsum to get the new key by leveraging the fact that the cumsum doesn't change outside the boundary (ie within the segment).

I tested my code using the following fake data

df = pd.DataFrame({
    'Count': [2,0,0,0,4,4,4,4,4,4,0,0,0,0,0,0,6,6,6,6,6,6,6,0,0,0,1], 
    'angle_1frame_abs': [np.nan,0,0,0,4,4,4,4,4,4,1,1,1,1,1,1,6,6,6,6,6,6,6,2,2,2,2],
})