python pandas-在您所在的行上方添加一列的值

Question

I have a dataframe that looks like this (but longer):

OnsetTime  OffsetTime     OnSec    OffSec  RTsec    TrialDur  
36163       38165         36.163   38.165  0.000     2.002   
39157       41152         39.157   41.152  0.605     1.995   
42152       44155         42.152   44.155  0.509     2.003   
45164       47153         45.164   47.153  0.503     1.989   
48159       50161         48.159   50.161  0.558     2.002   

I want to make a new column that would, for each row, add the values in the TrialDur column above but not including it. and it would need to add on .001 of a second, since TrialDur is trial duration, and I want my new column to indicate the time when a new stimulus came on the screen. so it would look like this:

NewVar
0
2.003
3.999
6.003
7.993
9.996

The first row would be 0 since the first stimulus started at timepoint 0. The second would be right after the first trial ended (based on the TrialDur variable), at 2.003 seconds, and so on.

How do I make a variable that adds the values above it in each row?

Answer 1

You can use cumsum to compute the cumulative sum (add 0.001 before that), then shift that column by 1, finally set the first row to be 0.

df['NewVar'] = (df.TrialDur + 0.001).cumsum()
df.loc[df.index[-1]+1, 'NewVar'] = 0
df['NewVar'] = df.NewVar.shift(1)
df.loc[0, 'NewVar'] = 0

Because NewVar has one more row, so I first add one empty row at the end, and I assume that the index is in numerical order.