I have one column in my Dataframe and I am trying to calculate the energy loss with formula. Problem is that I want to use only two valid rows each time where values are not NaN.
Energy is the input column and looking for something like loss column.
| Energy | loss |
|---|---|
| NaN | Nan |
| NaN | Nan |
| NaN | Nan |
| 4 | Nan |
| NaN | Nan |
| 3 | 1/2(4^2-3^2) |
| NaN | Nan |
| 11 | Nan |
| 3 | 1/2(3^2-11^2) |
| NaN | NaN |
| 14 | Nan |
I tried Lambda custom function but not able to send the next row.
>Solution :
Try something like this:
df = pd.DataFrame({'Energy':[4,None,3,None,11,3,None,14]})
energy = df.Energy.dropna()
def my_loss(series):
return 1/2*(series.iloc[0]**2-series.iloc[1]**2)
loss = energy.rolling(2).apply(my_loss)
df['loss'] = loss[1::2] # skip half of the results
Basically you apply your custom function in the rolling of the droped nan energy, and then merge it again with your df.