What is the inverse operation of np.log() and np.diff()?

Question

I have used the statement dataTrain = np.log(mdataTrain).diff() in my program. I want to reverse the effects of the statement. How can it be done in Python?

Answer 1

The reverse will involve taking the cumulative sum and then the exponential. Since pd.Series.diff loses information, namely the first value in a series, you will need to store and reuse this data:

np.random.seed(0)

s = pd.Series(np.random.random(10))

print(s.values)

# [ 0.5488135   0.71518937  0.60276338  0.54488318  0.4236548   0.64589411
#   0.43758721  0.891773    0.96366276  0.38344152]

t = np.log(s).diff()
t.iat[0] = np.log(s.iat[0])
res = np.exp(t.cumsum())

print(res.values)

# [ 0.5488135   0.71518937  0.60276338  0.54488318  0.4236548   0.64589411
#   0.43758721  0.891773    0.96366276  0.38344152]