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

Issue

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?

Solution

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]

Answered By - jpp