You can store the DataFrames generated in the loop in a list and concatenate them with features
once you finish the loop.
In other words, replace the loop:
for count in range(num_samples):
# .... code to produce `input_vars`
features = features.append(input_vars) # remove this `DataFrame.append`
with the one below:
tmp = [] # initialize list
for count in range(num_samples):
# .... code to produce `input_vars`
tmp.append(input_vars) # append to the list, (not DF)
features = pd.concat(tmp) # concatenate after loop
You can certainly concatenate in the loop but it’s more efficient to do it only once.