Quick comment on Chapter 10 #7
Description
In Concept01_timeseries_data.ipynb in Chapter 10, I believe you can simplify and speed up the following code:
def split_data(data, percent_train=0.80):
num_rows = len(data)
train_data, test_data = [], []
for idx, row in enumerate(data):
if idx < num_rows * percent_train:
train_data.append(row)
else:
test_data.append(row)
return train_data, test_data
as follows:
def split_data(data, percent_train=0.80):
num_rows = len(data)*percent_train
return data[:num_rows], data[num_rows:]