Keras Deep Learning Cookbook

Loading the dataset

1. We define a parser to convert YY to YYYY, shown as follow:

def parser(x):     return datetime.strptime('200' + x, '%Y-%m')

2. Next, call the read_csv function of pandas to load a .csv file into a pandas DataFrame.

Notice the data parser being used is the function defined previously.

3. The next read_csv function is called in the next code:

series = read_csv('sales-of-shampoo-over-a-three-ye.csv', header=0, parse_dates=[0], index_col=0,                         squeeze=True, date_parser=parser)

4. Once the series is loaded, let's summarize the first few rows:

print(series.head())

The output of the preceding code is as follows:

Month2001-01-01 266.02001-02-01 145.92001-03-01 183.12001-04-01 119.32001-05-01 180.3

5. Next, let's print the line plot using ...