Keras Deep Learning Cookbook

 Load the dataset

1. First, we define a parser to convert YY to YYYY:

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

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

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

3. Summarize the first few rows using the following code:

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

4. Let's print the line plot using the following code:

series.plot()pyplot.show()

The output of the line plot is as follows: