code

#Parsing datetime
#exploring the length of date objects
lengths = data["Date"].str.len()
lengths.value_counts()
data['Date']= pd.to_datetime(data["Date"])
#Creating a collumn of year
data['year'] = data.Date.dt.year
# function to encode datetime into cyclic parameters. 
#As I am planning to use this data in a neural network I prefer the months and days in a cyclic continuous feature.
def encode(data, col, max_val):
    data[col + '_sin'] = np.sin(2 * np.pi * data[col]/max_val)
    data[col + '_cos'] = np.cos(2 * np.pi * data[col]/max_val)
    return data
data['month'] = data.Date.dt.month
data = encode(data, 'month', 12)
data['day'] = data.Date.dt.day
data = encode(data, 'day', 31)
data.head()