g6_intro.py

from datetime import datetime, timedelta,date
import pandas as pd
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from __future__ import division

import warnings
warnings.filterwarnings("ignore")

import plotly.plotly as py
import plotly.offline as pyoff
import plotly.graph_objs as go

#import Keras
import keras
from keras.layers import Dense
from keras.models import Sequential
from keras.optimizers import Adam 
from keras.callbacks import EarlyStopping
from keras.utils import np_utils
from keras.layers import LSTM
from sklearn.model_selection import KFold, cross_val_score, train_test_split

#initiate plotly
pyoff.init_notebook_mode()

#read the data in csv
df_sales = pd.read_csv('sales_data.csv')

#convert date field from string to datetime
df_sales['date'] = pd.to_datetime(df_sales['date'])

#show first 10 rows
df_sales.head(10)