In [1]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import statsmodels.graphics.tsaplots as sgt 
import statsmodels.tsa.stattools as sts 
from statsmodels.tsa.arima_model import ARIMA
from statsmodels.tsa.seasonal import seasonal_decompose

plt.rcParams["figure.figsize"] = 10, 5


    

In [2]:

    

def to_float(v):
    try:
        return float(v)
    except:
        pass

ftse = pd.read_csv("/data/FTSE.csv")
ftse.index = pd.to_datetime(ftse.Date)
ftse = ftse[["Adj Close"]]
ftse.columns = ["Close"]
ftse.Close = ftse.Close.apply(to_float)
ftse = ftse.dropna()
ftse = ftse.sort_index().asfreq(freq='B', method = "ffill")
ftse.head()


    

    
Out[2]:







  

    

      

      
Close
    
    

      
Date
      

    
  
  

    

      
2000-01-04
      
6665.9
    
    

      
2000-01-05
      
6535.9
    
    

      
2000-01-06
      
6447.2
    
    

      
2000-01-07
      
6504.8
    
    

      
2000-01-10
      
6607.7
    
  

In [ ]: