## import necessary libraries
import pandas as pd 
import matplotlib.pyplot as plt
import re
plt.style.use('fivethirtyeight') #Five thirty eight style for all plots
print plt.style.available
%matplotlib inline

## Read in the logfile line-by-line into a list
with open(r' ') as f:  ###!!!!! Enter your file path between the quotes
    lines = f.readlines()
f.close()

## Testing my Regex patterns to match all required table attributes
print 'Date:', re.findall('\d+/\d+/\d+', lines[1383]) #Date
print 'Time:', re.findall('\d+:\d+:\d+', lines[1383]) #Timestamp
print 'UserID:',re.findall('(\S+@\S+)', lines[1109])  #User ID 
print 'Name:',re.findall('\w+@', lines[1109])[0][:-1] #Name/ User 
print 'Location:',re.findall('@\D+', lines[1109])[0][1:] #Location
print 'Message:', re.findall('"\S+"', lines[1109])[0][1:-1] #message

## The following loop block parses the logfile and matches the Date with user
mylist = [] #To store the info
for i in range(len(lines)):
    if 'TIMESTAMP' in lines[i] and 'TIMESTAMP' not in lines[i+1]:
        print i+1, 'Found'
        j = i+1
        flag = True
        
        while flag:
            
            if 'TIMESTAMP' in lines[j]:
                #i=j-2;
                flag = False
            
            elif len(re.findall('(\S+@\S+)', lines[j]))>0:
                mylist.append([re.findall('\d+/\d+/\d+', lines[i])[0],re.findall('\d+:\d+:\d+', lines[j])[0],re.findall('(\S+@\S+)', lines[j])[0],re.findall('\w+@', lines[j])[0][:-1],re.findall('@\D+', lines[j])[0][1:],re.findall('"\S+"', lines[j])[0][1:-1]])
                j = j+1
                
            elif len(re.findall('(\S+@\S+)', lines[j])) == 0:
                j = j+1
        
    else:
        print i+1,'not found'

len(mylist)#checking length of the list with the data
mylist[896] #checking an entry for completeness

##Creating a pandas dataframe from the list
mydata = pd.DataFrame(mylist, columns =(['Date', 'Time', 'UserID', 'Name', 'LocationID', 'Message']))

##Convert Date column to datetime format
mydata['Date'] = pd.to_datetime(mydata['Date'])

##Export to excel file
#mydata.to_excel(r' ') ###!!!!! Enter your output file path between the quotes