In [3]:

    

%matplotlib inline 

import numpy as np
import scipy as sp
import matplotlib as mpl
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import pandas as pd

pd.set_option('display.width', 500)
pd.set_option('display.max_columns', 100)
pd.set_option('display.notebook_repr_html', True)
import seaborn as sns #sets up styles and gives us more plotting options


    

In [4]:

    

# Time period 1st Jan - 30th April (arbitrary )

# API credentials
# Email address 705762800217-compute@developer.gserviceaccount.com
# Key IDs 948ee8e2a420ef14a5d5a29bd35104fe2f1e6ed4


    

In [5]:

    

# open file. It is requested via API explorer using request parameters:

#Account: Skein.co
#Property: Skein.co
#View: Skein.co - Report
#ids: ga:93735856
#start-date: 2017-02-01
#end-date: 2017-04-30

#metrics
#ga:sessions

#dimensions
#ga:eventAction


    

In [6]:

    

# Open file
events= pd.read_csv('skein_data/Skein_tags.csv')

# rename columns
events.columns=['Events','Sessions'] 

# group by events
events = events.set_index('Events')

events


    

    
Out[6]:






  

    

      

      
Sessions
    
    

      
Events
      

    
  
  

    

      
Case Studies page
      
60
    
    

      
Contact Us page
      
16
    
  

In [7]:

    

#count rows

df=pd.DataFrame(events)
total_rows=len(df.axes[0])
print(total_rows)


    

    




2

In [8]:

    

#checking the count of tags

if total_rows < 5:
    result = print("Set tags to enable more user analytics features.")
    
else:
    result = True
    
result


    

    




Set tags to enable more user analytics features.

In [9]:

    

# open file. It is requested via API explorer using request parameters:

#Account: Skein.co
#Property: Skein.co
#View: Skein.co - Report
#ids: ga:93735856
#start-date: 2017-02-01
#end-date: 2017-04-30

#metrics
#ga:goal1Completions
#ga:goal2Completions
#ga:goal3Completions
#ga:goal4Completions


    

In [11]:

    

# Open file
goals= pd.read_csv('skein_data/Skein_goals_tags.csv')

goals


    

    
Out[11]:






  

    

      

      
ga:goal1Completions
      
ga:goal2Completions
      
ga:goal3Completions
      
ga:goal4Completions
    
  
  

    

      
0
      
814
      
5
      
11
      
63
    
  

In [14]:

    

#count rows

df=pd.DataFrame(goals)
total_goals=len(df.axes[1])
print(total_goals)


    

    




4

In [15]:

    




    

    
Out[15]:





4

In [17]:

    

print(d % 'goals defined')


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-17-0e53afdbf5ae> in <module>()
----> 1 print(d % 'goals defined')

TypeError: unsupported operand type(s) for %: 'int' and 'str'

In [ ]: