In [1]:

    

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib

%matplotlib inline
matplotlib.style.use('ggplot')


    

In [2]:

    

#plot_df = pandas.DataFrame({
#    'col1': [1, 3, 2, 4],
#    'col2': [3, 6, 5, 1],
#    'col3': [4, 7, 6, 2],
#})
mongo_df = pd.read_csv('./mongo.csv',header=0,index_col=0)
mysql_df = pd.read_csv('./mysql.csv',header=0,index_col=0)


    

In [3]:

    

mongo_df


    

    
Out[3]:






  

    

      

      
duration
    
    

      
query
      

    
  
  

    

      
1
      
25.997
    
    

      
2
      
2.158
    
    

      
3
      
0.107
    
    

      
4
      
0.156
    
    

      
5
      
0.005
    
    

      
6
      
0.007
    
  

In [4]:

    

mysql_df


    

    
Out[4]:






  

    

      

      
duration
    
    

      
query
      

    
  
  

    

      
Fill
      
11.366532
    
    

      
Index
      
2.153368
    
    

      
Update
      
0.454594
    
    

      
Delete
      
0.132651
    
    

      
Count
      
2.254035
    
    

      
Interval
      
0.000820
    
  

In [5]:

    

# Cambio los nombres de las columnas para identificar cada dato y copio el index de mysql,
# porque el CSV de mongo no lleva el nombre de las querys.

mongo_df.columns=["MongoDB"]
mysql_df.columns=["MySQL"]
mongo_df.index = mysql_df.index
mongo_df


    

    
Out[5]:






  

    

      

      
MongoDB
    
    

      
query
      

    
  
  

    

      
Fill
      
25.997
    
    

      
Index
      
2.158
    
    

      
Update
      
0.107
    
    

      
Delete
      
0.156
    
    

      
Count
      
0.005
    
    

      
Interval
      
0.007
    
  

In [6]:

    

final_df = pd.concat([mysql_df,mongo_df],axis=1)
final_df


    

    
Out[6]:






  

    

      

      
MySQL
      
MongoDB
    
    

      
query
      

      

    
  
  

    

      
Fill
      
11.366532
      
25.997
    
    

      
Index
      
2.153368
      
2.158
    
    

      
Update
      
0.454594
      
0.107
    
    

      
Delete
      
0.132651
      
0.156
    
    

      
Count
      
2.254035
      
0.005
    
    

      
Interval
      
0.000820
      
0.007
    
  

In [7]:

    

final_df.plot(kind='bar').set(ylabel='ms')


    

    
Out[7]:





[<matplotlib.text.Text at 0x7f0dd97b6750>]






    

In [8]:

    

final_df.plot(logy=True,kind='bar',figsize=(15,15*3/4)).set(ylabel='ms')


    

    
Out[8]:





[<matplotlib.text.Text at 0x7f0dd9613610>]