In [121]:

    

import pandas as pd
import networkx as nx


    

In [104]:

    

pd.read_csv('summary.csv', parse_dates=True)


    

    
Out[104]:






  

    

      

      
statistic
      
value
    
  
  

    

      
0
      
number-of-commits
      
119
    
    

      
1
      
number-of-entities
      
105
    
    

      
2
      
number-of-entities-changed
      
435
    
    

      
3
      
number-of-authors
      
3
    
  

In [34]:

    

authors_churn = pd.read_csv('author-churn.csv')


    

In [42]:

    

authors_churn


    

    
Out[42]:






  

    

      

      
author
      
added
      
deleted
    
  
  

    

      
0
      
Brian Hicks
      
4081
      
1705
    
    

      
1
      
Daniel Krawczyk
      
1285
      
772
    
    

      
2
      
Tomasz Janiszewski
      
4034
      
2401
    
  

In [ ]:

    

authors = pd.read_csv('authors.csv')


    

In [41]:

    

authors.head()


    

    
Out[41]:






  

    

      

      
entity
      
n-authors
      
n-revs
    
  
  

    

      
0
      
main.go
      
3
      
31
    
    

      
1
      
web.go
      
3
      
29
    
    

      
2
      
README.md
      
3
      
26
    
    

      
3
      
marathon/marathon.go
      
3
      
22
    
    

      
4
      
web_test.go
      
3
      
19
    
  

In [43]:

    

authors.describe()


    

    
Out[43]:






  

    

      

      
n-authors
      
n-revs
    
  
  

    

      
count
      
105.000000
      
105.000000
    
    

      
mean
      
1.514286
      
4.142857
    
    

      
std
      
0.735295
      
5.570231
    
    

      
min
      
1.000000
      
1.000000
    
    

      
25%
      
1.000000
      
1.000000
    
    

      
50%
      
1.000000
      
2.000000
    
    

      
75%
      
2.000000
      
5.000000
    
    

      
max
      
3.000000
      
31.000000
    
  

In [24]:

    

%matplotlib inline
authors.plot(kind='scatter', x='n-authors', y='n-revs');


    

In [32]:

    

authors.groupby('n-authors').describe()


    

    
Out[32]:






  

    

      

      

      
n-revs
    
    

      
n-authors
      

      

    
  
  

    

      
1
      
count
      
66.000000
    
    

      
mean
      
2.045455
    
    

      
std
      
1.884608
    
    

      
min
      
1.000000
    
    

      
25%
      
1.000000
    
    

      
50%
      
1.000000
    
    

      
75%
      
2.000000
    
    

      
max
      
10.000000
    
    

      
2
      
count
      
24.000000
    
    

      
mean
      
3.791667
    
    

      
std
      
1.587428
    
    

      
min
      
2.000000
    
    

      
25%
      
2.750000
    
    

      
50%
      
3.500000
    
    

      
75%
      
5.000000
    
    

      
max
      
7.000000
    
    

      
3
      
count
      
15.000000
    
    

      
mean
      
13.933333
    
    

      
std
      
9.284908
    
    

      
min
      
4.000000
    
    

      
25%
      
7.000000
    
    

      
50%
      
9.000000
    
    

      
75%
      
20.500000
    
    

      
max
      
31.000000
    
  

In [119]:

    

communication = pd.read_csv('communication.csv', parse_dates=True)


    

In [169]:

    

strength = communication['strength']
communication['normal_strength'] = strength.apply(lambda x: (x - strength.min()) / (strength.max() - strength.min()))


    

In [160]:

    

communication.head()


    

    
Out[160]:






  

    

      

      
author
      
peer
      
shared
      
average
      
strength
      
normal_strength
    
  
  

    

      
0
      
Tomasz Janiszewski
      
Daniel Krawczyk
      
27
      
57
      
47
      
1
    
    

      
1
      
Daniel Krawczyk
      
Tomasz Janiszewski
      
27
      
57
      
47
      
1
    
    

      
2
      
Tomasz Janiszewski
      
Brian Hicks
      
24
      
56
      
42
      
0
    
    

      
3
      
Brian Hicks
      
Tomasz Janiszewski
      
24
      
56
      
42
      
0
    
    

      
4
      
Daniel Krawczyk
      
Brian Hicks
      
18
      
47
      
38
      
0
    
  

In [170]:

    

G=nx.from_pandas_dataframe(communication, 'author', 'peer', ['strength'])


    

In [171]:

    

pos=nx.spring_layout(G)
edgewidth = [ d['strength'] for (u,v,d) in G.edges(data=True)]
nx.draw_networkx_edge_labels(G, pos)
nx.draw_networkx_nodes(G,pos)
nx.draw_networkx_labels(G,pos)
nx.draw_networkx_edges(G, pos, edge_color=edgewidth)


    

    
Out[171]:





<matplotlib.collections.LineCollection at 0x7f8ba34bdbd0>






    

In [179]:

    

nx.k_nearest_neighbors(G, weight='strength')


    

    
Out[179]:





{2: 2.0}

In [178]:

    

nx.pagerank(G, weight='strength')


    

    
Out[178]:





{'Brian Hicks': 0.31693061243932524,
 'Daniel Krawczyk': 0.3344486194845959,
 'Tomasz Janiszewski': 0.34862076807607845}