In [1]:

    

import numpy as np
import pandas as pd
from clustergrammer_widget import *
net = Network(clustergrammer_widget)


    

    




add widget class

In [2]:

    

net.load_file('rc_two_cats.txt')
net.make_clust()
net.widget()


    

In [4]:

    

df_genes = net.widget_df()
df_genes.shape


    

    




<clustergrammer_widget.clustergrammer.Network object at 0x1105309d0>






    
Out[4]:





(8, 6)

In [ ]:

    




    

In [5]:

    

net.load_df(df_genes)
net.make_clust()
net.widget()


    

In [19]:

    

len(net.widget_instance.mat_string)


    

    
Out[19]:





35003

In [14]:

    

net.widget_instance.mat_string


    

    
Out[14]:





u"\t('H1734', 'Category: one', 'Gender: Female')\t('HCC827', 'Category: one', 'Gender: Female')\n('STK32A', 'Gene Type: Interesting')\t2.824551497\t1.156531983\n('STK31', 'Gene Type: Interesting')\t1.788457016\t3.8891158239999997\n"

In [21]:

    




    

    
Out[21]:





(38, 29)

In [6]:

    

# generate random matrix
num_rows = 500
num_cols = 10
np.random.seed(seed=100)
mat = np.random.rand(num_rows, num_cols)

# make row and col labels
rows = range(num_rows)
cols = range(num_cols)
rows = [str(i) for i in rows]
cols = [str(i) for i in cols]

# make dataframe 
df = pd.DataFrame(data=mat, columns=cols, index=rows)


    

In [7]:

    

net.load_df(df)
net.make_clust()
net.widget()


    

In [8]:

    

df_random = net.widget_df()
df_random.shape


    

    




<clustergrammer_widget.clustergrammer.Network object at 0x1103932d0>






    
Out[8]:





(26, 3)

In [ ]:

    




    

In [ ]: