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This notebook plots the number of origins of viviparity and reversions to oviparity, broken down by tree. The result is a grouped histogram.



In [1]:

    
import pandas as pd
from pandas import *
import matplotlib.pyplot as plt
%matplotlib inline
from ggplot import *
from numpy import random 
plt.style.use('ggplot')

Read data using pandas.



In [3]:

    
data = pd.read_csv("../Data/Histogram/pared_down.csv")
data



In [99]:

    
data.columns









    Out[99]:





Index([u'diff', u'vo', u'Term', u'Improvement'], dtype='object')

Pivot the table to group the data by tree.



In [ ]:

    
table = pivot_table(data, index=['Tree'], columns=['Parameter'])
table

Plot using native pandas plotting.



In [32]:

    
table.plot(kind='bar', width=.7, sort_columns=True).set_ylim(0,75)

plt.tight_layout()
plt.savefig('exTotal.svg', bbox_inches='tight', dpi=300)



In [81]:



In [ ]:

	Tree	Reversions	Origins	Parameter
0	0	32	21	NP
1	0	24	25	1p
2	0	26	24	2p
3	5684	24	22	NP
4	5684	20	23	1p
5	5684	26	20	2p
6	5870	28	18	NP
7	5870	17	28	1p
8	5870	26	18	2p
9	83796	35	18	NP
10	83796	33	22	1p
11	83796	42	18	2p