%matplotlib inline
import scipy.stats
import idc
import idaapi
import idautils
import numpy as np
import pandas as pd
import pylab
#Better looking Graphs..
pd.options.display.mpl_style = 'default' 
pylab.rcParams['figure.figsize'] = 12.0, 8.0
#Binary Info
print "MD5: {} Binary: {}".format(idc.GetInputMD5(), idc.GetInputFile())

def entropy(in_bytes):
    bytes = np.array(np.fromstring(in_bytes,dtype='uint8'), dtype='int32')
    return scipy.stats.entropy(bytes[np.nonzero(bytes)])

def get_func_bytes(func_ea):
    bytes = ""
    for start, end in idautils.Chunks(func_ea):
        bytes += idaapi.get_many_bytes(start, end - start)
    return bytes
    
func_start = idc.GetFunctionAttr(idc.ScreenEA(), idc.FUNCATTR_START)

data = ((func_ea, entropy(get_func_bytes(func_ea))) for func_ea in idautils.Functions())
func_df = pd.DataFrame(data, columns=["EA", "Entropy"])

func_df['Formatted_EA'] = func_df['EA'].map(lambda ea: "{:X}".format(ea))

df_plt = func_df
ax = df_plt.plot(kind='scatter', x='EA', y='Entropy')
ax.set_xticklabels(['{:X}'.format(int(ea)) for ea in ax.get_xticks()])
ax

func_df.sort(['Entropy'], ascending=False)

idc.Message(str(func_df.sort(['Entropy'], ascending=False)))