In [1]:
import numpy as np
import pandas as pd
import pylab as pl
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.read_csv('tmp/session_c.csv')
In [2]:
df.dtypes
Out[2]:
In [40]:
pl.figure(figsize=(12, 6))
p=df.groupby('Bytes')['Bytes'].count().plot.bar(width=2,edgecolor='blue',color='blue')
p.tick_params(labelbottom='off',top='off',bottom='off')
p.set_yscale('log')
fig = p.get_figure()
fig.savefig('tmp/bytes000.png')
In [41]:
df['Bytes2']=np.floor(df.Bytes/10)*10+10
pl.figure(figsize=(12, 6))
p=df.groupby('Bytes2')['Bytes2'].count().plot.bar(width=2,edgecolor='blue',color='blue')
p.tick_params(labelbottom='off',top='off',bottom='off')
p.set_yscale('log')
fig = p.get_figure()
fig.savefig('tmp/bytes001.png')
In [42]:
df['Bytes3']=np.floor(df.Bytes/100)*100+100
pl.figure(figsize=(12, 6))
p=df.groupby('Bytes3')['Bytes3'].count().plot.bar(width=2,edgecolor='blue',color='blue')
p.tick_params(labelbottom='off',top='off',bottom='off')
p.set_yscale('log')
fig = p.get_figure()
fig.savefig('tmp/bytes002.png')
In [43]:
df.to_csv('tmp/session_d.csv')
In [ ]: