In [1]:
from __future__ import division
import datetime
import pandas
import numpy
import matplotlib.pyplot as plt
import seaborn
seaborn.set_style("whitegrid")
seaborn.despine()
%matplotlib inline
%config InlineBackend.figure_formats = {'svg',}

In [22]:
df = pandas.read_csv('../data/profiles.data', skiprows=8)
df.drop(0, axis=0, inplace=True)
columns = ['node' + str(index) for index in range(1, len(df.columns))]
columns.insert(0, 'date')
df.columns = columns
df.date = df.date.apply(lambda x: datetime.datetime.strptime(x, '%Y-%m-%d %H:%M'))
df.set_index('date', inplace=True)

In [28]:
l = ["node_d3", "node_c6", "node_b7", "node_d11", "node_b5", "node_d12", "node_b8", "node_b1", "node_c8", "node_d4", "node_d6", "node_d1", "node_a2", "node_b2", "node_b6", "node_d2", "node_d7", "node_c2", "node_c5", "node_d10", "node_c4", "node_b9", "node_c7", "node_b4", "node_c12", "node_d5", "node_d9", "node_a1", "node_c1", "node_d8", "node_c11", "node_a3", "node_c10", "node_b10", "node_b3", "node_c3", "node_c9"]
len(l)


Out[28]:
37

In [39]:
start = datetime.datetime(2014, 6, 17, 0, 0, 0)
end = datetime.datetime(2014, 6, 18, 0, 0, 0)
plt.figure(figsize=(11, 5))
plt.plot(df[['node' + str(index) for index in range(10, 20)]].sum(axis=1)[start:end])
plt.show()



In [38]:
df.head()


Out[38]:
node1 node2 node3 node4 node5 node6 node7 node8 node9 node10 ... node51 node52 node53 node54 node55 node56 node57 node58 node59 node60
date
2014-01-01 00:00:00 136.76 41.34 152.66 261.84 62.40 188.53 177.52 558.59 101.26 72.74 ... 644.26 568.26 113.34 126.62 40.97 42.67 117.43 51.63 288.94 158.37
2014-01-01 00:15:00 330.67 319.30 249.48 432.85 62.64 266.66 403.14 494.19 101.18 72.47 ... 863.52 622.75 115.99 128.60 131.80 43.42 292.46 116.57 359.73 82.66
2014-01-01 00:30:00 230.49 345.85 260.34 486.18 153.67 223.28 335.08 564.88 40.39 171.81 ... 835.47 417.05 43.26 51.88 133.26 111.20 185.46 116.77 459.78 267.10
2014-01-01 00:45:00 268.72 442.71 165.64 553.54 153.14 227.09 515.32 793.35 37.66 314.38 ... 935.81 447.22 133.12 52.79 41.03 198.43 199.23 50.95 442.35 267.17
2014-01-01 01:00:00 471.48 322.18 164.73 438.62 449.57 270.88 396.80 682.30 38.00 348.73 ... 912.99 661.86 135.32 51.17 127.59 208.64 200.04 358.03 339.16 583.85

5 rows × 60 columns