In [1]:

    

import pandas as pd
import matplotlib.pyplot as plt

#%matplotlib inline


    

In [2]:

    

ecg = pd.read_csv('sel100.csv',header=[0,1],dtype=float)
print ecg


    

    




       'Elapsed time' 'MLII'   'V5'
            'seconds'   'mV'   'mV'
0               0.000  4.725  4.775
1               0.004  4.735  4.745
2               0.008  4.725  4.735
3               0.012  4.715  4.745
4               0.016  4.720  4.735
5               0.020  4.705  4.725
6               0.024  4.700  4.710
7               0.028  4.690  4.715
8               0.032  4.710  4.710
9               0.036  4.710  4.710
10              0.040  4.695  4.695
11              0.044  4.690  4.690
12              0.048  4.710  4.710
13              0.052  4.695  4.705
14              0.056  4.705  4.685
15              0.060  4.700  4.705
16              0.064  4.710  4.715
17              0.068  4.710  4.720
18              0.072  4.700  4.720
19              0.076  4.705  4.745
20              0.080  4.720  4.785
21              0.084  4.735  4.790
22              0.088  4.740  4.790
23              0.092  4.730  4.805
24              0.096  4.755  4.825
25              0.100  4.765  4.835
26              0.104  4.780  4.830
27              0.108  4.780  4.840
28              0.112  4.780  4.850
29              0.116  4.805  4.860
...               ...    ...    ...
224970        899.880  4.700  4.980
224971        899.884  4.720  4.990
224972        899.888  4.740  5.005
224973        899.892  4.740  4.995
224974        899.896  4.735  4.990
224975        899.900  4.735  4.990
224976        899.904  4.765  5.010
224977        899.908  4.775  5.015
224978        899.912  4.770  5.020
224979        899.916  4.785  5.035
224980        899.920  4.795  5.045
224981        899.924  4.805  5.040
224982        899.928  4.790  5.040
224983        899.932  4.780  5.060
224984        899.936  4.785  5.075
224985        899.940  4.790  5.070
224986        899.944  4.785  5.055
224987        899.948  4.770  5.055
224988        899.952  4.770  5.070
224989        899.956  4.800  5.055
224990        899.960  4.805  5.035
224991        899.964  4.780  5.030
224992        899.968  4.760  5.045
224993        899.972  4.745  5.045
224994        899.976  4.715  5.025
224995        899.980  4.690  5.025
224996        899.984  4.690  5.040
224997        899.988  4.695  5.035
224998        899.992  4.680  5.010
224999        899.996  4.680  5.015

[225000 rows x 3 columns]

In [3]:

    

ecg_t = ecg.iloc[1000:2999,0]
ecg_a1 = ecg.iloc[1000:2999,1]
ecg_a2 = ecg.iloc[1000:2999,2]


    

In [4]:

    

ax1 = plt.subplot(211);
plt.plot(ecg_t,ecg_a1);
plt.xlabel('Time');
plt.ylabel('MLII');
ax2 = plt.subplot(212, sharex=ax1, sharey=ax1);
plt.plot(ecg_t,ecg_a2);
plt.xlabel('Time');
plt.ylabel('V5');


    

In [5]:

    

plt.show()


    

In [ ]: