import pandas as pd
!head bicycle-wheel-radial-inertia-rate-gyro-measurement.csv
time,angular_velocity 0.0,3.236790061330015 0.0020000000000000018,3.2304788385296246 0.003999999999999997,3.2195776355287498 0.005999999999999998,3.2092501800752573 0.008,3.1926115018876944 0.009999999999999995,3.1880215217073844 0.011999999999999997,3.1765465712743266 0.013999999999999999,3.1490066903384144 0.016,3.123188052093832
gyro_data = pd.read_csv('bicycle-wheel-radial-inertia-rate-gyro-measurement.csv',
index_col='time')
gyro_data.head()
angular_velocity | |
---|---|
time | |
0.000 | 3.236790 |
0.002 | 3.230479 |
0.004 | 3.219578 |
0.006 | 3.209250 |
0.008 | 3.192612 |
type(gyro_data)
pandas.core.frame.DataFrame
len(gyro_data)
1001
gyro_data.columns
Index(['angular_velocity'], dtype='object')
gyro_data['angular_velocity']
time 0.000 3.236790 0.002 3.230479 0.004 3.219578 0.006 3.209250 0.008 3.192612 ... 1.992 -0.271675 1.994 -0.207989 1.996 -0.144303 1.998 -0.085207 2.000 -0.030127 Name: angular_velocity, Length: 1001, dtype: float64
gyro_data.index
Float64Index([ 0.0, 0.0020000000000000018, 0.003999999999999997, 0.0059999999999999975, 0.008, 0.009999999999999995, 0.011999999999999995, 0.014, 0.016, 0.018000000000000002, ... 1.9820000000000004, 1.984, 1.9860000000000004, 1.988, 1.9900000000000004, 1.992, 1.9940000000000004, 1.996, 1.9980000000000004, 2.0000000000000004], dtype='float64', name='time', length=1001)
gyro_data.head()
angular_velocity | |
---|---|
time | |
0.000 | 3.236790 |
0.002 | 3.230479 |
0.004 | 3.219578 |
0.006 | 3.209250 |
0.008 | 3.192612 |
%matplotlib widget
gyro_data.plot(style='.')
Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …
<matplotlib.axes._subplots.AxesSubplot at 0x7f71eb9032e8>
type(gyro_data)
pandas.core.frame.DataFrame