I have data that looks like: 1495573445.162, 0, 0.021973, 0.012283, -0.995468, 1 1495573445.172, 0, 0.021072, 0.013779, -0.994308, 1 1495573445.182, 0, 0.020157, 0.015717, -0.995575, 1 1495573445.192, 0, 0.017883, 0.012756, -0.993927, 1 1495573445.202, 0, 0.021194, 0.012161, -0.994705, 1 1495573445.212, 0, 0.019638, 0.013718, -0.994019, 1 1495573445.222, 0, 0.019440, 0.010803, -0.994476, 1 1495573445.232, 0, 0.018112, 0.010849, -0.993073, 1 1495573445.242, 0, 0.020157, 0.011154, -0.994644, 1 1495573445.252, 0, 0.020340, 0.010040, -0.995804, 1 1495573445.262, 0, 0.017792, 0.009857, -0.996078, 1 1495573445.272, 0, 0.020538, 0.010239, -0.994858, 1This is accelerometer data where the data frame columns are labeled Time stamp, Time skipped, x, y, z, and label with the index set to Time stamp. The sampling rate is around 100Hz. How should I create a sliding window in this case? I came up with this:def sliding_window(data, window_size, step_size):    data = pd.rolling_window(data, window_size)    data = data[step_size - 1 :: step_size]    print data    return dataI doubt this is the correct answer, and I don't know what to set window_size and step_size given that I have a 100Hz sampling rate.
Sliding window time series data with Python Pandas data frame
python;time series;pandas;dataframe