def plot_autocorrelation(timeseries_df, valueCol=None, timeCol='timestamp',
    timeInterval='30min', partial=False):
    """
    Plot autocorrelation of the given dataframe based on statsmodels.tsa.stattools.acf
			(which apparently is simple Ljung-Box model)
    Assumes:
       default timecol == 'timestamp' if different pass a kw parameter

    """
    import statsmodels.api as sm
    import matplotlib.pyplot as plt
    fig = plt.figure(figsize=(12, 8))
    ax1 = fig.add_subplot(111)
    if not partial:
        plt = sm.graphics.tsa.plot_acf(timeseries_df[valueCol].squeeze(),
            lags=40, ax=ax1)
    else:
        plt = sm.graphics.tsa.plot_pacf(timeseries_df[valueCol], lags=40,
            ax=ax1)
    plt.show()
    return plt
