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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def plot_acf(series, ax=None, lags=None, alpha=None, use_vlines=True, unbiased=False, fft=True, title='Autocorrelation', zero=True, vlines_kwargs=None, show=True, **kwargs):
 """Plot a series' auto-correlation as a line plot. A wrapper method for the statsmodels ``plot_acf`` method. Parameters series : array-like, shape=(n_samples,) The series or numpy array for which to plot an auto-correlation. ax : Matplotlib AxesSubplot instance, optional If given, this subplot is used to plot in instead of a new figure being created. lags : int, array-like or None, optional (default=None) int or Array of lag values, used on horizontal axis. Uses np.arange(lags) when lags is an int. If not provided, ``lags=np.arange(len(corr))`` is used. alpha : scalar, optional (default=None) If a number is given, the confidence intervals for the given level are returned. For instance if alpha=.05, 95 % confidence intervals are returned where the standard deviation is computed according to Bartlett's formula. If None, no confidence intervals are plotted. use_vlines : bool, optional (default=True) If True, vertical lines and markers are plotted. If False, only markers are plotted. The default marker is 'o'; it can be overridden with a ``marker`` kwarg. unbiased : bool, optional (default=False) If True, then denominators for autocovariance are n-k, otherwise n fft : bool, optional (default=True) If True, computes the ACF via FFT. title : str, optional (default='Autocorrelation') Title to place on plot. Default is 'Autocorrelation' zero : bool, optional (default=True) Flag indicating whether to include the 0-lag autocorrelation. Default is True. vlines_kwargs : dict, optional (default=None) Optional dictionary of keyword arguments that are passed to vlines. show : bool, optional (default=True) Whether to show the plot after it's been created. If not, will return the plot as an Axis object instead. **kwargs : kwargs, optional Optional keyword arguments that are directly passed on to the Matplotlib ``plot`` and ``axhline`` functions. Notes ----- This method will only show the plot if ``show=True`` (which is the default behavior). To simply get the axis back (say, to add to another canvas), use ``show=False``. Examples -------- <matplotlib.figure.Figure object at 0x122fab4e0> Returns ------- plt : Axis or None If ``show`` is True, does not return anything. If False, returns the Axis object. """

    _err_for_no_mpl()
    res = pacf(x=series, ax=ax, lags=lags, alpha=alpha, use_vlines=use_vlines,
               unbiased=unbiased, fft=fft, title=title, zero=zero,
               vlines_kwargs=vlines_kwargs, **kwargs)

    return _show_or_return(res, show)