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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 missing_inds(x, format_data=True):
 """ Returns indices of missing data This function is useful to identify rows of your array that contain missing data or nans. The returned indices can be used to remove the rows with missing data, or label the missing data points that are interpolated using PPCA. Parameters x : array or list of arrays format_data : bool Whether or not to first call the format_data function (default: True). Returns inds : list, or list of lists A list of indices representing rows with missing data. If a list of numpy arrays is passed, a list of lists will be returned. """


    if format_data:
        x = formatter(x, ppca=False)

    inds = []
    for arr in x:
        if np.argwhere(np.isnan(arr)).size is 0:
            inds.append(None)
        else:
            inds.append(np.argwhere(np.isnan(arr))[:,0])
    if len(inds) > 1:
        return inds
    else:
        return inds[0]