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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 pca_overview(adata, **params):
 """\ Plot PCA results. The parameters are the ones of the scatter plot. Call pca_ranking separately if you want to change the default settings. Parameters adata : :class:`~anndata.AnnData` Annotated data matrix. color : string or list of strings, optional (default: `None`) Keys for observation/cell annotation either as list `["ann1", "ann2"]` or use_raw : `bool`, optional (default: `True`) Use `raw` attribute of `adata` if present. {scatter_bulk} show : bool, optional (default: `None`) Show the plot, do not return axis. save : `bool` or `str`, optional (default: `None`) If `True` or a `str`, save the figure. A string is appended to the default filename. Infer the filetype if ending on {{'.pdf', '.png', '.svg'}}. """

    show = params['show'] if 'show' in params else None
    if 'show' in params: del params['show']
    scatterplots.pca(adata, **params, show=False)
    pca_loadings(adata, show=False)
    pca_variance_ratio(adata, show=show)