'Returns pandas DataFrames for all values'

def _to_pandas(self):

    index = self._index
    num_zeros = np.ceil(np.log10(self._ncomp))
    comp_str = (('comp_{0:0' + str(int(num_zeros))) + 'd}')
    cols = [comp_str.format(i) for i in range(self._ncomp)]
    df = pd.DataFrame(self.factors, columns=cols, index=index)
    self.scores = self.factors = df
    df = pd.DataFrame(self.projection, columns=self._columns, index=index)
    self.projection = df
    df = pd.DataFrame(self.coeff, index=cols, columns=self._columns)
    self.coeff = df
    df = pd.DataFrame(self.loadings, index=self._columns, columns=cols)
    self.loadings = df
    self.eigenvals = pd.Series(self.eigenvals)
    self.eigenvals.name = 'eigenvals'
    vec_str = comp_str.replace('comp', 'eigenvec')
    cols = [vec_str.format(i) for i in range(self.eigenvecs.shape[1])]
    self.eigenvecs = pd.DataFrame(self.eigenvecs, columns=cols)
    self.rsquare = pd.Series(self.rsquare)
    self.rsquare.index.name = 'ncomp'
    self.rsquare.name = 'rsquare'
    self.ic = pd.DataFrame(self.ic, columns=['IC_p1', 'IC_p2', 'IC_p3'])
    self.ic.index.name = 'ncomp'
