Misleading error when non-numeric inputs fed to SimpleImputer

Currently, if a dataframe with non-numeric values is passed into the simple imputer and the strategy is mean or median, it will give an error like `ValueError: Length of passed values is 2, index implies 3`.
This is because the mean and quantile functions automatically exclude any non-numeric columns. If `numeric_only=False` gets passed to the mean and quantile functions, it would give a more straightforward error like `TypeError: could not convert string to float: 'xyz'` for mean, and `TypeError: can't multiply sequence by non-int of type 'float'` for median.

Start at the SimpleImputer implementation and trace the mean and median strategy paths for dataframe inputs containing non-numeric values. Reproduce the reported case, then verify that invalid inputs produce direct conversion errors rather than the misleading length/index error; no specific source file or test is named in the issue.

Written by the indexing model from the issue text.