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These make it clear that we need to use the tibble behavior when joining, concatenating or casting skim_df objects. For a better discussion, on why this is important and how these functions work, see: https://vctrs.r-lib.org/reference/howto-faq-coercion-data-frame.html.

Usage

# S3 method for skim_df.skim_df
vec_ptype2(x, y, ...)

# S3 method for skim_df.tbl_df
vec_ptype2(x, y, ...)

# S3 method for tbl_df.skim_df
vec_ptype2(x, y, ...)

# S3 method for skim_df.skim_df
vec_cast(x, to, ...)

# S3 method for skim_df.tbl_df
vec_cast(x, to, ...)

# S3 method for tbl_df.skim_df
vec_cast(x, to, ...)

Details

vec_ptype2.* handles finding common prototypes between skim_df and similar objects. vec_cast.* handles casting between objects. Note that as of dplyr 1.0.2, dplyr::bind_rows() does not full support combining attributes and vctrs::vec_rbind() is preferred instead.