R- mutate/drop integer values in a nested list

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I'am facing an issue while working on nested list. I've accumulated a large list, containing 1161 rows- where each row contains a scraped tibble (with individual columns and rows). While trying to unnest/bind_rows the result I get the error message: Can't combine ..1$Varname and ..374$Varname . So these represent identical variblenames, that are not merge-able because of a different structure.

How can I drop, mutate, or filter these integer values to unnest or bind_rows into an unnested dataframe?

( I already tried to convert the list into a nested dataframe and work on that, but to no real success.

nested_df <- tibble(said_list, .id=names(said_list))

df1 <- unnest(nested_df, cols = c(said_list))

df = bind_rows(said_list , .id="ID")

Right now I´m stuck at running the unnest/bind_row command, which identifies one single location with integers, and deleting that single column. e.g.

said_list[[374]][4] <- NULL

Thanks in advance, this is my first post- so please let me know if you need additional code or infromations

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