Bind rows with different data types

Question

I have some dataframes with more than 3000 columns in each, and I want to bind them together.

When I use

library(dplyr)

bind_rows(dataframe1, dataframe2, dataframe3, dataframe4)

I get a lot of warnings:

In bind_rows_(x, .id) : Unequal factor levels: coercing to character
...

I guess it's because a column has data of type factor in one dataframe and data of type character in another dataframe. But how can I solve this problem?

I know I can use

sapply(dataframe1, class)

to get the classes of a dataframe, but as there are many columns, it is impossible to go through them all in all 4 dataframes.

This seems to be a problem about the data, but what does it mean that something has type factor? Is it a number?

Answer 1

Perhaps start with ?factor about what factors are.

To avoid the warnings, you either use supressWarnings, or you will need to convert to character first. For example (untested):

library(tidyverse)
l <- list(dataframe1, dataframe2, dataframe3, dataframe4)
map_dfr(l, ~mutate(., across(where(is.factor), as.character))