I'm trying biomaRt (a bioconductor package) for converting a column of Uniprot IDs to their corresponding protein names using RStudio. But I'm still not able to see the names changing. I'd appreciate it if someone can have a look at my code and correct it for me so that it does actually work

#Install the biomaRt (a bioconductor package)
if (!require("BiocManager", quietly = TRUE))
  install.packages("BiocManager")

BiocManager::install("biomaRt")

# Load the required libraries
library(biomaRt)

# Read the CSV file
fold_changes <- read.csv("fold_changes.csv")

# Connect to the Ensembl database using biomaRt
ensembl <- useMart("ensembl", dataset = "hsapiens_gene_ensembl")

# Get the protein names using biomaRt
search_ids <- c("protein")
protein_names <- biomaRt::getBM(attributes = c("ensembl_gene_id","uniprotswissprot", "description","hgnc_symbol","gene_biotype"),#,"entrezgene" 
                                filters = "uniprotswissprot", 
                                values = search_ids, 
                                mart = ensembl)

# Rename the protein name column to "protein_name"
colnames(fold_changes)[1] <- "protein_name"

# Write the updated data frame to a new CSV file
write.csv(fold_changes, file = "fold_changes_with_names.csv", row.names = FALSE)

Your call to getBM has an extra '#' in it that is probably not helping things. Plus you are asking a database for a lot of things in one query, which will often result in tons of results coming back. It's usually better to ask for just a few things. If you just want the protein name, I would get that. Also, you want to always include your filter as an attribute, because a database won't return things in the same order that you provided. Also also, if you have NCBI Gene IDs it's probably better to query a database that is based on them rather than something like the Biomart server, which is based on Ensembl. So, a few examples.

> library(biomaRt)
> mart <- useEnsembl("ensembl","hsapiens_gene_ensembl")
> library(org.Hs.eg.db)
## get some random Gene IDs
> egids<- head(keys(org.Hs.eg.db), 20)
> z <- getBM(c("entrezgene_id","ensembl_gene_id","uniprotswissprot","description","hgnc_symbol"), "entrezgene_id", egids, mart)
## check for duplicates
> table(z$entrezgene_id)

 1  2  9 10 12 13 14 15 16 18 19 20 21 22 23 24 25 
 2  2  2  2  2  2  2  2  2  2  2  2  2  2 14  2  2
> head(z)
  entrezgene_id ensembl_gene_id uniprotswissprot
1            23 ENSG00000225989           Q8NE71
2            23 ENSG00000225989                 
3            23 ENSG00000236149           Q8NE71
4            23 ENSG00000236149                 
5            10 ENSG00000156006           P11245
6            10 ENSG00000156006                 
                                                                 description
1 ATP binding cassette subfamily F member 1 [Source:HGNC Symbol;Acc:HGNC:70]
2 ATP binding cassette subfamily F member 1 [Source:HGNC Symbol;Acc:HGNC:70]
3 ATP binding cassette subfamily F member 1 [Source:HGNC Symbol;Acc:HGNC:70]
4 ATP binding cassette subfamily F member 1 [Source:HGNC Symbol;Acc:HGNC:70]
5                   N-acetyltransferase 2 [Source:HGNC Symbol;Acc:HGNC:7646]
6                   N-acetyltransferase 2 [Source:HGNC Symbol;Acc:HGNC:7646]
  hgnc_symbol
1       ABCF1
2       ABCF1
3       ABCF1
4       ABCF1
5        NAT2
6        NAT2

## Alternative method
> library(UniProt.ws)
> ws <- UniProt.ws()
> select(ws, egids, "id", "GeneID")

   From      Entry       Entry.Name
1     1     P04217       A1BG_HUMAN
2     1     V9HWD8     V9HWD8_HUMAN
3     2     P01023       A2MG_HUMAN
4     9     P18440       ARY1_HUMAN
5     9     F5H5R8     F5H5R8_HUMAN
6     9     Q400J6     Q400J6_HUMAN
7    10     P11245       ARY2_HUMAN
8    10     A4Z6T7     A4Z6T7_HUMAN
9    12     P01011       AACT_HUMAN
10   12 A0A024R6P0 A0A024R6P0_HUMAN
11   13     P22760       AAAD_HUMAN
12   14     Q13685       AAMP_HUMAN
13   14     C9JEH3     C9JEH3_HUMAN
14   15     Q16613       SNAT_HUMAN
15   15     F1T0I5     F1T0I5_HUMAN
16   16     P49588       SYAC_HUMAN
17   18     P80404       GABT_HUMAN
18   18     X5D8S1     X5D8S1_HUMAN
19   19     O95477      ABCA1_HUMAN
20   19 A0A7I2V5U0 A0A7I2V5U0_HUMAN
21   19     B2RUU2     B2RUU2_HUMAN
22   19     B7XCW9     B7XCW9_HUMAN
23   20     Q9BZC7      ABCA2_HUMAN
24   21     Q99758      ABCA3_HUMAN
25   21     Q4LE27     Q4LE27_HUMAN
26   22     O75027      ABCB7_HUMAN
27   22 A0A087WW65 A0A087WW65_HUMAN
28   22 A0A0S2Z2Z3 A0A0S2Z2Z3_HUMAN
29   23     Q8NE71      ABCF1_HUMAN
30   23 A0A1U9X609 A0A1U9X609_HUMAN
31   23     Q2L6I2     Q2L6I2_HUMAN
32   24     P78363      ABCA4_HUMAN
33   24     Q6AI28     Q6AI28_HUMAN
34   25     P00519       ABL1_HUMAN
35   25 A0A024R8E2 A0A024R8E2_HUMAN
36   25     Q59FK4     Q59FK4_HUMAN
Warning message:
IDs not mapped: 11, 17, 3

Which still has duplicates, but not as bad.