I have 10 Excel(XLSX) files I would like to join up into a single data frame for analysis

[Gbenga_Akinyemi]

Please, I have an assignment involving a large volume of data saved in 10 different files. I need an explanation and the code procedure for merging them into one singe R data frame for analysis.

These files are arranged in similar number of columns, and column title.

Note, they are not different sheets on an Excel file but different Excel files. Kindly help. ( Kindly find the image attached below)

[williaml]

Perhaps one of these?

Reading and combining many tidy data files in R | Claus O. Wilke

Vignette: Write & Read Multiple Excel files with purrr

[M_AcostaCH]

For load all the files, you could use this:
Remember set working directory

setwd(~path) # working directory
library(readxl)

files.list <- list.files(pattern='*.xlsx') # all the files are .xlsx
df.list <- lapply(files.list, read_excel)

[mikecrobp]

The main tools you need are:

1. A way of reading in Excel files - choose one
2. A way of creating a UNION of those files. I use rbind (in fact rbind.data.frame)
3. A way of dealing with the fact the column names are not exactly the same (which is expected by rbind)

A simple loop would be OK for 10 files. I think the tricky bit is point 3 above

[Gbenga_Akinyemi]

Thanks so much for the nice response.
Kindly help me with the procedures and codes needed to to achieve this feat,,,,
Please, help me..
Thanks..

[Sivuyile]

You can break this task up into a few elements. The first is the retrieval of the files. Secondly, the reading of files. Finally, merging them.

library(readxl)
library(dplyr)
library(tidyr)

Data_Files <- data.frame(excel_path =list.files(full.names=TRUE,pattern = ".xlsx$",
path=getwd())) # Find the files in your working directory/path

Data_Files <- Data_Files %>%
 mutate(excel_files = lapply(excel_path, read_xlsx)) %>% # Read Each xlsx file.
 unnest(excel_files) # Expand the list of excel files by binding rows.

[Ahuba_Oscar]

Please load the data and combine them using bind_rows() assuming that the columns are matching. If they are in xlsx then use .xlsx instead of .csv that I have used.

[williaml]

@Gbenga_Akinyemi

Kindly help me with the procedures and codes needed to to achieve this feat,,,,
Please, help me..

Use purrr or as shown in the articles. Everything you need is already there. Just read the articles. You can't expect people to do your work for you.

Otherwise, don't load the files individually, that is a waste of your time and not good practice given that you're just repeating a function ten times. Also, use Projects rather than setting the working directory. It is just good practice.