Import & Merge Multiple CSV Files in R (Example) | dplyr, plyr & readr Packages | How to Load & Read

How to import and merge CSV files in the R programming language. More details: statisticsglob...
R code of this video:
data1 ＜- data.frame(id = 1:6, # Create first example data frame
x1 = c(5, 1, 4, 9, 1, 2),
x2 = c("A", "Y", "G", "F", "G", "Y"))
data2 ＜- data.frame(id = 4:9, # Create second example data frame
y1 = c(3, 3, 4, 1, 2, 9),
y2 = c("a", "x", "a", "x", "a", "x"))
data3 ＜- data.frame(id = 5:6, # Create third example data frame
z1 = c(3, 2),
z2 = c("K", "b"))
write.csv(data1, "C:/Users/Joach/Desktop/my_folder/data1.csv", # Write first example data frame
row.names = FALSE)
write.csv(data2, "C:/Users/Joach/Desktop/my_folder/data2.csv", # Write second example data frame
row.names = FALSE)
write.csv(data3, "C:/Users/Joach/Desktop/my_folder/data3.csv", # Write third example data frame
row.names = FALSE)
install.packages("dplyr") # Install dplyr package
install.packages("plyr") # Install plyr package
install.packages("readr") # Install readr package
library("dplyr") # Load dplyr package
library("plyr") # Load plyr package
library("readr") # Load readr package
data_all ＜- list.files(path = "C:/Users/Joach/Desktop/my_folder", # Identify all csv files in folder
pattern = "*.csv", full.names = TRUE) %＞%
lapply(read_csv) %＞% # Store all files in list
bind_rows # Combine data sets into one data set
data_all_df ＜- as.data.frame(data_all) # Convert tibble to data.frame
install.packages("purrr") # Install & load purrr package
library("purrr")
data_join ＜- list.files(path = "C:/Users/Joach/Desktop/my_folder", # Identify all csv files in folder
pattern = "*.csv", full.names = TRUE) %＞%
lapply(read_csv) %＞% # Store all files in list
purrr::reduce(full_join, by = "id") # Full-join data sets into one data set
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[@surajbhagat2672]

how to add new column in combined data describing the each DataName where do those data belong?

[@cansustatisticsglobe]

Hello! Please see the following R code. Where I defined a special function that reads the CSV elements and retrieves the source name using the gsub function (statisticsglobe.com/sub-gsub-r-function-example) and then creates a source_name column using the mutate function (statisticsglobe.com/r-mutate-transmute-functions-dplyr-package). library("dplyr") library("plyr") library("readr") # Function to read each CSV file and add a source column read_csv_with_source

[@amane49]

Another amazing to the point video !! Easy to follow, logical and very helpful!

[@matthias.statisticsglobe]

What a great and motivating comment! Thank you very much for your support!

[@vishakhakarnawat]

Thanks. Could you also show how to merge multiple .txt files excluding headers and get the resultant output in .txt?

[@cansustatisticsglobe]

Hello Vishakha, Would you like to implement something like this? data1

[@danielmoreno1097]

Thx, this help me so much, greetings from Colombia

[@matthias.statisticsglobe]

That's great to hear, thank you so much for the positive feedback, Daniel! Greetings back from Germany

[@krono32]

This helped me with a project. Thank you!

[@micha.statisticsglobe]

Thanks a lot for your feedback. Glad it helped! 🙂

[@Sara-LeeRamsawak-s6x]

Thanks so much, this is very helpful. What does this row of code do? --> data_all_df ＜- as.data.frame(data_all) # Convert tibble to data.frame

[@Ifeanyi.StatisticsGlobe]

Hi User-MV. Yes, as.data.frame( ) converts a tibble into a dataframe. You can confirm this by running str( ) on the new converted dataframe object. I hope this helps!