Unable to Change Comma to a Dot in Decimals in R [closed]

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I have a .csv file that I’m having trouble processing because the numbers use commas for decimals, which causes issues when reading the file in R. Excel interprets commas for decimals, while R uses dots. I want to replace the commas with dots as I load the data into R. Here are some of the approaches I’ve tried:

Approach 1:

data <- read.csv2("cleaned_data.csv", stringsAsFactors = FALSE)
data$Daily_Loss <- as.numeric(gsub(",", ".", data$Daily_Loss))
data$Total_Loss <- as.numeric(gsub(",", ".", data$Total_Loss))
data$loss_2023 <- as.numeric(gsub(",", ".", data$loss_2023))
data$loss_2024 <- as.numeric(gsub(",", ".", data$loss_2024))

Approach 2:

data <- read.csv("cleaned_data.csv", sep = ";", dec = ",", stringsAsFactors = FALSE)
data$Daily_Loss <- as.numeric(gsub(",", ".", trimws(data$Daily_Loss)))
data$Total_Loss <- as.numeric(gsub(",", ".", trimws(data$Total_Loss)))
data$loss_2023 <- as.numeric(gsub(",", ".", trimws(data$loss_2023)))
data$loss_2024 <- as.numeric(gsub(",", ".", trimws(data$loss_2024)))

Any suggestions on how I can fix this more efficiently? What I want to do after is:

total_loss_2023 <- sum(data$loss_2023, na.rm = TRUE)
total_loss_2024 <- sum(data$loss_2024, na.rm = TRUE)
cat("Total Loss in 2023: ", total_loss_2023, "\n")
cat("Total Loss in 2024: ", total_loss_2024, "\n")

Any help is welcomed! That is part of the table I am trying to convert to a different format.

without sep=";" does not work. your proposal gives me: Error in read.table(file = file, header = header, sep = sep, quote = quote, : more columns than column names — user778
– user778, Commented Dec 25, 2024 at 19:25
Hi, in my question I specify that my file is .csv and I wrote that I already tried: read.csv2("cleaned_data.csv", stringsAsFactors = FALSE) read.csv("cleaned_data.csv", sep = ";", dec = ",", stringsAsFactors = FALSE) — user778
– user778, Commented Dec 25, 2024 at 19:36
Posts to SO need to show the input which in this case is the csv file so that others can run the code. If the file is large you can post a cut down version. — G. Grothendieck
– G. Grothendieck, Commented Dec 25, 2024 at 19:39
Just use read.csv("file.csv", dec = ","), like @G.Grothendieck suggested, instead of read.csv2(). It works for me! — Ifeanyi Idiaye
– Ifeanyi Idiaye, Commented Dec 25, 2024 at 19:47

lailaps · Accepted Answer · 2024-12-25 20:06:15Z

2

To handle comma decimals efficiently, try:

data <- read.csv2("cleaned_data.csv", dec = ",", stringsAsFactors = FALSE)

read.csv2() is designed for European-style CSV files with semicolon separators and comma decimals. If that doesn't work you can use this for replacing the commas:

data <- read.csv("cleaned_data.csv", stringsAsFactors = FALSE)
# Convert all numeric columns at once
numeric_cols <- c("Daily_Loss", "Total_Loss", "loss_2023", "loss_2024")
data[numeric_cols] <- lapply(data[numeric_cols], function(x) as.numeric(gsub(",", ".", x)))

answered Dec 25, 2024 at 20:06

lailaps

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