跳到主要内容

Repeat data frames in R

· 阅读需 3 分钟

Briefly introduce how to create data frames with repeated suffixes in R

Sometimes, we want to create some data frames with a fixed prefix and a range of numbers. For example, we want to create 10 data frames with names df1, df2, …, df10.

We have two ways to do this.

  1. One list: create a list of data frames and store them into a list df_list.
  2. Individual dataframe: create 10 data frames with names df1, df2, …, df10 directly.

One list

Firstly, let’s try to create a list of data frames and store them into a list df_list.

library(dplyr)

num <- 1:10

# Create an empty list
df_list <- list()

# Loop through the numbers
for (i in num) {
# suppose we have different values for x and y
temp <- data.frame(x = rnorm(10), y = rnorm(10)) %>%
# Add a column with the current number
mutate(id = i)
# Add the data frame to the list
df_list[[i]] <- temp
}

Then, we can use dplyr to transform the list to a dataframes by using bind_rows.

df <- bind_rows(df_list)

head(df)

A data.frame: 6 x 3

x <dbl> y <dbl> id <int>
1 -0.4229988 -0.2171858 1
2 1.5798157 0.9990500 1
3 -0.1763058 -1.1700267 1
4 0.5552782 -0.4305593 1
5 0.2594807 1.3306744 1
6 0.5152127 0.4716893 1

Individual dataframe

Secondly, let’s try to create 10 data frames with names df1, df2, …, df10 directly.

Then, we can use dplyr to transform the dataframes to a dataframes by using bind_rows.

num <- 1:10

for (i in num) {
# use assign to create a new variable.names
assign(paste0("df_", i), data.frame(x = rnorm(10), y = rnorm(10)))
}

# List all the data frames
ls(pattern = "df_")
  1. ‘df_1’
  2. ‘df_10’
  3. ‘df_2’
  4. ‘df_3’
  5. ‘df_4’
  6. ‘df_5’
  7. ‘df_6’
  8. ‘df_7’
  9. ‘df_8’
  10. ‘df_9’
  11. ‘df_list’

If you want to create a list to store all these variables, we can use get function to get the variable by its name.

# For example, we want to store in df_list2

df_list2 <- list()

for (i in num) {
# use assign to create a new variable.names
df_list2[[i]] <- get(paste0("df_", i))
}