R – Create DataFrame from Existing DataFrame

Naveen Nelamali

2 years ago

You are often required to create a DataFrame from an existing DataFrame in R. When you create from an existing you may be required to select subset of columns or select only a few rows by filtering. This is one of the most use-cases when we are working with the data.

1. Quick Examples

The following are quick examples of how to create a DataFrame from an existing R DataFrame.


# Quick examples

# Example 1 - Select columns id, gender and dob
df2 = data.frame(df$id,df$gender,df$dob)

# Example 2 - Create DataFrame with 1,3 and 4 columns 
df2 <- df[,c(1,3,4)]

# Example 3 - Create DataFrame with selecting range of columns 
df2 <- df[,c(1:3,5)]

# Example 4 - Create DataFrame with id,gender and name columns 
df2 <- df[,c('id','gender','dob')]

# Example 5 - Create DataFrame with 1,3 and 4 rows 
df2 <- df[c(1,3,4),]

# Example 6 - Create DataFrame with 1,3,4 rows and columns 2 and 4 
df2 <- df[c(1,3,4),c(2,4)]

# Example 7 - By using subset with column names
df2 <- subset(df, select=c("id", "gender", "dob"))

# Example 8 -  By using subset with indices
df2 <- subset(df, select=c(2:3, 5))

Let’s create a DataFrame, run these examples and explore the output.


# Create DataFrame
df <- data.frame(
  id = c(10,11,12,13),
  name = c('sai','ram','deepika','sahithi'),
  gender = c('M','M','F','F'),
  dob = as.Date(c('1990-10-02','1981-3-24','1987-6-14','1985-8-16')),
  state = c('CA','NY','DE','FL')
)

# Print DataFrame
df

# Output
#  id    name gender        dob state
#1 10     sai      M 1990-10-02    CA
#2 11     ram      M 1981-03-24    NY
#3 12 deepika      F 1987-06-14    DE
#4 13 sahithi      F 1985-08-16    FL

2. Create DataFrame From Existing using data.frame()

data.frame() method is used to create a DataFrame in R and also is used to create an empty DataFrame. Similarly, you can also use this to create a DataFrame by selecting subset columns and rows from an existing one.


# Create DF by selecting columns id, gender and dob
df2 = data.frame(df$id,df$gender,df$dob)
df2

# Output
#  df.id df.gender     df.dob
#1    10         M 1990-10-02
#2    11         M 1981-03-24
#3    12         F 1987-06-14
#4    13         F 1985-08-16

Note that column names have data frame prefix if you can rename columns by using R function colnames().

3. Create data frame by Selecting Columns from Existing

You can also create a DataFrame by selecting columns from the existing DataFrame. While selecting the columns you can also by name, indices, and use a range of columns.


# Create DataFrame with id,gender and name columns 
df2 <- df[,c('id','gender','dob')]
df2

# Output
#  id gender        dob
#1 10      M 1990-10-02
#2 11      M 1981-03-24
#3 12      F 1987-06-14
#4 13      F 1985-08-16

The same output can also be achieved by using indices.


# Create DataFrame with 1,3 and 4 columns 
df2 <- df[,c(1,3,4)]
df2

Similarly, you also select columns by ranges of indices.


# Create DataFrame with selecting range of columns 
df2 <- df[,c(1:3,5)]
df2

4. Create DataFrame by Selecting subset of Rows

To create a DataFrame by selecting subset of rows from the existing DataFrame use the below approach. From the following example df[c(1,3,4),] returns rows 1, 3, and 4.


# Create DataFrame with 1,3 and 4 rows 
df2 <- df[c(1,3,4),]
df2

# Output
#  id    name gender        dob state
#1 10     sai      M 1990-10-02    CA
#3 12 deepika      F 1987-06-14    DE
#4 13 sahithi      F 1985-08-16    FL

5. By Selecting Rows & Columns together

using the same approach select the rows and columns together and initialize the DataFrame with the result.


# Create DataFrame with rows 1,3 and 4 and columns 2,4 
df2 <- df[c(1,3,4),c(2,4)]
df2

# Output
#     name        dob
#1     sai 1990-10-02
#3 deepika 1987-06-14
#4 sahithi 1985-08-16

6. By using subset() function

subset() is a R primitive function that is used to select the columns from the DataFrame and assign this result to the variable to create df with the result.


# By using subset with column names
df2 <- subset(df, select=c("id", "gender", "dob"))
df2

# Output
#  id gender        dob
#1 10      M 1990-10-02
#2 11      M 1981-03-24
#3 12      F 1987-06-14
#4 13      F 1985-08-16

You can also use the subset() to select columns by indices.


# By using subset with indices
df2 <- subset(df, select=c(2:3, 5))
df2

Conclusion

In this article, you have learned several examples of how to create a DataFrame from the existing DataFrame in R. When you create from an existing you may be required to select a subset of columns or select only a few rows by filtering. This is one of the most use-cases when we are working with the data.