List of Dataframes in R
Last Updated :
01 Jul, 2021
DataFrames are generic data objects of R which are used to store the tabular data. They are two-dimensional, heterogeneous data structures. A list in R, however, comprises of elements, vectors, data frames, variables, or lists that may belong to different data types. In this article, we will study how to create a list consisting of data frames as its components and how to access, modify, and delete these data frames to lists. list() function in R creates a list of the specified arguments. The data frames specified as arguments in this function may have different lengths.
Operations that can be performed on a list of DataFrames are:
- Creating a list of Dataframes
- Accessing components of a list of Dataframes
- Modifying components of a list of Dataframes
- Concatenation of lists of Dataframes
- Deleting components of a list of Dataframes
Creating a list of Dataframes
To create a list of Dataframes we use the list() function in R and then pass each of the data frame you have created as arguments to the function.
Example:
Python3
df1 = data.frame(
y1 = c( 1 , 2 , 3 ),
y2 = c( 4 , 5 , 6 )
)
df2 = data.frame(
y1 = c( 7 , 8 , 9 ),
y2 = c( 1 , 4 , 6 )
)
listOfDataframe = list (df1, df2)
print (listOfDataframe)
|
Output:
[[1]]
y1 y2
1 1 4
2 2 5
3 3 6
[[2]]
y1 y2
1 7 1
2 8 4
3 9 6
Accessing components of a list of Dataframes
We can access components of a list of data frames in two ways.
- Access components by names: All the components of a list of data frames can be named and we can use those names to access the components of the list using the dollar command.
Example:
Python3
df1 = data.frame(
y1 = c( 1 , 2 , 3 ),
y2 = c( 4 , 5 , 6 )
)
df2 = data.frame(
y1 = c( 7 , 8 , 9 ),
y2 = c( 1 , 4 , 6 )
)
listOfDataframe = list (
"Dataframe1" = df1,
"Dataframe2" = df2
)
print (listOfDataframe)
cat( "Accessing Dataframe2 using $ command\n" )
print (listOfDataframe$Dataframe2)
|
$Dataframe1
y1 y2
1 1 4
2 2 5
3 3 6
$Dataframe2
y1 y2
1 7 1
2 8 4
3 9 6
Accessing Dataframe2 using $ command
y1 y2
1 7 1
2 8 4
3 9 6
-
- Access components by indices: We can also access the components of the list of data frames using indices. To access the top-level components of a list of data frames we have to use a double slicing operator “[[ ]]” which is two square brackets and if we want to access the lower or inner level components of a list we have to use another square bracket “[ ]” along with the double slicing operator “[[ ]]”.
Example:
Python3
df1 = data.frame(
y1 = c( 1 , 2 , 3 ),
y2 = c( 4 , 5 , 6 )
)
df2 = data.frame(
y1 = c( 7 , 8 , 9 ),
y2 = c( 1 , 4 , 6 )
)
listOfDataframe = list (
"Dataframe1" = df1,
"Dataframe2" = df2
)
print (listOfDataframe)
cat( "Accessing Dataframe2 using indices\n" )
print (listOfDataframe[[ 2 ]])
cat( "Accessing second column from Dataframe1 using indices\n" )
print (listOfDataframe[[ 1 ]][ 2 ])
cat( "Accessing 4 from Dataframe2 using indices\n" )
print (listOfDataframe[[ 2 ]][ 2 , 2 ])
|
$Dataframe1
y1 y2
1 1 4
2 2 5
3 3 6
$Dataframe2
y1 y2
1 7 1
2 8 4
3 9 6
Accessing Dataframe2 using indices
y1 y2
1 7 1
2 8 4
3 9 6
Accessing second column from Dataframe1 using indices
y2
1 4
2 5
3 6
Accessing 4 from Dataframe2 using indices
[1] 4
Modifying components of a list of Dataframes
A list of data frames can also be modified by accessing the components and replacing them with the ones which you want.
Example:
Python3
df1 = data.frame(
y1 = c( 1 , 2 , 3 ),
y2 = c( 4 , 5 , 6 )
)
df2 = data.frame(
y1 = c( 7 , 8 , 9 ),
y2 = c( 1 , 4 , 6 )
)
listOfDataframe = list (
"Dataframe1" = df1,
"Dataframe2" = df2
)
cat( "Before modifying the list of data frame\n" )
print (listOfDataframe)
listOfDataframe$Dataframe2 = data.frame(
y1 = c( 70 , 80 , 9 ),
y2 = c( 14 , 41 , 63 )
)
listOfDataframe[[ 1 ]][ 2 ] = c( 23 , 45 , 67 )
listOfDataframe[[ 1 ]][ 2 , 1 ] = 15
cat( "After modified the list of data frame\n" )
print (listOfDataframe)
|
Output:
Before modifying the list of data frame
$Dataframe1
y1 y2
1 1 4
2 2 5
3 3 6
$Dataframe2
y1 y2
1 7 1
2 8 4
3 9 6
After modified the list of data frame
$Dataframe1
y1 y2
1 1 23
2 15 45
3 3 67
$Dataframe2
y1 y2
1 70 14
2 80 41
3 9 63
Concatenation of lists of Dataframes
Two lists of data frames can be concatenated using the concatenation function. So, when we want to concatenate two lists of data frames we have to use the concatenation operator.
Syntax:
list = c(list, list1)
list = the original list of the data frame
list1 = the new list of the data frame
Example:
Python3
df1 = data.frame(
y1 = c( 1 , 2 , 3 ),
y2 = c( 4 , 5 , 6 )
)
df2 = data.frame(
y1 = c( 7 , 8 , 9 ),
y2 = c( 1 , 4 , 6 )
)
listOfDataframe = list (
"Dataframe1" = df1,
"Dataframe2" = df2
)
cat( "Before concatenation of the new list of data frame\n" )
print (listOfDataframe)
df3 = data.frame(
y1 = c( 7 , 8 , 98 ),
y2 = c( 10 , 44 , 6 )
)
newListOfDataframe = list (
"Dataframe3" = df3
)
listOfDataframe = c(listOfDataframe, newListOfDataframe)
cat( "After concatenation of the new list of data frame\n" )
print (listOfDataframe)
|
Output:
Before concatenation of the new list of data frame
$Dataframe1
y1 y2
1 1 4
2 2 5
3 3 6
$Dataframe2
y1 y2
1 7 1
2 8 4
3 9 6
After concatenation of the new list of data frame
$Dataframe1
y1 y2
1 1 4
2 2 5
3 3 6
$Dataframe2
y1 y2
1 7 1
2 8 4
3 9 6
$Dataframe3
y1 y2
1 7 10
2 8 44
3 98 6
Deleting components from a list of Dataframes
To delete components of a list of data frames, first of all, we need to access those components and then insert a negative sign before those components. It indicates that we had to delete that component.
Example:
Python3
df1 = data.frame(
y1 = c( 1 , 2 , 3 ),
y2 = c( 4 , 5 , 6 )
)
df2 = data.frame(
y1 = c( 7 , 8 , 9 ),
y2 = c( 1 , 4 , 6 )
)
listOfDataframe = list (
"Dataframe1" = df1,
"Dataframe2" = df2
)
cat( "Before deletion the list is\n" )
print (listOfDataframe)
cat( "After Deleting Dataframe1\n" )
print (listOfDataframe[[ - 1 ]])
cat( "After Deleting first column from Dataframe2\n" )
print (listOfDataframe[[ 2 ]][ - 1 ])
|
Output:
Before deletion the list is
$Dataframe1
y1 y2
1 1 4
2 2 5
3 3 6
$Dataframe2
y1 y2
1 7 1
2 8 4
3 9 6
After Deleting Dataframe1
y1 y2
1 7 1
2 8 4
3 9 6
After Deleting first column from Dataframe2
y2
1 1
2 4
3 6
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