The goal of this tutorial is to learn how to split a dataframe into several dataframes by the value of one column. This could be useful if we want to perform analysis in a certain subset of a dataset.
# In this tutorial we are going to use the iris dataset
# We will count the amount of plants of each Species
data("iris")
str(iris)## 'data.frame': 150 obs. of 5 variables:
## $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
## $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
## $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
## $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
## $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...# We can split the table by the species getting 3 different datasets
iris_split <- split(iris, iris$Species)
# We can see that three datasets have been created
str(iris_split)## List of 3
## $ setosa :'data.frame': 50 obs. of 5 variables:
## ..$ Sepal.Length: num [1:50] 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
## ..$ Sepal.Width : num [1:50] 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
## ..$ Petal.Length: num [1:50] 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
## ..$ Petal.Width : num [1:50] 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
## ..$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ versicolor:'data.frame': 50 obs. of 5 variables:
## ..$ Sepal.Length: num [1:50] 7 6.4 6.9 5.5 6.5 5.7 6.3 4.9 6.6 5.2 ...
## ..$ Sepal.Width : num [1:50] 3.2 3.2 3.1 2.3 2.8 2.8 3.3 2.4 2.9 2.7 ...
## ..$ Petal.Length: num [1:50] 4.7 4.5 4.9 4 4.6 4.5 4.7 3.3 4.6 3.9 ...
## ..$ Petal.Width : num [1:50] 1.4 1.5 1.5 1.3 1.5 1.3 1.6 1 1.3 1.4 ...
## ..$ Species : Factor w/ 3 levels "setosa","versicolor",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ virginica :'data.frame': 50 obs. of 5 variables:
## ..$ Sepal.Length: num [1:50] 6.3 5.8 7.1 6.3 6.5 7.6 4.9 7.3 6.7 7.2 ...
## ..$ Sepal.Width : num [1:50] 3.3 2.7 3 2.9 3 3 2.5 2.9 2.5 3.6 ...
## ..$ Petal.Length: num [1:50] 6 5.1 5.9 5.6 5.8 6.6 4.5 6.3 5.8 6.1 ...
## ..$ Petal.Width : num [1:50] 2.5 1.9 2.1 1.8 2.2 2.1 1.7 1.8 1.8 2.5 ...
## ..$ Species : Factor w/ 3 levels "setosa","versicolor",..: 3 3 3 3 3 3 3 3 3 3 ...# Now we can create the different dataframes
iris_setosa <- iris_split$setosa
iris_versicolor <- iris_split$versicolor
iris_virginica <- iris_split$virginica
# Let's check the content of this new datasets
str(iris_setosa)## 'data.frame': 50 obs. of 5 variables:
## $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
## $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
## $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
## $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
## $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...str(iris_versicolor)## 'data.frame': 50 obs. of 5 variables:
## $ Sepal.Length: num 7 6.4 6.9 5.5 6.5 5.7 6.3 4.9 6.6 5.2 ...
## $ Sepal.Width : num 3.2 3.2 3.1 2.3 2.8 2.8 3.3 2.4 2.9 2.7 ...
## $ Petal.Length: num 4.7 4.5 4.9 4 4.6 4.5 4.7 3.3 4.6 3.9 ...
## $ Petal.Width : num 1.4 1.5 1.5 1.3 1.5 1.3 1.6 1 1.3 1.4 ...
## $ Species : Factor w/ 3 levels "setosa","versicolor",..: 2 2 2 2 2 2 2 2 2 2 ...str(iris_virginica)## 'data.frame': 50 obs. of 5 variables:
## $ Sepal.Length: num 6.3 5.8 7.1 6.3 6.5 7.6 4.9 7.3 6.7 7.2 ...
## $ Sepal.Width : num 3.3 2.7 3 2.9 3 3 2.5 2.9 2.5 3.6 ...
## $ Petal.Length: num 6 5.1 5.9 5.6 5.8 6.6 4.5 6.3 5.8 6.1 ...
## $ Petal.Width : num 2.5 1.9 2.1 1.8 2.2 2.1 1.7 1.8 1.8 2.5 ...
## $ Species : Factor w/ 3 levels "setosa","versicolor",..: 3 3 3 3 3 3 3 3 3 3 ...In this tutorial we have learnt how to create new datasets subsetting by the value of one of the variables using the split function.