The goal of this tutorial is to learn how to remove rows from our dataset.
# In this tutorial we are going to use the iris dataset
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 ...# When using dataframes we can call elements with the logic
# Dataframe[ rownumber, colnumber]
# In this case we are calling the first row and first column element
iris[1,1]## [1] 5.1# We can call entire rows using the logic
# Dataframe[ rownumber, ]
iris[5, ]## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 5 5 3.6 1.4 0.2 setosa# At the same time we can use negative numbers to call all rows except the ones we call
# We can see that the row #5 is gone
head(iris[-5, ])## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa# We can use a vector to remove more than one row at the time
# Now rows 1, 4 and 6 are missing
head(iris[ -c(1, 4, 6), ])## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosaIn this tutorial we have learnt how to remove rows from a dataset calling them by number.