Load Data in R – How to load data from a R library

Loading data from a R library is a useful way to access pre-built datasets that are included in various R packages. These libraries usually contains a wide range of datasets that can be used for different types of data analysis and machine learning tasks.

To load data from a R library, you first need to install the library if it’s not already installed. This can be done by using the install.packages() function in R. Once the library is installed, you can load it into your current R session by using the library() function.

Once the library is loaded, you can access the datasets that it contains by using the data() function. This function lists all the datasets that are included in the library, and you can select one to load into your R session.

For example, if you want to load the iris dataset from the datasets library, you can use the command data(iris) after the library(datasets) command.

Once the data is loaded, it will be stored in a data frame, which is a special type of object in R that is used to store and manipulate tabular data. You can then use the data frame to perform various operations, such as filtering, sorting, and aggregating the data.

In summary, loading data from a R library is a useful way to access pre-built datasets that are included in various R packages. To load data from a R library, you first need to install the library if it’s not already installed. Once the library is loaded, you can access the datasets that it contains by using the data() function. Once the data is loaded, it will be stored in a data frame, which is a special type of object in R that is used to store and manipulate tabular data. You can then use the data frame to perform various operations, such as filtering, sorting, and aggregating the data.

In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: How to load data from a R library.