Load Data in R – How to load data from a csv file in R

Loading data from a CSV file in R is a common task in data analysis and machine learning. CSV stands for Comma Separated Values and it is a plain text file format that is used to store data in a tabular form.

In R, there are several ways to load data from a CSV file, but the most common one is using the read.csv() function. This function is included in the base R package and it is used to read a CSV file and create a data frame with the contents of the file.

When using the read.csv() function, you need to specify the path of the CSV file and some additional parameters, such as the separator character, the number of rows to skip, and the character encoding.

You can also use the read.table() function with sep=”,” as an argument, it does the same thing as read.csv() but its more general and can load data from other delimiter files as well.

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 CSV file in R is a common task in data analysis and machine learning. CSV stands for Comma Separated Values and it is a plain text file format that is used to store data in a tabular form. In R, you can use the read.csv() function or the read.table() function with sep=”,” as an argument to load the data from a CSV file. This function reads the CSV file and creates a data frame with the contents of the file. 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.

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 csv file in R.