Summarise Data in R – How to know dimention of a dataset in R

In R, it is important to know the dimensions of a dataset, such as the number of rows and columns, to ensure that it is properly formatted and ready for analysis.

To check the dimensions of a dataset in R, you can use the dim() function. This function takes a data frame or a matrix as an argument and returns the number of rows and columns in the dataset.

For example, if you have a dataset called “data”, you can check its dimensions by using the command dim(data)

Another way of checking the dimensions of a dataset is by using the nrow() and ncol() functions. The nrow() function returns the number of rows in the dataset, and the ncol() function returns the number of columns in the dataset.

For example, if you have a dataset called “data”, you can check the number of rows and columns by using the command nrow(data) and ncol(data) respectively.

In summary, In R, it is important to know the dimensions of a dataset, such as the number of rows and columns, to ensure that it is properly formatted and ready for analysis. To check the dimensions of a dataset, you can use the dim() function, which takes a data frame or a matrix as an argument and returns the number of rows and columns in the dataset. Alternatively, you can use the nrow() and ncol() functions to check the number of rows and columns respectively in the dataset.

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 know dimention of a dataset in R.

Summarise Data in R – How to know dimention of a dataset in R

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