Summarise Data in R – How to get summary statistics in R

In R, summary statistics are a set of measures that provide a quick and easy way to understand the main characteristics of a dataset. These measures include measures of central tendency (such as mean and median) and measures of variability (such as standard deviation and range).

In R, you can easily get a summary of statistics for a dataset by using the summary() function. This function takes a data frame or a numeric vector as an argument, and returns a summary of the main statistics for the dataset, including the mean, median, standard deviation, minimum and maximum values, and the number of observations.

For example, if you have a dataset called “data”, you can get a summary of statistics for the dataset by using the command summary(data)

In addition to the summary() function, in R, there are other functions such as min(), max(), range(), quantile() that can give you specific summary statistics of a dataset.

In summary, In R, summary statistics are a set of measures that provide a quick and easy way to understand the main characteristics of a dataset. These measures include measures of central tendency (such as mean and median) and measures of variability (such as standard deviation and range). The summary() function can give you a quick summary of statistics for a dataset by taking a data frame or a numeric vector as an argument and returning the mean, median, standard deviation, minimum and maximum values, and the number of observations. Additionally, R provides other functions such as min(), max(), range(), quantile() that can give you specific summary statistics of a 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 get summary statistics in R.

 

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