# R Console

## Trending

#### R Console

## Manipulating Columns of Data

Using some basic functions within R, it's possible to create a small dataset and manipulate columns within the dataset to make it easier to work with, such as: dropping columns multiplying columns assigning names to columns, loading columns into new dataframes

#### R Console

## Performing a LASSO Regression

Using some basic R functions, you can easily perform a Least Absolute Shrinkage and Selection Operator regression (LASSO) and create a scatterplot comparing predicted results vs. actual results. In this example the mtcars dataset contains data on fuel consumption for 32 vehicles manufactured in the 1973-1974 model year. This example compares actual fuel consumption to predicted fuel consumption using a LASSO regression.

#### R Console

## Performing an OLS Regression

Using some basic R functions, you can easily perform an Ordinary Least Squares (OLS) regression and create a scatterplot comparing predicted results vs. actual results. In this example the mtcars dataset contains data on fuel consumption for 32 vehicles manufactured in the 1973-1974 model year. This example compares actual fuel consumption to predicted fuel consumption using an OLS regression.

#### R Console

## Simple Operations on a Data Frame

You can perform some simple tabulations on a data frame by using some basic commands within R to load calculations applied against the dataset into columns, then printing them. In this example the mtcars dataset contains data on fuel consumption for 32 vehicles manufactured in the 1973-1974 model year. The output contains computed correlations between pairs of columns.

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