3. R programming language in Data science

Data Visualization in R language

R has powerful graphics packages that help in data visualization. These graphics can be viewed on the screen, and saved in various formats, including .pdf, .png, .jpg, .wmf and .ps. It can be customized according to various graphic needs and enables you to copy and paste in Word or PowerPoint files.

You can create a bar chart, pie chart, histogram, kernel density plot, line chart, boxplot, heat map, and word cloud.

Let’s look at boxplots in R.

Boxplots are also known as whisker diagrams. They will display the distribution of data based on the following parameters:

  • Minimum
  • First quartile
  • Median
  • Third quartile
  • Maximum

To create a boxplot, you need to provide a boxplot(data).


The line at the bottom of the box is the minimum value, and the line of the top of the box is the maximum value. The dark line inside the box is the median value, and the points lying outside the box are outliers.

Now that you know more about data visualization in R, let’s jump into learning the different phases of the data science life cycle.

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