Introduction to Data Visualization in R

What is Data Visualization?

Data Visualization is an approach for summarizing and visualizing the important characteristics and statistical properties of a Dataset.

Once we get a Dataset, especially a big one, the first question that arises is what is there in the dataset and if there is any pattern in the Data. The best approach to answer this question is Data Visualization. It helps to form an intuition about the data before starting any formal methods. Also, Data Visualisation is important to tell stories about the Data.
Based on this concept, Data Visualization can be divided into 2 types:

1. Exploratory
2. Explanatory

Exploratory Data Visualization:

Easily Generated and intended for a small audience. It mainly involves Exploring the Data for our own understanding.

Explanatory Data Visualization:

Labor intensive and intended for a broader audience. It involves Explaining our understanding of the Data to an audience like in a presentation.

R supports both of the above types of Visualization and provides many useful tools for the same. Some basic graphs can be created using the plot command. It takes in many parameters like x-axis data, y-axis data, x-axis label, y-axis labels, color, and title.

We can create the below graphs in R:

  1. Line Plot
  2. Bar Plot
  3. Box plot
  4. Scatter plot
  5. Histogram
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