# How to visualise Dataset in R

Visualizing a dataset in R is an important step in understanding the underlying patterns and relationships in the data. There are various data visualization techniques and packages available in R, such as ggplot2, lattice, and base R plotting functions. Some of the most commonly used visualizations in R include:

**Bar charts:** Bar charts are used to compare the values of different categories or groups. They are useful for comparing the distribution of categorical variables.

**Line charts:** Line charts are used to show trends over time. They are useful for visualizing the change in a variable over time.

**Scatter plots:** Scatter plots are used to show the relationship between two or more variables. They are useful for understanding the correlation between variables.

**Histograms:** Histograms are used to show the distribution of a numerical variable. They are useful for understanding the distribution of a variable and identifying outliers.

**Box plots:** Box plots are used to show the distribution of a numerical variable and identify outliers. They are useful for comparing the distribution of a variable across different groups or categories.

It’s important to note that the type of visualization used will depend on the type of data and the question you’re trying to answer. Also, it’s important to keep the visualization simple and clear, this will make it easy to understand the insights from the data.

In this Data Science Recipe, you will learn: How to visualise Dataset in R.

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