The graphical representation of data suggests presenting the data distribution visually. It shows numerical data in an attractive visual or graphic manner to infer the most with a quick glance at it. To present data in a graphical form, we often use graphs, plots and charts of various types.

Benefits of presenting data graphically:

**Ease of Interpretation:**We can quickly draw out results without thorough knowledge about the dataset.**Comparison of data:**We can easily compare different aspects of the data set with graphically represented data.**Future predictions:**Prediction of future trends becomes very easy.

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## Types of Graphical Representation of Data

There are different types of graphical representation based on whether they are represented in graphs, charts, or tables. Data is represented using Bar Charts, Histogram, Line Graphs, Pie Charts, Pictographs, Frequency Distribution Graphs, Scatter Plot etc.

## Pictographs

A particular picture or symbol is used as a token to designate single data or several data of a dataset. For example, graphically representing the data of the number of cars parked in a parking lot during the week can be described as a pictograph, where a symbol may represent 5 to 10 cars; later on, this may be used to draw various inferences and trends.

## Histograms

A histogram represents a continuous frequency distribution of grouped or ungrouped data. In a histogram, bars are made without any gap between them, such that the height of the bar represents the frequency of the data and the width of the bar represents the class width.

Some important facts regarding histograms:

- Graphical representation of continuous frequency distribution
- There should be no gaps between corresponding bars
- Significance of height and width of the bars – height represents the frequency of the data distribution whereas width represents the class width or length of the class interval.
- Generally, the horizontal axis of the graph represents the class intervals of the distribution, and the vertical axis represents the frequency of the data distribution.
- It is not required to begin with 0 for both the axes; sometimes, a kink or break on the axis represents values not shown in the graph.
- If the class intervals are uniform, then the area of bars is directly proportional to the frequency of the corresponding class interval.
- If the class intervals are not uniform, then the height of the rectangle will be directly proportional to the ratio of frequencies to the width of class intervals.

## Bar Graphs

A Bar graph or bar chart represents data with rectangles of uniform width, which are called bars such that the height or length of the bars describes the frequency of a particular data. These bars can be made horizontally or vertically, depending on our choice. If vertical bars are made, then the horizontal axis represents the data, and the vertical axis represents the frequency of that data; for horizontal bars, it’s just the opposite. In a Bar Chart, bars are made with a uniform gap between them, representing discrete data distribution.

- Graphical representation of data by plotting bars of uniform width with equal gaps between them.
- The height of the bars is proportional to the frequency of the data, whereas width has no particular significance, but for the sake of uniformity, rectangles are made of equal width.
- All bars must be on a common axis.

## Pie Charts

Pie charts or circular charts represent data in the form of sectors of a circle. The area of the sector represents the frequency of the data distribution. It is a common visual way to describe data that could be understood by a layman.

- Circular representation of data distribution.
- The area of the sectors represents the frequency of the data.
- The angle of the sector depends upon the frequency.
- The various parts or slices of the pie chart show the relationship with the whole.