DATA VISUALIZATION AND IT'S TECHNIQUES

Introduction :-

A picture is worth a thousand words- especially when you are trying to understand and gain insights from data. It is especially revalant when you re trying to find relationships among thousands or even millions of variables and determine their relative importance.

To create meaningful visuals of our data,there are some tips amd techniques we should consider.Data size and column composition play an important role when selecting graps to represent our data.This article discusses some of the basic issues concerning data visualization and provides suggestions for addressing those issues.

Data Visualization :-

Data visualization is defined as a graphical representation that contains the information and the data .

It is used in many areas such as:-

* To model Complex events.

* Visualize phenomenone that cannot be observed directly,such as weather patterns,medical conditions.

Types of Analysis for Data Visualization :-

There are three different types of analysis for data visualization

Univariate Analysis :-

In the univariate analysis, we will be using a single feature to analyze almost all its properties.

1.Distribution Plot

2.Box and Whisker Plot

3.Violin Plot

Bivariate Analysis :-

When we compare the data between exactly 2 features then it is known as bivariate analysis.

1.Line plot

2.Bar Plot

3.Scatter Plot

Multivaraite Analysis :-

In the multivariate analysis, we will be comparing more than 2 varaiables