How to visualize the data using data charts or graphs?

Prasann patil
3 min readOct 21, 2020

· Why data visualization important?

Which is very helpful for evaluating modelling output of data, data cleaning, exploring the data, detecting of unusual data. Data visualization tool can be used in a verities ways Business intelligence is one of the trending tools of these days. User can set up visualization tools to generate automatic dash boards so that he can know the performance of different organizations so easily.

· Different types of charts to visualize the data?

Column Chart

Bar Chart

Line Chart

Tree Map

Pie Chart

Heat Map

Scatter Chart

Mekko Chart

Bubble Chart

Waterfall Chart

Historical Chart

Bullet Chart

Dual Axis Chart

Bubble Chart etc.

Scenarios to use different charts:

1. Compare values:

Charts are perfect for compare one or more values and data analyst can get low or high values in the data set.to create a comparison chart can use following graphs:

Column, Mekko, Bar, Pie, Line, Scatter plot, Bullet.

2. Composition of values:

In which chart to show how individual to make up, whole of something. To create composition of values can use following types of charts:

Pie, Bar, Column, Area, waterfall.

3. Distribution of data:

Can get outlier of normal tendency and range of information in values. To create distribution of data can use following types of charts:

Scatterplot, line, column, Bar.

4. Analysing trends in data set:

Analyst can get to know how a data set performed during a specific time period. Can use following charts:

Line, Dual axis line, column.

5. Understand relationship between value sets:

In which chart helps to know the relation between different values shows how the value related to other values and shows how positively effects on the other variables. Can use following charts:

Scatterplot, bubble, line.

· How charts look like:

Fig1. Column chart
Fig2. Bar chart
Fig3. Tree map
Fig4. Pie chart
Fig5. Heat map
Fig6. Scatter chart

· Design best practices

1. Avoid distortion

2. Should not skip values

3. Simplify less information data

4. Do be creative data label and legend

5. Don’t use 3D effects

6. Don’t use more than six colours

7. Shouldn’t overload the chart

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Prasann patil

I am mechanical engineer from KLE technological university, Hubli. and intersted in software engineering, integrating core and software skill brings innovation