This is part 2 of this data visualization article. If you haven’t read its first part, I would highly suggest you to first read part 1( click here for part 1 ) and then read this.

In this part we will be looking into :

1. Scatter plot (widely used in data science)
2. Line chart
3. Area chart
4. Box & Whisker plot

Lets deep dive into the details of each graph.

1.Scatter plot:

It consists of multiple data points plotted across two axes.

when to use:

• It is used to see whether a pattern to be found between variables.
• It is used to look if there any co-relation exists between two variables or not .

Above scatter plot shows the sales vs profit chart & we clearly see the pattern among these two variables. As sales increased profit of the company also increased.So these two variables are positively co-related.

When to avoid:

• If we don’t have bi-dimensional data.
• Scatter plots are not suitable when you observing time patterns.
• If the data is not numerical we cant use scatterplot.

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2.Line plot:

Line or multiple lines showing how single or multiple variables developed over time.

when to use:

• To track the development of several variables at the same time.

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In above line graph , we can see the Rainfall & temp change over time in one graph .

when to avoid :

• Never use line chart when we want to show how the parts of a whole change over time.

#data-visualization #graph #tableau #data-science #visualization