# AI – Scatter Plots

• Data Collections
• Scatter Plots
• Graphs

## Data Collection

Collecting data is the most important part of any Machine Intelligence projects.

The most common data to collect are numbers and measurements.

Often data are stored in arrays representing the relationship between values.

This table contains house prices versus size:

## Scatter Plots

Scatter Plot has points scattered over an area representing the relationship between two values.

### Example

var xArray = [50,60,70,80,90,100,110,120,130,140,150];
var yArray = [7,8,8,9,9,9,10,11,14,14,15];

// Define Data
var data = [{
x: xArray,
y: yArray,
mode:”markers”
}];

// Define Layout
var layout = {
xaxis: {range: [40, 160], title: “Square Meters”},
yaxis: {range: [5, 16], title: “Price in Millions”},
title: “House Prices vs. Size”
};

// Display with Plotly
Plotly.newPlot(“myPlot”, data, layout);

Try it Yourself »

## Graphs

Graph can also be used to show the same values:

### Source Code

var xArray = [50,60,70,80,90,100,110,120,130,140,150];
var yArray = [7,8,8,9,9,9,10,11,14,14,15];

// Define Data
var data = [{
x: xArray,
y:yArray,
mode:”lines”
}];

// Define Layout
var layout = {
xaxis: {range: [40, 160], title: “Square Meters”},
yaxis: {range: [5, 16], title: “Price in Millions”},
title: “House Prices vs Size”
};

// Display with Plotly
Plotly.newPlot(“myPlot”, data, layout);

Try it Yourself »

## When to Use Scatter Plots

Scatter plots are great for:

• Seeing the “Big Picture”
• Compare different values
• Discovering potential trends
• Discovering patterns in data
• Discovering relationships between data
• Discovering Clusters and Correlations