which type of chart is the least appropriate

which type of chart is the least appropriate

which type of chart is the least appropriate

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Which Type of Chart or Graph is Right for You?

Bar Chart

Bar charts are one of the most common data visualizations. You can use them to quickly compare data across categories, highlight differences, show trends and outliers, and reveal historical highs and lows at a glance. Bar charts are especially effective when you have data that can be split into multiple categories.

Line Chart

The line chart, or line graph, connects several distinct data points, presenting them as one continuous evolution. Use line charts to view trends in data, usually over time (like stock price changes over five years or website page views for the month). The result is a simple, straightforward way to visualize changes in one value relative to another.

which type of chart is the least appropriate
which type of chart is the least appropriate

Pie Chart

Pie charts are powerful for adding detail to other visualizations. Alone, a pie chart doesn’t give the viewer a way to quickly and accurately compare information. Since the viewer has to create context on their own, key points from your data are missed. Instead of making a pie chart the focus of your dashboard, try using them to drill down on other visualizations.

Maps

Maps are a no-brainer for visualizing any kind of location information, whether it’s postal codes, state abbreviations, country names, or your own custom geocoding. If you have geographic information associated with your data, maps are a simple and compelling way to show how location correlates with trends in your data.

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Density Maps

The Density maps reveal patterns or relative concentrations that might otherwise be hidden due to an overlapping mark on a map—helping you identify locations with greater or fewer numbers of data points. Density maps are most effective when working with a data set containing many data points in a small geographic area.

Scatter Plot

Scatter plots are an effective way to investigate the relationship between different variables, showing if one variable is a good predictor of another, or if they tend to change independently. A scatter plot presents lots of distinct data points on a single chart. The chart can then be enhanced with analytics like cluster analysis or trend lines.

Gantt Chart

Gantt charts display a project schedule or show changes in activity over time. A Gantt chart shows steps that need to be completed before others can begin, along with resource allocation.

Bubble Chart

Although bubbles aren’t technically their own type of visualization, using them as a technique adds detail to scatter plots or maps to show the relationship between three or more measures. Varying the size and color of circles creates visually compelling charts that present large volumes of data at once.

Treemap

Treemaps relate different segments of your data to the whole. As the name of the chart suggests, each rectangle in a treemap is subdivided into smaller rectangles, or sub-branches, based on its proportion to the whole. They make efficient use of space to show percent total for each category.

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Spider Charts

When a statistician needs to visually compare three or more quantitative variables,

he or she might choose to use a radar chart, also known as a spider or star chart.

The chart usually consists of a series of radii, each representing a different category, that splay out from a center point like spokes.

The length of each “spoke” is proportionate to the value being compared. For each category,

the spokes are then connected with a line of a designated pattern or color,

forming a star-like shape with points equal to the number of categories.

The result is a graphic representation that can reveal trends and compare categories all at the same time.

which type of chart is the least appropriate
Types of Graph And when to use them!

Population Pyramids

arket segments are often divided based on age and gender, and a population pyramid is an ideal visual representation of the two groups.

The graph classically takes on the shape of a pyramid when a population is healthy and growing —

the largest groups are the youngest, and each gender dwindles somewhat equally as the population ages, leaving the smallest groups at the top of the graph.

A population pyramid that veers away from its classic shape might indicate an irregularity in a population during a particular period,

such as a famine or an economic boom that led to an increase in deaths or births.

Of course, population pyramids aren’t always used to compare populations by age, and therefore don’t always take on the graph’s namesake shape.

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