Explore
For Enterprise
Join for Free
Log In

Arts and Humanities
Business
Computer Science
Data Science
Information Technology
Health
Math and Logic
Personal Development
Physical Science and Engineering
Social Sciences
Language Learning
Degrees
Certificates

Explore all of Coursera

Browse
Search
For Enterprise
Log In
Join for Free

Charting Guidelines: Bar Charts, Line Graphs, Pie Charts

Loading...

Visual Analytics with Tableau

University of California, Davis

4.5 (879 ratings) | 18K Students Enrolled

Course 3 of 5 in the Data Visualization with Tableau Specialization

In this third course of the specialization, we’ll drill deeper into the tools Tableau offers in the areas of charting, dates, table calculations and mapping. We’ll explore the best choices for charts, based on the type of data you are using. We’ll look at specific types of charts including scatter plots, Gantt charts, histograms, bullet charts and several others, and we’ll address charting guidelines. We’ll define discrete and continuous dates, and examine when to use each one to explain your data. You’ll learn how to create custom and quick table calculations and how to create parameters. We’ll also introduce mapping and explore how Tableau can use different types of geographic data, how to connect to multiple data sources and how to create custom maps.

Skills You'll Learn

Visual Analytics, Map, Tableau Software, Data Visualization (DataViz)

Reviews

4.5 (879 ratings)

5 stars
574 ratings
4 stars
235 ratings
3 stars
49 ratings
2 stars
11 ratings
1 star
10 ratings

AS

May 18, 2019

It was effective and simple to learn few concepts which can be fruitful for my future projects. However calculated fields should have been discussed more in detail.

SW

Jan 03, 2018

So Far, This is a Very Good course design. However, if it is possible, more practice assignment will be much better for learning and improving the skill.

From the lesson

Getting Started and Charting

In this module, you will explore the topic of charting in Tableau. By now you should already be well versed in how to change colors, shapes, and sizes of charts, so we are going to practice and demonstrate that skill more. You will be able to explain what the Tableau Tooltip does and when to use it. You will be able to discuss the various guidelines for choosing the right chart for your data. You will also create a chart using Tableau.

Introduction to Charting1:15

Tableau Charts19:03

Colors, Shapes, and Sizes4:48

Dual Line Charts3:08

Tableau Tooltip4:42

Charting Guidelines: Bar Charts, Line Graphs, Pie Charts6:48

Charting Guidelines: Maps, Scatter Plots, Gantt Charts, Bubble Charts4:59

Charting Guidelines: Histograms, Bullet Charts, Heat Maps and Highlight Tables4:45

Charting Guidelines: Treemaps and Box-and-Whisker Plots5:30

Taught By

Suk S. Brar, M.B.A.
Lead Business Consultant

Transcript

[MUSIC]

Welcome to this lesson in the module on charting.

I have put together some guidelines for the various charts that tableau offers and

ended up having to split the lesson into several parts.

This really is one large lesson.

But before I introduce it, let's review what we have learned so far.

We've covered the different types of charts available in tableau and

how to change their colors, shapes and sizes.

We've also discussed how to create dual layer charts and

how to use a tableau tooltip.

Now in this final set of videos,

we will focus on some guidelines you consider while creating your charts.

After you finish this lessons, you will be able to identify questions you should ask

before choosing a chart type and determine the purpose for your visualization and

you will be able to select the best charts to visualize what you're trying to say.

There's a lot to cover, so let's get started.

The place you start is with questions.

From the outset, ask yourself, what am I trying to say?

The single most important step you can take to make

a great visualization is to know what you're trying to say.

With the amount of data available today,

anyone can get lost in a world of scatter plots and geocoding.

It is vital that your visualization has a purpose and that you are selective

about what you include in your visualization to fulfill that purpose.

How do you know if your visualization has a purpose?

Well, ask some questions to find out.

Who is your audience?

What questions do they have?

What answers do you want to highlight for them?

What other questions might your visualization inspire?

What conversations may result?

The point is that your viewers should take something away from the time they spend

with your visualization Your next

order of business is to choose the right chart type.

Once you have a purpose for your visualization in mind, it is time to think

about what types of analysis will help you achieve that purpose.

You are looking to gain some guidelines that will indicate when to

use one kind of chart type rather than another.

Hopefully, these guidelines will help you with these decisions.

Choosing the right type of chart or graph visualization can be key to conveying

the most important insights in your data on site.

Let's revisit some of the charts available in tableau and I will

offer some guidelines or best practices regarding when to use that type of chart.

Let's start with the bar chart.

Bar charts are one of the most common ways to visualize data.

Why?

It's quick to compare information revealing highs and lows at glance.

Bar charts are especially effective when you have numerical data that splits nicely

into different categories, so you can quickly see trends within your data.

Here are guidelines for when to use bar charts.

When comparing data across categories.

For example, when you are looking to show volume of shirts in different sizes,

website traffic by origination site or percent of spending by department.

Include multiple bar charts on dashboard.

This helps the VR quickly compare related information instead of flipping

through a bunch of spreadsheet or slides to answer a question.

When adding color to bars, it imparts more impact.

Showing revenue performance with bars is informative, but

overlaying color to a profitability provides immediate insight.

When you can use stacked bars or side by side bars.

Displaying related data on top of or next to each other gives depth to your analysis

and addresses multiple questions at once.

When you can combine bar charts with maps.

Set the map to act as a filter.

So when you click on different regions, the corresponding bar

chart is displayed and when you can put bars on both sides of an axis.

Plotting both positive and

negative data points along a continuous axis is an effective way to spot trends.

Next, let's look at guidelines regarding line charts.

Line charts are right up there with bars and

pie charts as one of the most frequently used chart types.

Line charts connect individual numeric data points.

The result is a simple, straightforward way to visualize a sequence of values.

The primary use of a line chart is to display trends over a span of time.

Here are guidelines for when to use line charts.

When viewing trends and data over time.

For example, to show how stock prices change over a five-year period,

displaying website page views during a month or revenue growth by quarter.

When you can combine a line graph with bar charts.

A bar chart indicating the volume sold per day of a given stock combined with

a line graph of the corresponding stock price can provide visual queues for

further investigation.

When it makes sense to shade the area underlines.

When you have two or more line charts,

fill the space under the respective chart to create an area chart.

This can inform a viewer about the relative contribution that line

contributes to the whole.

Next, let's look at guidelines regarding pie charts.

Pie charts should be used to show relative proportions or percentages of information.

That's it.

Despite this narrow recommendation for when to use pies,

they are made with abandon.

As a result, they are the most commonly misused chart type.

If you're trying to compare data, leave it to bars or stacked bars.

Don't ask your viewer to translate pie wedges into relevant data or

compare one pie to another.

Key points from your data will be missed and the reader has to work too hard.

Here are guidelines regarding pie charts.

Use a pie chart when showing proportions.

For example, percentage of budget on different departments.

Response categories from a survey or

a breakdown of how Americans spend their leisure time.

Limit pie wedge to six.

If you have more than six proportions to communicate,

consider a bar chart instead of a pie chart.

It becomes too hard to interpret the pie pieces meaningfully when

the number of wedges exceeds six.

Consider overlaying pie charts on maps.

Pies can be an interesting way to highlight geographical trends

in your data.

If you choose to use this technique,

use pies with only a couple of wedges to keep it easy to understand.

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.

Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online.

© 2019 Coursera Inc. All rights reserved.

Download on the App Store

Get it on Google Play

Coursera
About
Leadership
Careers
Catalog
Certificates
MasterTrack™ Certificates
Degrees
For Enterprise
For Government

Community
Learners
Partners
Developers
Beta Testers
Translators

Connect
Blog
Facebook
LinkedIn
Twitter
Instagram
YouTube
Tech Blog

More
Terms
Privacy
Help
Accessibility
Press
Contact
Directory
Affiliates