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

Tableau Charts

Loading...

Visual Analytics with Tableau

University of California, Davis

4.5 (839 ratings) | 18K Students Enrolled

Course 1 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 (839 ratings)

5 stars
543 ratings
4 stars
228 ratings
3 stars
47 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 the first lesson in the Explaining Your Data using Tableau course.

In this lesson,

we will focus on the various types of charts Tableau allows you to use.

I will show the different types of charts that are available within Tableau and

illustrate how to create different types of charts.

After this lesson, you will be able to list the various

types of charts in Tableau and explain how to create a chart within Tableau.

Let me show you what I mean.

From the Tableau home page, look at the Show Me menu.

Here you can see the entire selection of chart types.

If you mouse over each chat type Tableau will offer guidance on which chart type is

best suited for the data you're trying to present.

For example.

For stacked bars, Tableau recommends one or more dimensions and one or

more measures.

Chart types that are not applicable to your worksheet

as it is currently constructed will be grayed out and not selectable.

Until you have the appropriate combination of measures and or dimensions.

The different chart types that Tableau allows you to use include text tables,

which are also cross tabs, heat maps, highlight tables, symbol maps, field maps,

pie charts, horizontal bar charts, stacked bar charts, side by side bar charts.

Tree maps, circle views, side by side circle views, line charts both

continuous and discrete, dual line charts, area charts both continuous and

discrete, scatter plots, histograms, box and whisker plots.

Gantt charts, bullet graphs and finally pack bubbles.

Let's look at each of this in term.

First, is the text table.

The text table also know as the cross tabs,

is essentially same view you would see from Excel data source.

Or by clicking the view data button On in the side bar.

The mark type is texts.

And the data is organized simply into rows and columns.

While text tables are applicable to most data sets.

They do not tell a very compelling story.

Nor do they highlight important pieces of your data without

additional formatting on your part.

Text tables are not normally recommended

as a primary visualization in your dashboard or presentation.

Consider using them as an appendix inclusion for

those report consumers that want more detail in a traditional format.

To create a text table, using our superstore dataset,

let's drag the region to the our row shelf.

Then let's also drag our customers segment to the real shelf.

Let's also drag our older date onto the column shelf.

And finally, let's add profit.

Now you have a close tabs showing profit from 2012 through 2015,

for each customer segment and for each region.

The next chart is the heat map.

To take a more visual approach you showing data than

we might typically see in a crosstabs.

Let's consider a heat map.

A heat map is a great way to compare categories using color and size.

In this, you can compare two different measures.

Let me show you what I mean by creating a hit map to show profit across years for

each customer segment and for each region.

To create a heat map using our super store data set,

let's drag the region to a row shelf.

Then let us drag our customer segment to the row shelf.

Let us also drag our order date onto the column shelf.

And finally, let us add profit to the size mark.

As you can see, the size of the square indicates the profit volume.

You can also click between different charts using the Show Me tab.

For example, to switch back to the text table,

all we need to do is click on the text table chart on the Show Me tab.

The next chart available in Tableau is a highlight table.

The highlight table allows us to apply conditional formatting to a view.

Tableau will automatically apply a color scheme in either a continuous or

stepped array of colors from highest to lowest.

It is great for comparing a field's values within a row or a column.

From our heat map, we can click on a highlight table in the Show Me menu.

The resulting grid is coloured in a blue gradient scale from highest,

depicted as the darkest, to lowest shown as the lightest in profits.

Next we have the symbol map.

One of the greatest features of Tableau software is the ease of utilizing maps for

your visualizations.

There are two chart types to choose from when creating a view with geographic data.

Symbol maps Infield maps.

Symbol maps are simply maps that used a type of mark.

Such as a field circle to represent a data point.

To create a symbol map, let's drag the state dimension to our chart area.

Tableau automatically understands this is a geographic field and

produces a simple chart.

The field map is another view ideal for geographic data.

Instead of circles or squares to display data points,

the field map uses shading on a country or state basis to indicate relationships.

To create our field map,

we can simply click on the Field map from our Show Me menu to color in our states.

Next is the familiar pie chart.

Pie charts are among the most popular.

If terribly over use charts in business presentations.

They are best suited to show proportional or percentage relationships.

When used in a right circumstance,

pie charts can quickly show relative value to the other data points in the measure.

Most data specialists strongly encourage you to use the famous pie chart

very selectively.

For instance, if your worksheet has multiple categories such as all 50 states.

They'll find that the pie chart becomes so

encumbered with marks that it ceases to have much visual value.

Next, is the horizontal bar chart.

The horizontal bar chart makes quick work of information consumption for

the report viewer.

They can immediately seek comparative relationships as well as approximate

numeric values.

Using our Superstore Data Set, let's drag the region to a row shelf.

Then let's drag our customer segment to the row shelf.

And finally, let's add profit.

Next we have the stack bar chart.

The stack bar chart is great for

adding another level of detail inside of a horizontal bar chart.

You can do this by adding another dimension to your horizontal

bar chart that will further divide the measure into a sub groups.

The sub groups are then color coded on each bar.

From our horizontal bar chart,

we can drag product category to the color on the marks board.

And now, we have our profit broken down for each category.

Let's turn our attention to the side by side bar chart.

The side by side bar chart is just like the stacked bar chart.

Except we've unstacked them and

put the bar side by side along the horizontal access.

To create the side by side bar chart we can click on the side by side bar chart

from the Show Me menu.

The side by side bar chart is a great way to compare each region in each category.

We can now see which region has the most profit within each product category.

Next let's look at tree maps.

If we click on the tree map from the Show Me menu,

we see a tree map visualization examining profit of product categories by region.

Profit is depicted by color and size.

The most profitable notes are dark blue.

The non profitable segments are grouped in light blue or gray.

Tree maps are a powerful visualization particularly for illustrating hierarchical

or tree structure data and part to whole relationships.

Because of their visual nature tree mapping is ideal for legibly showing

hundreds or even thousands of items in a single visualization simultaneously.

Using a tree map you can immediately show the landscape of performance

with this visualization.

This view is very similar to a heat map.

But the nodes are gathered by like,

kind in the hierarchy of dimensions you have defined.

Next, let's look at the circle view chart.

The circle view is another powerful visualization for comparative analysis.

If we click on the circle view chart on the Show Me menu.

We see a chart similar to a stack bar chart but with different shapes for

each regions.

We can drag the region category to size.

And now, we see profits for

each product category with the size of the circle representing the region.

Now, let's look at the side-by-side circle view.

The side-by-side circle view is a variant of the circle view.

The side-by-side circle allows you

to add more measures to be compared next to each other for a richer analysis.

Next, let's look at line charts.

Both continuous and discrete.

Tableau presents two options for line charts in the Show Me menu.

Lines that are continuous and lines that are discrete.

Continuous fields can have an infinite number of values, such as a temperature or

a thermometer.

Discrete fields on the other hand, containing finite amount of values.

Such as a number of students in each classroom for a school.

Tableau gives you a hint on which fields are discrete or continuous.

Discrete fields are colored blue when dragged to the column shelf or row shelf.

Whereas continuous fields are colored green.

The line chart is ideal for when you want to illustrate trends over time.

To use the line chart, you must have a date field.

We can drag our order date field to the column shelf,

our customer segment to the row shelf, and the profit to our chart.

From the Show Me menu we can click on a line chart and

we will immediately see the profit trend for each customer segment.

To compare a cross regions, we would use a discrete lines chart type.

We can drag the region dimension to our column's shelf.

And now we can see profit trans for each customer segments separated by regions.

Next, let's turn our attention to the dual line chart.

A dual line chart is also referred to as a dual axis chart.

It is an extension of a line chart with one notable exception.

It allows more than one measure to be represented

with two different access ranges.

This is done by signing the right and

left sides of the vertical access with different measures.

In this way, you can compare two different measures.

However, you need to be careful using a dual line chart.

Even though you can use any measure in this chart type.

Make sure that there is still a meaningful relationship between the two measures.

In other words, keep in mind the story you want to tell with your visualization.

To create a dual line chart, let's drag order date to the column shelf,

profit to the row shelf, and let's also add sales to the row shelf.

We now see two separate line charts.

To combine these charts, we can click on the dual line chart from the Show Me menu.

This dual line chart shown here, displays profit and

sales in a relation to each other.

Profit uses the left axis while sales uses the right axis.

This comparison can highlight important relationships between the two fields.

To synchronize both axis,

we can right-click on the right-hand side sales axis, and click on Synchronize Axis.

Now, both lines are on the same scale.

Next, let's consider area charts, both continuous and discrete.

Just as with the line chart, that Show Me many new offers that

area has an option with two versions, continuous or discrete.

You may wonder when to use either one.

The easiest way to think of this is that continuous data is measured.

Whereas discrete data is counted.

For instance, the length of an object is a continuous field.

It can be any length and the number line stretches to infinity.

The value can be any value in that number line.

It is considered continuous, since length can be measured.

However the number of stores in a franchise or

the number of employees in the HR database would be a discrete number.

Since those can only be counted.

In Tableau, continuous fields are colored green,

while discrete fields are colored blue.

The area chart is a combination between a line graph and a stacked bar chart.

It shows relative proportions of totals or percentage relationships.

By stacking the volume beneath the line,

the chart shows a total of the fields as well as their relative size to each other.

To create an area chart, we can drag our order date to the column shelf,

segment to the row shelf, and finally let that profit.

What we see now is a text table.

But if we go to our Show Me menu and

click on the area chart, Tableau will make the adjustment.

Let's switch our chart type in the chart we have just been referencing from

continuous to discrete.

And see how it changes our view.

We can use the Show Me menu to switch to a discrete area chart.

Let's click on the discrete area chart.

And we can click on the date to add quarters.

And now, we can compare profits for each year and quarter across customer segments.

Another useful chart is the scatter plot.

The scatter plot is also known as the scatter diagram, scatter chart,

scatter gram or a scatter graph.

A scatter plot is useful to compare two different measure for

patterns, like the circle view and the side by side circle chart.

The scatter plot also uses symbols to visualize data.

The big difference with the scatter plot is that both axis

in the chart are measures rather than dimensions.

With one measure on the column shelf and another measure on the row shelf.

Next up is a histogram.

Lets right click on a Profit measure and click on Create and

then Bins to create a bin field.

Let's try the profit Bin field from dimension to the column shelf.

Let's also drag the profit measure on the row shelf.

And change the aggregation to count.

In the example shown here.

I have built a histogram that breaks down individual profit

into bends of $283 increments.

Now let's turn our intention to the box and whisker plot.

The box and whisker plot is also know as the box plot.

Compared to the other chart types, the box and

whisker plot is a bit more complicated.

The box represents the values between the first and

the third quartile known as the interquartile range.

While the whiskers represent the distances between the lowest value to the first

quartile and the fourth quartile to the highest value.

Each quartile has a specific numeric value determined from the dataset.

You start by determining the median of the data set which is the middle number of

the data set.

Then, the upper and the lower quartile are determined.

These are simply the medians of the upper half of the data and

the median of lower half of the data.

That forms the box.

The maximum of the data set is the highest number in the data set.

While the minimum of the data set is the lowest number in the data set,

that forms a whiskers of the plot.

Next, let's look at the Gantt chart.

The Gantt chart was invented back in the 1910's by Mr.

Henry Gantt as a way to visualize his schedule or progression of time.

Since then, the Gantt chart has become a staple of project management methodology.

Each task can be planned as an individual data point with interdependencies

on other tasks and resources.

You can see how a complicated project such as developing a software application

could use a tool like this.

Next, let's look at the bullet graph.

A bullet graph is a very powerful way to compare data against historical

performance or pre-assigned thresholds.

A bullet graph is similar to a standard bar graph except that there

is a distribution showing progress towards a goal behind the bar.

Like a standard bar graph a bullet graph can be presented either horizontally

of vertically.

The pack bubbles view is also known as a bubbles hurt.

It is a means to show relational value without regards to axis.

The bubbles are packed in as tightly as possible to make efficient use of space.

To create a packed bubbles chart let's drag our region to our column shelf,

our customer segment to the row shelf and at our profit.

From the Show Me menu, let's click on the pack bubble's chart.

In this pack bubble's chart the arrangement of the bubbles is out of our

control.

But we can't control how big the bubbles are by putting a measure on size.

In this case I use profit.

The key to making pack bubbles chart useful is having the right

fields in the right places on the marks card, specifically on the color,

size, and detail shelf.

In summary,

I have introduced you to the various types of charts Tableau allows you to use.

I have shown you what each is best used for and

given you the basic instructions for creating these different types of charts.

After this lesson,

you should now be able to list the various types of charts in Tableau.

And explain how to create a chart in Tableau on a basic level.

As with editing skill, you will need to practice creating these charts

in order to become adept at using Tableau in these ways.

I encourage you to do so

right away to enforce your learning that you have just done.

Okay, now that you understand the different types of

charts available within Tableau.

I want to move on to show you many little modifications and

changes you can make with your formatting, labeling and other trick.

You will see that you're only limited by your imagination.

That is what we will cover in the next lesson.

Where we will explore the options for colors, shapes and sizes in Tableau.

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