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Â Welcome to the first lesson in the Explaining Your Data using Tableau course.

Â In this lesson,

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

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

Â illustrate how to create different types of charts.

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

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

Â Let me show you what I mean.

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

Â Here you can see the entire selection of chart types.

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

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

Â For example.

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

Â more measures.

Â Chart types that are not applicable to your worksheet

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

Â Until you have the appropriate combination of measures end or dimensions.

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

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

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

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

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

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

Â Gantt charts, bullet graphs and finally pack bubbles.

Â Let's look at each of this in term.

Â 1:52

First, is the text table.

Â The text table also know as the cross tabs,

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

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

Â The mark type is texts.

Â And the data is organized simply into rows and columns.

Â 2:10

While text tables are applicable to most data sets.

Â They do not tell a very compelling story.

Â Nor do they highlight important pieces of your data without

Â additional formatting on your part.

Â Text tables are not normally recommended

Â as a primary visualization in your dashboard or presentation.

Â Consider using them as an appendix inclusion for

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

Â 3:04

The next chart is the heat map.

Â To take a more visual approach you showing data than

Â we might typically see in a crosstabs.

Â Let's consider a heat map.

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

Â In this, you can compare two different measures.

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

Â each customer segment and for each region.

Â 3:30

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

Â let's drag the region to a row shelf.

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

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

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

Â 4:07

The next chart available in Tableau is a highlight table.

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

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

Â stepped array of colors from highest to lowest.

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

Â 4:28

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

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

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

Â 4:46

Next we have the symbol map.

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

Â your visualizations.

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

Â Symbol maps Infield maps.

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

Â Such as a field circle to represent a data point.

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

Â Tableau automatically understands this is a geographic field and

Â produces a simple chart.

Â 5:23

The field map is another view ideal for geographic data.

Â Instead of circles or squares to display data points,

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

Â To create our field map,

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

Â 5:50

Next is the familiar pie chart.

Â Pie charts are among the most popular.

Â If terribly over use charts in business presentations.

Â They are best suited to show proportional or percentage relationships.

Â When used in a right circumstance,

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

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

Â very selectively.

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

Â They'll find that the pie chart becomes so

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

Â 6:28

Next, is the horizontal bar chart.

Â The horizontal bar chart makes quick work of information consumption for

Â the report viewer.

Â They can immediately seek comparative relationships as well as approximate

Â numeric values.

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

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

Â And finally, let's add profit.

Â 7:01

Next we have the stack bar chart.

Â The stack bar chart is great for

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

Â You can do this by adding another dimension to your horizontal

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

Â The sub groups are then color coded on each bar.

Â 7:34

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

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

Â Except we've unstacked them and

Â put the bar side by side along the horizontal access.

Â 8:09

Next let's look at tree maps.

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

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

Â Profit is depicted by color and size.

Â The most profitable notes are dark blue.

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

Â Tree maps are a powerful visualization particularly for illustrating hierarchical

Â or tree structure data and part to whole relationships.

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

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

Â 8:48

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

Â with this visualization.

Â This view is very similar to a heat map.

Â But the nodes are gathered by like,

Â kind in the hierarchy of dimensions you have defined.

Â 9:04

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

Â The circle view is another powerful visualization for comparative analysis.

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

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

Â each regions.

Â 9:32

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

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

Â The side-by-side circle allows you

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

Â 9:47

Next, let's look at line charts.

Â Both continuous and discrete.

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

Â Lines that are continuous and lines that are discrete.

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

Â a thermometer.

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

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

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

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

Â Whereas continuous fields are colored green.

Â 10:25

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

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

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

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

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

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

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

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

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

Â 11:07

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

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

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

Â It allows more than one measure to be represented

Â with two different access ranges.

Â 11:33

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

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

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

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

Â 11:49

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

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

Â We now see two separate line charts.

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

Â This dual line chart shown here, displays profit and

Â sales in a relation to each other.

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

Â This comparison can highlight important relationships between the two fields.

Â To synchronize both axis,

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

Â 12:32

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

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

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

Â You may wonder when to use either one.

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

Â Whereas discrete data is counted.

Â 12:53

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

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

Â The value can be any value in that number line.

Â It is considered continuous, since length can be measured.

Â However the number of stores in a franchise or

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

Â Since those can only be counted.

Â 13:20

In Tableau, continuous fields are colored green,

Â while discrete fields are colored blue.

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

Â It shows relative proportions of totals or percentage relationships.

Â By stacking the volume beneath the line,

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

Â 13:42

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

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

Â What we see now is a text table.

Â But if we go to our Show Me menu and

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

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

Â continuous to discrete.

Â And see how it changes our view.

Â 14:06

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

Â Let's click on the discrete area chart.

Â And we can click on the date to add quarters.

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

Â 14:27

Another useful chart is the scatter plot.

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

Â scatter gram or a scatter graph.

Â A scatter plot is useful to compare two different measure for

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

Â The scatter plot also uses symbols to visualize data.

Â The big difference with the scatter plot is that both axis

Â in the chart are measures rather than dimensions.

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

Â 15:28

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

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

Â Compared to the other chart types, the box and

Â whisker plot is a bit more complicated.

Â The box represents the values between the first and

Â the third quartile known as the interquartile range.

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

Â quartile and the fourth quartile to the highest value.

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

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

Â the data set.

Â Then, the upper and the lower quartile are determined.

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

Â the median of lower half of the data.

Â That forms the box.

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

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

Â that forms a whiskers of the plot.

Â 16:25

Next, let's look at the Gantt chart.

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

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

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

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

Â on other tasks and resources.

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

Â could use a tool like this.

Â Next, let's look at the bullet graph.

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

Â performance or pre-assigned thresholds.

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

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

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

Â of vertically.

Â 17:17

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

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

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

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

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

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

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

Â control.

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

Â In this case I use profit.

Â 18:03

In summary,

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

Â I have shown you what each is best used for and

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

Â After this lesson,

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

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

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

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

Â I encourage you to do so

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

Â 18:38

Okay, now that you understand the different types of

Â charts available within Tableau.

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

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

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

Â That is what we will cover in the next lesson.

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

Â