Each bar is now comprised of a number of sub-bars, each one corresponding with a level of a secondary categorical variable. We want to move to a stacked bar chart when we care about the relative decomposition of each primary bar based on the levels of a second categorical variable. A stacked bar chart also achieves this objective, but also targets a second goal. One bar is plotted for each level of the categorical variable, each bar’s length indicating numeric value. The main objective of a standard bar chart is to compare numeric values between levels of a categorical variable. ![]() The Strawberry Mall location appears to have a lower proportion of revenue attributed to equipment, while equipment has a larger share for Peach St. ![]() We can see that for most locations, clothing is quite a bit larger in sales than equipment, which in turn is larger than accessories. Each bar is subdivided based on levels of the second categorical variable, department. location has the highest revenue and Apple Rd. The primary categorical variable is store location: we can see from the sorted overall bar heights that the Cherry St. The stacked bar chart above depicts revenue from a fictional fitness retailer for a particular period of time, across two categorical variables: store location and department. Each bar in a standard bar chart is divided into a number of sub-bars stacked end to end, each one corresponding to a level of the second categorical variable. I want to give credits to all the contributors to How to use custom colours in a stacked bar chart, please check that community thread if you have questions or just to learn more about custom colors in stacked bar charts.The stacked bar chart (aka stacked bar graph) extends the standard bar chart from looking at numeric values across one categorical variable to two. I'm attaching an example app so you can check how it's done. So again we could use the good old if statement or pick&match to end up having customized segment colors in our stacked bar chart. Now that our chart is standard bi-dimensional bar chart, all we need to do is to apply custom colors as described earlier in this post. To complete our chart, we’ll need to add a simple if statement (or the more elegant pick&match combo) in our measure expression, similar to this one: The dimensions will be “Year” and the recently created “measure”. Once the data has been loaded then it’s time to create our chart. ![]() Our table will contain the name of the segments for our chart, I called it in my example. In order to do that we’ll add a new table to our data model. To solve this situation, we need to work-around our chart to make it again bi-dimensional. The problem comes when trying to color the segments, at this point we can’t target specific segments anymore because each one of our segments is made of an expression. We could get a stacked bar chart using one single dimension "Year", and 4 expressions Q1,Q2, Q3 and Q4. In this scenario our data table contains one column per quarter as in the image below but we still want to represent them in one stacked chart using custom colors. If(Quarter='Q1',red(),if(Quarter='Q2',blue(), if(Quarter='Q3', green(), yellow())))Īlternatively, you could use conditional functions for a more elegant approach: This is the simplest case, you just need to target each one of the segments (Quarters in our example) by name, you could just use an if statement to target them, something like: The procedure to customize the colors will depend of what type of chart you have, bi-dimensional chart or multi-expression chart, let’s start with bi-dimensional chart coloring. Alternatively, we could recreate the chart using one single dimension "Year" and 4 expressions one per each one of the quarters. To create a simple stacked bar chart like the one in our example we've needed 2 dimensions (Year and Quarter) and one measure. ![]() Just by observing the chart a few seconds we can conclude that Actual Amount was higher in 2007 than 2006, and it seems clear that Q2 rise in 2007 contributed significantly to the 2007 total increase in Actual Amount. Stacked bar charts are perfect to represent the contribution of particular elements to the total, the classic example is Sales by Year and by Quarter.
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