A drop-down list is a way you can control a user’s input in Excel, to ensure that they don’t make a mistake when entering in data. It can also serve as a helpful way to make your chart more dynamic. In this post, I’ll show you how that’s possible.
Starting with a regular chart
For this example, I’m going to use the following table in Excel that shows historical World Cup attendance between 1930 and 2018. It shows the total, average, and highest attendance at each tournament:
Now, you could chart this out but the problem is that things can get a bit crowded:
Another issue here is because the chart is looking at total attendance along with average and highest numbers, the scales will distort the chart, making it difficult to compare averages and highest attendances. The solution to this is to use a drop-down list where the user can select which metric they want to see.
Setting up the drop-down list
Creating a drop-down list is simple and it involves just going into the Data tab and selecting the Data Validation button, where you can select the List option and enter all the possible selections you want a user to be able to choose from:
The key is to use the user selection and then populate a column with those values. For example, I’ll set a column header so that it is linked to the drop-down selection. That way, if someone selects Total Attendance, that will be the the header for the new column. I will also use the OFFSET function to determine which of the columns that I’m copying the values over from:
=OFFSET(A2,0,MATCH($F$1,$A$1:$E$1,0)-1)
In the above formula, I’m looking for cell F1 (the header that’s referencing the drop-down selection) within the range A1:E1, to see which one of the headers it matches up with. Using the OFFSET function, I can then pluck the value from the correct column. If I copy the formula down, then my new column will be based on the drop-down selection and it will automatically update based on the selection that is made
And that column, which is highlighted in yellow, is now the only one that is used in my chart. Now, the chart is cleaner and only includes the selected series rather than all three of them:
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A key performance indicator (KPI) is a way to track how well you’re progressing towards a particular goal. Oftentimes, you might have many KPIs that you will want to track. You can create these visuals in Excel using donut charts, and below, I’ll show you how you can also have them change color based on whether you’re on track for hitting your goal or not.
Start by categorizing your results
One thing you should consider doing is to create different groups to categorize your results. For example, suppose a key metric was to ensure operating expenses were no more than $10,000 for the current period. If my actual expenses are at $9,000, I would want the chart to show green and to indicate I’m on track versus if my actuals were over $15,000 and I was way over budget.
I can classify these values based on how close they are to the target amount. Here are three categories I will set up and the rules for them:
On Target: If the actual amount is <= 100% of the target.
Slightly Over: If the actual amount is >100% and <=125%.
Well Over: If the actual amount is >125%.
One field I will also create to help track the progress will be % of Target where I take the actual and divide it by the target. Your rules could vary depending on KPI. With expenses, obviously the goal will be to come in under them whereas with sales the incentive will be to come in higher. So you don’t want to assume that your calculations will always be the same in every situation.
I also created a field called Remainder which will capture the unfilled part of the circle. Think of the top half of a circle adding to 1 and the bottom half to another 1, together they total 2. And for the remainder, I use the a formula that takes the maximum of 0 and 2 – the % of Target amount. The purpose of this is to ensure that the remaining amount isn’t negative and that everything adds up to 2.
By creating these classifications, it will be easier to set up the chart to show different colors based on which category a result falls into. Here’s an example of how this might look on Excel. These categories have been created using IF statements based on the rules noted earlier.
The key goal of creating these categories is by ensuring no result shows up in more than one place. For Expense 1, it was on target so that’s the only category it falls under. Expense 2 was 20% higher than the target, so it goes into the ‘slightly over’ category. And Expense 3, which was 50% higher, it falls into the ‘well over’ category.
Now that these categories are set up, I can go about and create the actual chart.
Creating the donut chart
Using the table shown above, I’ll create a donut chart for Expense 1.
This includes all the categories I have set up, which isn’t what I want. There are multiple changes I’m going to make to this chart:
Remove the unneeded fields.
Apply different colors for the categories.
Adjusting the chart so it goes from left to right.
Adding some text boxes.
To remove the fields that aren’t needed, I’ll right-click on the chart and click on Select Data. Then, uncheck the first three field:
Next up, I’ll adjust the colors. The easiest way to do this is to click on the different colors in the legend box:
I’ll click on the blue box for ‘On Track’ series and select the color Green from the Home tab for that (note: you’ll first have to select the legend, and then click on the individual series). After setting all the different colors, this is what my chart looks like thus far:
I still need to adjust the starting point of the chart as the green slice starts from the middle, not the left. To fix this, I right-click on the chart and select Format Data Series. Then, I’ll change the angle of the first slice to 270:
Here you can also change the hole size. The smaller the hole, the larger the slices will be. If I adjust it down to 50%, here’s what my updated chart looks like:
At this point, the legend really isn’t necessary anymore since the colors will do the job and I don’t really need the labels.
One final step you may want to consider is to use a text box instead of a label. Once you’ve added a text box, you can link it to the name of your metric (this can be done through the formula bar). Repeat the same steps for the Actual, and you can have both the name of the metric and the value to automatically update:
When using textboxes, I always format them to remove the background fill and remove the border. You can do this by right-clicking Format Shape and select No Fill and No Line
Now if I were to update the Actuals for Expense 1 to $15,000, pushing me into the ‘well over’ category, my chart would automatically update:
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Do you have a chart that you want to easily modify the range on, without needing to manually select the data again? Thanks to a new Excel feature, there are now multiple ways you can do that.
1. Creating the chart range as a table
One way you can set up a dynamic chart range in Excel is to put your data into a table. That way, Excel can easily see where you data starts and ends. Suppose you have the following data:
You could show this on a chart but if you needed to add or remove rows from it, your chart wouldn’t automatically re-size. If you deleted data, then there would be gaps on your chart. And if you just added a row, Excel wouldn’t add it to your chart unless you re-selected your range.
To fix this, you can convert you data into a table. To do this, go to the Insert tab on the ribbon and select Table. You may see some default formatting applied afterwards:
Tables will automatically expand as you add or remove data, and formulas will also copy down by default to any new rows. Currently, this is what my chart looks like for this table:
In the below example, you’ll see data being added and removed from the table, and the change to the corresponding chart.
2. Using an array
If you don’t want to convert you data into a table, Excel has now made it possible to dynamically update your chart using just an array, which is new functionality. From the earlier example, I can create an array that populates the data using the following formula:
=OFFSET(A1,0,0,COUNTA(A:A),2)
The first argument reflects the starting point of the data. The next two are left as zero since I don’t want to actually offset the range. The last two arguments indicate the size of the array, and this is key to making the chart automatically update.
By using the COUNTA function, the formula will automatically adjust based on the number of items in that column. That way, if you add or remove items, the offset function will adjust your range. The last argument (2) indicates that the data set is to two columns wide. Now by updating the source data, both my array will update and so too will the chart:
Arrays are not new to Excel but the ability for them to dynamically update a chart is a new feature. As of now, this feature hasn’t fully rolled out to the public and is only available through the Office Insiders program. To get access to that, you can sign up to be an Insider (free of charge) and then moving forward, you will have Excel’s latest and greatest features as soon as they become available.
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Conditional formatting cells can be an effective way to highlight values so that they can easily stand out. You can apply similar logic to charts, and in this post, I’ll show you how you can use conditional formatting with Excel charts. By doing so, you can highlight gaps and key numbers.
Create more than one series to categorize your results
Excel’s conditional formatting isn’t designed to work on charts. But one way you can still achieve the same results is by categorizing results, and creating a series for each category. Here’s an example, using Amazon’s sales growth. Below are the year-over-year growth rates it has achieved over the past 12 quarters:
Charting the data out would show the highs and lows effectively:
However, suppose you wanted to highlight the high-growth periods (30% or more), with the more moderate ones (15%), and the quarters which were below that. To do that, I’m going to add a few more columns and use IF statements to populate the columns based on the growth rate.
Now, if I populate these values on a chart, they shows up like this:
These column charts are skinnier and that’s because they are taking up more space as there are three different series for each quarter. To get around this, I can just change the charts so that they are stacked. Since only one of these columns will ever contain a value, there’s no danger they will actually ever stack. But by changing the chart type, they won’t take up as much space.
The advantage of this approach is that you don’t even need to rely on the axis to determine what range the growth rate falls within. Although you have to create additional columns by doing this, you can hide any columns that you don’t need to see. You can apply this type of logic to other types of charts as well.
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Are you creating a chart that shows progress, with a certain goal in mind? In this post, I’ll show you how to create a chart with a target line so that you can see how close you are progressing toward your goal.
A common example for this type of chart is where you are reporting monthly sales and have a goal you want to reach for the year. Here’s a chart that shows the monthly revenue and has a cumulative total as well:
Creating the target line
To create a target line, I need to add another series to this chart. For example, let’s say your goal is for sales to hit $50,000 for the year. To do that, you just need to create another series. I’ll call it ‘Target’ and for each of the values, I’ll enter in $50,000:
You don’t need to enter $50,000 manually into each cell. You could use the autofill to copy the values down. However, a more flexible way to do this is to enter $50,000 into the first cell, and use a formula to refer to that cell. That way, if you change your target amount, you only need to make the change in one cell.
If you’ve already created your chart and want to add the line to your chart, you’ll need to right-click on the chart and click Select Data. Then, adjust your chart range so that it includes the extra column, and then you’ll see your chart update with the line. If you are creating a chart from scratch, then you just have to select the correct range when first creating it.
One additional thing you may want to do at this stage is to adjust the formatting of the target line. A good idea can be to make it look different from the other lines on your chart. One way you can do this is by using dashes. If you click on the target line, you will see a pane show up on the right-hand side showing you options to format the data series. Click on the paint bucket icon and you’ll see various settings for the line. There is one option for the Dash type which will allow you to show the line as breaking up as opposed to being solid:
After also changing the color to a solid black, this is what my chart looks like with these changes:
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Waterfall charts are an effective way to display data visually. They are particularly useful if you’re analyzing an income statement and want to see which parts accounted for the bulk of the change in profitability from one period to the next. In this example, I’m going to use Amazon’s first-quarter earnings of 2022, which saw the company’s bottom line fall into the red for the first time since 2015. Using a waterfall chart, we can quickly analyze what were the big drivers behind the drop in profitability — and the results may surprise you.
Step 1: Preparing the data for a waterfall chart
In a waterfall chart, you want to calculate the change in values. To start with, I’ve entered all the main income statement line items from Amazon’s Q1 earnings for 2022 and 2021, side by side:
I’ve grouped some expenses together for the sake of not having too many items. With waterfall charts, there are a couple of dangers. The first is that your descriptions run too long and it’s hard to display the line items. The second is that you have too many items and your chart needs to become excessively wide to accommodate all the changes.
One thing you’ll notice here is that at the bottom I have the net income (loss) line. This is a summation of the above items to ensure that it correctly ties out to the profit or loss that the company reported. This is an important step to make sure that you’ve entered your data correctly. Expenses should be negative (outflows) while income should be positive (inflows).
The next step is to now calculate the difference between the two periods, which can be done in a change column that takes the current value and subtracts from it the prior period’s value:
At the bottom, I’ve summed up all the changes. These figures are in millions, and so this is a significant $11.951 billion change in net income from a profit of $8.1 billion in the prior-year period to a loss of $3.8 billion.
Now that the data looks correct, the next step is to plot these values on a waterfall chart.
Step 2: Plotting the waterfall chart
To create the chart, I’ll select the data in the change column along with the related headers. From there I can either click on the image of a chart in the menu bar or I can go to the Insert menu and select Chart. If it doesn’t detect which chart I want to use, then I can select the image of waterfall chart from the Chart type drop-down option in the Setup tab:
Now it will show this:
The chart looks correct, however there are multiple changes we can make to help this look better.
Step 3: Modifying the waterfall chart
To start with, I’m going to modify the colors. While red makes sense for negatives, I’m going to change the blue to green, to better reflect a positive inflow of cash. This can be done by double-clicking on the chart and in the Chart Editor, going to the Series section, and scrolling to the Positive label. There, I can change the fill color:
This also gives me the option to change the line color and transparency using the opacity percentages. At this point, I’ll remove the legend since the green and red values are sufficient to tell you whether it was a positive or negative change.
The next thing I’ll change is the grey subtotal bar at the end. Ideally, you would have a starting and ending point on the chart to better show where one period started and where the other ended. But by default, the subtotal just adds up the sum of the change. To adjust this, I’m going to add a row to my table above Net Sales, called Q1 2021 Net Income. In the change column, I will simply put the amount, no change. This is what my updated table looks like:
If the chart doesn’t automatically update, you may need to update the range. This can be done by double-clicking on the chart and in the Setup section, modifying the range for the Series and/or the X-axis. But the bar charts for the totals still need adjusting. The first one shows green. To fix this, I’ll double-click on the chart to edit it and under the Series section, select the box to Use first value as a subtotal. Now the first bar chart will turn grey.
In the same section, I’ll also uncheck the box that says Add subtotal after last value in series. That will remove the last bar chart. Then, I’ll click on the option to Add new subtotal. Select to add it after the last item. By doing this, I can now specify the name of that total, as opposed to just showing ‘Subtotal.’ In this space, I’ll enter Q1 2022 Net Loss.
The only thing left now is to adjust the chart and stretch it out sufficiently so that the labels display horizontally. And I’ll also add a title — this can be done in the Customize section and under the Chart & Axis Titles area. Here is my completed waterfall chart in Google Sheets:
Now, from looking at this, you can see that Amazon was still at a profit until it reached the other income and expenses line. This would still require additional digging to see the reason for the loss, but it would point us in the right direction. And Amazon’s breakdown of these other expense items tells us that it incured a $7.6 billion loss on its investment in Rivian Automotive — the key reason its net profit from a year ago turned into a loss. While other expenses increased, they alone weren’t enough to pull the company into a net loss position.
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A chart in Excel can be a quick and easy way to display information. In this example, I’m going to use a bar chart to show a range of values, displaying both the highs and lows. Whether you want to show the range of a stock price’s highs and lows over the past year, or just a range between possible prices of something, this can apply to either one of those approaches.
In this example, I’m going to use first-time dog expenses, which can be very broad, with some items costing as little as $10 while others being well into the hundreds.
Creating the charts
First off, I’ll download the data into a spreadsheet. Here’s how it looks:
This format can easily be converted into bar charts. However, I don’t want two different bar charts, and so I’ll use the option to create a Stacked Bar Chart instead.
This doesn’t at first look like the chart that I want to create since this is adding both the highs and lows together. What I can do to make this work is by making the bar chart for the low amount to be invisible. To do this, I’ll right-click on one of the blue bar charts and select the fill option to No Fill
Upon doing this, that first bar chart disappears:
Without a scale, it doesn’t matter that the ranges are stacked since it effectively only shows the difference from the end of the first bar chart (which would be the start of the range) to the end of the second bar chart (this would cover the difference in value between the first bar chart and the second one). What I will do at this point is get rid of any legends and values along the x-axis.
To more effectively display the data, I’ll also add data labels. For the second bar chart, which is highlighted in orange, I’ll right-click and select Add Data Labels. By default, it’ll put the value in the middle. However, I’ll adjust it so that it goes towards the end of the bar chart. To change the appearance of the labels, simply right-click on any of them and select Format Data Labels. And under Label Position, pick the option to show Inside End. This will now move the data label to the end of the bar chart. After modifying some of the colors, this is what my chart looks like now:
You could also remove some of the gridlines. And you may want to add data labels for the first bar chart to show where the starting point is. But given that some of these bar charts are small, they may not be large enough to accommodate both values.
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Dashboards in Excel can update when a user makes a selection on a slicer or refreshes data. You can even use macros to automatically update a chart or dashboard for you. In this post, I’ll share with you a template that I’ve created that will allow you to effectively play your dashboard, updating it from one period to the next, and showing the change in the chart over time. Here it is in action:
The template has three sections: one for pivot tables, one for the data, and one for the dashboard. You can set the file up however you want, the main area that needs to remain largely the same is the dashboard sheet. Every chart on this sheet only will automatically get updated. And for it to work properly, all the charts need to be linked to the one timeline chart in here (i.e. there cannot be more than one). For information on how to set up your timeline (or any other slicer for that matter) so that you can link it to multiple charts, you’ll need to learn about how to adjust Report Connections in this post.
Once you’ve got the charts you want to be connected to the timeline, then it’s a matter of just updating the settings section on the Dashboard tab. This is off to the left, with the values that you need to enter/update highlighted in yellow.
These simply specify what date you want to start from, where you want to end at, and by which interval you want to jump (e.g. x days/months/years). Depending on the frequency you select, your dashboard can either play very quickly, or very slowly.
The last step is to just click the Animate Dashboard button at the end of the home tab:
Upon clicking this, the timeline will jump by the intervals you specified. No other changes will be made to any filters or slicers you have selected. The only changes will take place to the timeline, at which point, you should see something similar to the video posted at the top of this post.
If you liked this free template that helps you animate your dashboards, please give this site a like on Facebook and also be sure to check out some of the many templates that we have available for download. You can also follow us on Twitter and YouTube.
In Excel, you can create quick and easy visuals with only a formula. You don’t need to insert charts or worry about if they are set up correctly. In this post, I’ll show you how you can quickly create both bar and column charts.
For this example, I’m going to use data from Apple’s most recent earnings report, to see the split between sales of its different categories. Here’s what the data looks like from its most recent filing:
To create a simple bar chart, I’m going to use the REPT function, which allows me to repeat text. The character I’m going to repeat is the “|” line, which on most keyboards is the button above the enter key. Holding shift and that key should give you that line. The number of times I want to repeat the character will be the value in column B. But because it’s too large, I’m going to divide it by a factor of 100. Here’s how that formula will look:
=REPT("|",B4/1000)
If I copy this down, my bar chart remains a work in progress:
One way to make this look like more of a bar chart is by changing the font. In column C, I’m going to change it to Britannic Bold. And now, this looks like a proper bar chart:
If I sort the values from largest to smallest, then it’s easier to see the progression:
This is good, but this is also still a bar chart. To convert this into a column chart, I need to make a couple of changes. The first thing is I need to arrange the data differently so that the fields and the values are going horizontally rather than vertically. To do this, you can just transpose the data. You can do this using the TRANSPOSE function. Now, my data is better suited for a column chart:
Now, I’ll add back the REPT function and use the same font. Except for this time, I will modify the cells so that the alignment is vertical:
Now, after compressing the columns, I have a column chart set up:
Here’s a quick video showing the steps:
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The MACD line and chart is a popular tool for technical analysts who buy and sell stocks. And in this post, I’ll show you how you can create it from start to finish. In my example, I’ve downloaded Apple’s stock price history for the past year from Yahoo Finance, and I’ll use that to calculate its MACD line. Here’s a sample of what I’m starting with:
Calculating the exponential moving averages
To calculate the MACD line, I’ll need to create multiple exponential moving averages (EMAs). One for 9 days, 12 days, and for 26 days. The logic will be the same so I can start with creating a formula for the 9-day EMA and then apply that to the others.
I’m going to create a couple of variables. The first being the n for the number of days. And the second one is for the weighting that you’ll apply to more recent values, and thus, turning it from a simple moving average into an exponential one. The weighting is calculated as follows:
=2/(1+n)
I’ll start my formulas to calculate the 9-day EMA by first checking to see if I have at least 10 data points. If I don’t, then I’m only calculating a simple moving average. Here’s how the start of that formula looks, assuming my closing stock prices start from cell B5 and my variable n is in cell C1:
IF(COUNTA($B$5:$B5)<=C$1,AVERAGE($B$5:$B5)
A key part of the formula is freezing cells properly. Cell $B$5 won’t move, but $B5 will as I drag it down. And this allows me to calculate the cumulative number of data points, and the corresponding average. The next part of the formula is what happens if I have more than nine data points. In that case, I will take the weighting (this is cell C2) on my sheet, and multiply that by the difference between the most recent stock price and the previous EMA. This will then get added to the previous day’s EMA:
C$2*($B5-$C4)+$C4
Column C is the one that contains the EMAs. My complete formula is as follows:
I can now copy this logic across multiple columns to calculate the 12 and 26 day EMAs as well:
Now, I’ll set up the calculations for the final three columns:
MACD: This involves taking the 12-day EMA and subtracting the 26-day EMA from that.
Signal Line: This is a 9-day EMA of the MACD line.
Histogram: This is calculated as the difference between the MACD line and the Signal line.
With all those columns set up, here is my completed table:
Creating the charts
With all the columns set up, the next part is to put the key data into a chart to illustrate the MACD line, Signal line, and Histogram. To make the chart look like a typical MACD chart, I’ll need to set the MACD line and Signal line to be line charts, and for the Histogram to be a column chart.
Initially, when the chart is created, there’s too much data in there since the data set is bigger than it needs to be:
To fix this, I right-click on the chart and click Select Data. Then, I remove all the series except for the last three: MACD line, Signal line, and Histogram. My updated chart looks as follows:
There are still a few more changes that I am going to make here. The first is to fix the axis, as there are gaps between the column charts. That’s because Excel is recognizing the axis as a date axis. And while that’s correct, that means there will be gaps since stocks don’t trade every day of the week, and thus, those gaps, are weekends. To fix this, right-click on the axis and click Format Axis. And then, change the Axis Type so that it is a Text axis:
And then, under the Labels section, I set the position so that it is Low and at the bottom of the chart. My updated chart looks a bit better:
The last change you may want to consider is adjusting the column chart gap, to shrink it so the chart looks more like a histogram. If you right-click on them and click Format Data Series, there’s an option to change the Gap Width. I find that setting this to 50% normally results in a good gap size::
And now we’ve got a chart that resembles what you might find on major finance sites when looking at MACD. If you want to follow along with the sheet that I’ve created, you can download my MACD chart template here.
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