The stacked chart wasn’t terrible.

She already formatted it, following all the usual dataviz and accessibility principles. (White outlines, brand colors, direct labels instead of legends, sequential colors for a sequential variable, only labeling the min and max on the scale, using sufficient color contrast, etc.)

The challenge was that her chart was going into a dynamic dashboard, so depending on which filters were selected, the numbers might be really big, really small, or even zero.

We needed to think forward and plan for all those different scenarios.

Challenge: A Single Stack is Lonely

Another challenge was that her chart looked lonely.

I don’t love stacked charts for a single stack.

I don’t have peer-reviewed articles to back this up; it’s a personal preference.

Stacks are extroverts. They thrive with their friends, like this:

Challenge: Stacked Charts are Tough for Tiny Slices

Remember how her chart was going into a dynamic dashboard?

So depending on which filter(s) were selected, the numbers might be really small.

Stacked charts are terrible for small slices. They’re hard to label, and even harder to see.

You’ve run into this, haven’t you? It’s a common dataviz headache.

Challenge: Stacked Charts are Tough for Zeros

Another common dataviz headache is that stacked charts are terrible for zeros.

Because they literally can’t show zeros. There’s nothing to visualize.

Sure, I’ve seen people try all sorts of workarounds, like adding text boxes off to the side that explain that a category isn’t shown because the number was a zero. But that’s messy and time-consuming.

Solution: Use Columns/Bars Instead of Stacks

I often recommend changing the stacked bar/column into a regular bar/column, like this.

(Should you use vertical columns or horizontal bars? I’m using vertical columns here because this particular graph is sequential.)

(Worried you’ll have to delete the chart and start from scratch? No way! It’s faster than that. You can change the chart type with just a few clicks.)

Can you see how regular bar/column charts work better for tiny numbers?

Can you see how regular bar/column charts work better for zeros?

And don’t worry — regular bar/column charts still work when comparing multiple categories, too. We’d simply make a small multiples layout, like this.

Your Turn

These principles can and should be applied to every software program.

As you can see, I’m using everyday software (Excel) in these examples.

Have any how-to Excel questions? Comment here and let me know. I’ll post a link to an existing tutorial, or I’ll make a brand new tutorial for you.

The post Fixing Stacked Charts with Tiny Slices appeared first on Depict Data Studio.

And if we’ve already got the exact values within the graph itself, the y-axis can become even more cluttered.

In this video, you’ll learn how to adjust your graph’s vertical scale so that it only shows the minimum and maximum value. You’ll adjust the min and max “bounds” and the “units.”

You’ll also get bonus tips for setting up this chart type, the columns with a target/goal line. This is a “combo chart” in Excel. You’ll need to set up the table in a very specific format to get this chart to display correctly.

What’s Inside

• 0:00 Overview
• 0:24 Welcome to Dataviz On The Go
• 0:32 Setting Up the Table for the “Combo Chart”
• 1:54 The Edited Chart (Dataviz Best Practices)
• 2:16 How to Only Label the Min and Max
• 4:11 Download the Spreadsheet
• 4:20 Don’t Forget to Like, Subscribe, and Share

Download the Spreadsheet

It’s here: https://depictdatastudio.ck.page/onlylabelminandmax

Read the Transcript

Ann K. Emery: [00:00:00] In this video, you’re going to learn how to only label the min and the max on your scale. Like this. Instead of putting the labels on the columns and the scale, we only need the min and the max on the scale. Otherwise, it would be redundant. If this seems like it might be relevant to you and your workplace, stick around, I’ll give you some context, and then I’ll get into the how tos.

It’s Ann Emery. You’re watching Dataviz on the Go, the series where I make quick tutorials as I’m racing around between my meetings and my workshops. All right, let’s get into the context and then the how to’s. This is how you’d have to set up your table for this style of graph. You would list out your fictional project names in this example, the actual number that you want to appear in your columns or a percentage or a currency, and then you’d repeat the target

over and over and over in the third column, you’re going to arrange them least to greatest so that you get that [00:01:00] order in your chart least to greatest. You’re going to add an intentional gap in your table. That’s on purpose because guess what? Yep. You guessed it. It creates an intentional gap in your chart.

And then the final thing you need to know here is you’re going to have this target appear one extra time at the end. Okay. Because that’s what helps the line extend a little bit beyond the columns so that you can add a nice direct label right here. Okay. That’s the gist of how you need to set up your table for this style chart, which is the columns with the target line or the goal line.

It’s going to be a combo chart. So you’re going to highlight your table. You’re going to insert a combo chart. You’re going to get this mess. Which isn’t helpful and doesn’t tell us everything. And also has the super redundant, super detailed scale right here as well. The edited version is going to look mostly like this grouping by color, a nice dark light contrast here.

You’re [00:02:00] going to gray out the target line because that’s the sidekick. That’s not the main character. You’re going to add some words. You’re going to add a little bit of math. You’re going to add some icons. Okay. It’s pretty much done. It’s pretty much done with the exception of the overly labeled scale like this.

So the how to’s, let me copy and paste this chart. So as usual, we can admire them side by side, and here’s where you’re going to click. You’re going to click on the. The numbers on the scale. You have to be really careful here. Don’t click on the white space between the numbers, click on the actual number, click on the numeral on the actual font color here, not in the white space.

Okay. You click there. You see the rectangle appear around the outside of the numbers. You do a right click, you go to the bottom of your list right here. Format axis, and it pulls up this sidebar for us. You can see the min and the max. That’s pretty easy to follow, right? If the biggest number is a [00:03:00] 951, let’s make it extend to a thousand.

Nice, even round number, a little bit bigger than the biggest number. This is the part you have to adjust right here. The units, the units mean how often do you want a demarcation. Excel guesses. It’s gonna guess too much. It’s gonna guess too often. It guessed right here. It said, how about every hundred? And I’m like, nope, because why?

Why? Right? If you already have the exact values on the columns, you don’t need the numbers to estimate the values because there’s no estimation needed. They already have the exact values. You could do something like I don’t do this. I’m just going to show you what this does. If you insert a 250 here, then you get a demarcation every 250.

So if you only want to label the min and the max, then whatever your max value is, that’s what’s going to go in this box. Got it? If your scale goes from zero to a thousand, then you want a demarcation [00:04:00] every Thousand units. You press enter, it shows you every thousand. Now it’s perfect. We’ve got the min and the max on the scale, plus the exact values on the columns.

If you wanna download this spreadsheet and dig around and explore and see how I set everything up, look below this video and there’s a link to download it. Don’t forget to like, subscribe and share.

The post How to Label Only the Min and Max on the Excel Graph appeared first on Depict Data Studio.

We’ll call them the Statelandia Public Health Department.

Before

Here’s what their “before” version looked like.

The information on how many adults overall had been diagnosed with high blood pressure was tucked inside the title, while the graph focused on the breakdown by age group.

All the important details are there, hooray! But we all wanted more cohesion between the title and the graph.

Two Options for Visualizing “Overall” Data or Averages on Bar Charts

There are two primary ways to visualize our “overall” data or averages when we’re making bar or column charts.

The two options include:

1. Add a column. We can add intentional gaps between the “overall” data and the subgroups. In technical terms, the space is a preattentive attribute. Preattentive attributes help our audience recognize instantly that the overall vs. subgroups are a bit different.
2. Add a line. Another option is adding a line on top of the bars or columns. I’ve seen people add literal lines in Excel (Insert – Shape – Line). That works, but the fancier option is to use a Combo Chart in Excel. (If you’re not familiar with Combo Charts, you can download my template below.)

Let’s apply these two options to the blood pressure example.

Option 1: Visualize “Overall” Data by Adding a Column

I *think* this is my preferred approach. I’m still on the fence. Hmm…

A Few Quick Wins

I always start with Quick Wins. These edits can be tackled within minutes.

Quick Wins give us momentum so that we have mental energy to tackle the Not-So-Quick Wins.

Here’s what we edited:

• We changed the horizontal bar chart into a vertical column chart. Age groups are ordinal, and I generally try to arrange ordinal data from left to right. You can read more about my bar vs. column logic here, and you can learn how to make this quick rotation in Excel here.
• We rounded the decimal places to the nearest whole number. You can learn more about lowering the numeracy level of our graphs here.
• We moved the percentage labels inside the columns (so they don’t accidentally make the columns look taller than they really are).
• We decluttered the graph (removing gridlines, showing fewer increments on the y-axis, tucking the labels inside the columns, etc.).

Add an “Overall” Column with an Intentional Gap

Next, we added the “overall” data to the graph as its own column.

We also spaced the overall column apart from the others. These are separate types of data (an overall number is qualitatively different from a breakout by subgroups). They need to be arranged separately on the slide.

If you’re using Excel, simply add an empty row to the table that feeds into your graph.

You can learn more about adding intentional gaps in this blog post.

Adjust the Text Placement

Next, we moved around the text boxes.

All the important text was there — but in a single full-width text box.

We simply placed “like with like” — the overall text with the overall column, and the subgroup text with the subgroup columns.

We also moved the “year” data to the source at the bottom of the slide.

Bold the Key Words & Color-Code by Category

For extra skimmability, we bolded a few key words.

Then, we adjusted the colors. Separate colors for separate categories of information.

Color-coding by category is one of my all-time favorite dataviz techniques! You can see color-coding applied to one-pagers, recurring monthly reports, technical reports, and slideshows in these linked examples.

The final version would look like this:

Option 2: Visualizing “Overall” Data by Adding a Line

I love adding lines to visualize targets and goals.

We can add lines to visualize “overall” or “average” data, too.

BUT make sure to gray out something. Otherwise, the line chart gets messy.

You might gray out the columns, like this:

Or, you might gray out the line, like this:

Visualizing “Overall” Data on Line Charts

It’s easy to apply these techniques to line charts.

Just add another line!

Your Turn

Which approach is your favorite?

Adding a column?

Or adding a line?

And why?

For this case study, I prefer adding a column because it was easier to arrange the takeaway text in the right places (the takeaway text is simply above the columns). For the line charts, the takeaway text didn’t feel as seamless.

Comment below and share your own insights.

Bonus: Download My Spreadsheet

Not familiar with the intentional spacing in the bar chart?

Not familiar with the combo chart design in the line chart?

Download my spreadsheet here.

The post How to Visualize “Overall” Data or Averages in Bar Charts appeared first on Depict Data Studio.

Well, maybe you could.

When you work with data, you usually use the same tools over and over. You become familiar with them. You know the ins and outs, and you work faster because you remember the shortcuts and hidden menus.

Even with all your know-how, you can still come up against a roadblock, unable to do what you need.  How about taking what you know and use it…but differently. Hack it.

Hack? What? 

What hacking am I talking about? Not any of the Merriam-Webster definitions (think literally beating around the bush ). This hacking is more like the idea behind ikeahackers – taking a product and using it in a different way or for a different purpose than the original creator intended. Psst.. It doesn’t have to be ikea. You can take 2 giant foam cushions, and turn them into a side table.

What Do You Want?

Microsoft Excel added a map to its chart types. Great!

But what if you want to create a hex map?

A hex map is a map that represents an area (a US state for example) as a single hexagon, in the approximate position it should be. This eliminates problems that come up because of the different sizes of states. In the US it is especially helpful when including Alaska and Hawaii since they are both positioned far away from the contiguous US states.

A hex map would have equal representation for all the US states. No state would be too small (hello Rhode Island) or too big (looking at you, Alaska).

Get from Where You Are…

Ok, how to do that? Does Excel map include a hex map option? Nope.

Well, it looks like it’s organized in rows and columns.

Could we use the Excel cell structure for that? Maybe, but how will we get the data to the cells?

Well, a scatter plot could be the basis of that but you would need to build the whole map somehow.

How?

…to Where You Need to Go!

Other people (like David Napoli and John Schwabish) who understand Excel quite well sat down and wrote the process.

They did not use code. They did not use a special hidden feature.

They hacked Excel by using a standard feature such as the scatter plot.

It was done by understanding how scatter plots are built.

Scatter plots place your data in certain positions, based on the x,y coordinates provided.

You could use that to prepare the data for a scatter plot that looks like the US, then add the data, add hexagons, and so on. Since someone already did that, you can simply read up on their work.

Keep it Simple, S…Sweetheart

There are many more simple hacks you can use in Excel. 

A useful one I recently used is showing the total in a stacked bar or column chart.

A stacked bar chart has the option to display the data labels of each series but not the total.

Consider this example displaying the number of projects in different divisions.

Aside from the clutter, if users want to know the total per quarter, I don’t expect them to start adding up the numbers themselves.

But it’s not an option!

Wait, Excel displays the data labels of each series.

Why not create a series summing up quarterly projects and then just showing the data labels?

Did it. 

Then added it to the chart where it was displayed in all its glory.

Once I choose “No Fill” and “No Line” and add the data labels, things look different.

If you don’t like to think of all those stacked pieces jutting out of the chart, or you want the vertical axis to be determined automatically there’s another thing you can do.

Edit the chart type and choose the Grand Total series to be something other than a stacked column.

Same result, one more step, but a step that can keep the chart looking this way even if the data changes and your axis needs to change as well.

Gimme More…

I also have to mention one of Ann’s many hacks, because it is just so useful and so simple – using the Webdings font as a dynamic graphic component.

Read it and congratulate yourself on learning something small but powerful.

Now What?

Stop.

Stop and think. 

Stop and find time to invest in your professional development and think on the tools you are using. Break away from the “walls” of the examples you’ve learned from and truly think about features you know.  Try to imagine them as simple, skeletal definitions of input-output. “I have data and Excel places it on a grid.” “If there is space in the data, there is space in the table.” “My chart doesn’t have to show everything included in it, some of it can just be structure.”

Stop before you create a chart, table or report and think about what you want to do, without restricting yourself to whatever tool you need to use. Sketch it, describe it in words, use whatever helps you have it defined in your mind. Only after that think of your implementation, think of your own view of features in your tools and plan on how to use them. 

Now, go forth and be technically creative!

Connect with Anat Zohar

LinkedIn: https://www.linkedin.com/in/anatzohar/

The post How to Hack Excel — and Add Totals to the Tops of Stacked Column Charts appeared first on Depict Data Studio.

Before

When asked to submit their existing visualizations to be redesigned, one of the conference attendees sent me this dashboard (shown below).

The attendee was responsible for monitoring key statistics about the university’s library.

The dashboard included information about the number of visitors, transactions, checkouts, and interlibrary loans.

These twelve metrics and their associated icons were intended to provide an at-a-glance overview about the library during a given month.

What’s Working Well: Length, Icons, and Text Size Hierarchy

A few things were already working well for this dashboard:

• The most notable accomplishment was that it already fit on one page! I typically see “dashboards” that drone on for way too many pages. I’m not an old school dashboard designer. I don’t believe that dashboards have to fit on a single page or screen. But sometimes the multi-page dashboards also contain so much narrative text that they’re more of a report than a dashboard.
• The icons were also working well. Michelle Borkin and her team found that icons make graphs more memorable, so I add or keep icons whenever I can.
• Finally, the dashboard already incorporated a text size hierarchy of sorts. A hierarchy means that the most important information should be large, dark, and bold so that it grabs our attention. The twelve big numbers are already stood out, which was a plus.

What Needs Editing: Clutter, Alignment, and Context

There are a couple easy edits:

• We’re going to do the usual decluttering for
  this dashboard. That’s a given, right? We’ll simply remove the borders that
  outline each of the twelve data points.
• We also need to adjust the alignment. The numbers and words are centered within their boxes. Yet
  the icons aren’t quite centered over them. Intentional alignment makes our visualizations
  look polished.
• The biggest edit needed is context. The dashboard
  currently shows February’s numbers. For example, 24,051 people visited the
  university’s library during February alone. I have no idea if that’s a huge
  number or a tiny number. A single number on its own doesn’t tell us much. We
  need more context. We need to be able to compare that number to something. There are a few comparisons
  we could make. For example, we could compare that number to the prior month
  (January vs. February). Or, we could compare that number to our goal
  (February’s actual number compared to February’s goal).  

After: Monitor Patterns Over Time

Here’s the first idea for this university’s monthly dashboard.

These are made-up numbers, but hopefully you still understand the gist of the makeover.

I:

• gave viewers the opportunity to monitor patterns over time. Each month has its own column. Now, we can compare the current month to past months, which adds much-needed context.
• added graphs, which I created with Microsoft Excel’s spark columns.
• decluttered the dashboard by removing unnecessary outlines. I chose to keep the single horizontal line beneath the months, but that line is gray, not black.
• color-coded by category. I grouped the twelve data points into categories: Visitors (blue), Transactions (purple), and New Materials Acquired (turquoise).
• applied a text hierarchy. The title is large, dark, and bold. The headings (Visitors, Transactions, and New Materials Acquired) are a medium size because they’re of medium importance.
• adjusted the alignment. The words are left-aligned and the numbers are right-aligned. The icons are center-aligned with one another, and they’re top-aligned beside each of their categories.

After: Track Progress Towards Goals  

Here’s the second idea.

It’s also clutter-free; includes graphs and a text hierarchy; and groups the twelve data points into categories (which are color-coded, of course).

The difference is the dashboard’s purpose. The before version only looked at one month at a time. To provide more contextual details, the first makeover allowed viewers to compare patterns over time. This second makeover allows viewers to track progress towards goals.

I included columns for Running Totals and Year-End Goals. Then, I indicated whether the goal was achieved with filled-in squares and empty squares. I taught you how to create these square icons in an earlier post. They’re just lowercase g’s and c’s in the Webdings font!

Finally, I visualized the percentage of the goal that had been achieved so far. I call these progress bars. In some areas, the library has already exceeded their goal, so the bars spill past the 100% mark—a cause for celebration!

The Winning Idea

Which dashboard is correct?! Both of them!

Two dashboards, two different purposes.

I recommend designing several options for your viewers. Ask which one they prefer. Gathering feedback is one of the most important steps of the design process.

Bonus! Download the Spreadsheets

These are Microsoft Excel files, which are then distributed to viewers as static PDFs.

(I rarely make interactive dashboards with drop-down menus or checkboxes anymore. Leaders are busy and simply don’t have the time to explore interactive dashboards. I’ve found that the busier the audience, the more they prefer receiving a PDF’d one-pager.)

You can download my file and adapt the templates however you’d like for your own metrics and numbers.

The post Re-envisioning a University’s Monthly Report: Two Reports with Two Different Purposes appeared first on Depict Data Studio.

The default: The data just sits there inside a Dusty Shelf Report.  

But what if your data could actually inform real-life decisions?  

I recently sat down with Vivian Jefferson from Loudoun County Public Schools, a growing district in the Washington, D.C. metro area.   

Vivian and I are both members of the same Facebook group (a community for everyone taking data visualization training with me).  

A couple weeks ago, Vivian mentioned that her graphs had been featured on the news (!!!).  

The topic was school reopening plans for the 2020-2021 academic year. Vivian and her colleagues had collected surveys from parents and teachers to gauge their opinions.  

Watch the Conversation Below 

Vivian and I talked about the 52,000 surveys that her office designed, administered, cleaned, and visualized within a two-week timeframe.  

She’ll teach you how they visualized the data, making sure to have detailed reports for technical audiences and a storytelling slideshow for a school board meeting with hundreds of attendees.  

And, she’ll tell you how her graphs ended up being featured inside a news story for an even broader audience. 

About Vivian Jefferson 

Vivian works in the research office of Loudoun County Public Schools in Virginia. The district is one of the largest in the state, with 83,000 students and 94 school facilities (and counting–they open a new school almost every year!). They average about 2,500 new students each year.  

The research office is a four-person team consisting of a program analyst, data analyst, office supervisor, and Vivian, who manages surveys.  

How Vivian’s Role Has Shifted Due to COVID-19 

Vivian noted that the data requests have been more urgent and bigger in size as the leadership tries to make decisions quickly. Loudoun County Public Schools closed in early March but was able to implement some online learning using existing tools.  

“The leadership wanted to monitor how that was going: Are students logging in, are they engaged? What we found was that the tools that we had couldn’t necessarily collect all of that data. We could tell how many students were logging in, but not if that were completing the activities or for how long they were logged in,” said Vivian.  

Vivian and her colleagues have been doing more surveys to try and find where people stand and what their concerns are.   

Vivian also said that the biggest impact she feels has been on what they haven’t been able to do.  

In the spring, they usually conduct assessments to see how students have progressed. They haven’t been able to do that, so they don’t know if the interventions they had in place worked. They also don’t know what the student needs and strengths are going into the next school year.  

“We won’t have the whole last quarter of data to be able to compare with previous years. Anytime we see trend data for 2020, it’s going to have an asterisk that it’s showing only three-quarters of the data. And I think that’s probably happening all over with school districts across the country,” Vivian said.  

Designing the School Reopening Surveys 

Let’s dive into the survey that was featured on the news. 

School leaders requested a “survey of families and staff to see where their comfort level is with these three models that we’ve developed, what they’re concerned about and their needs are.” The school system was considering three models: 100% in-person, 100% virtual, or a hybrid. 

Vivian’s office designed and administered two surveys: one for parents and one for all school-based staff, such as administrators, office staff, and other professionals in addition to teachers. 

They reviewed similar surveys from other school districts, and then added questions specific to their own county. 

Parents were asked about their spring 2020 online learning experience; which of the three reopening models they preferred; whether they had computer access for distance learning; and more. 

Staff were asked whether they received the support and resources they needed in spring 2020; whether they would be comfortable being inside a classroom with physical distancing measures in place; and whether they were comfortable taking their temperatures and wearing face coverings. 

Then, the surveys were translated into Spanish, and links were emailed to parents and staff, and further promoted on social media.  

Collecting the Survey Responses 

Vivian said, “We knew we were going to get a lot interest in it because it’s such a hot topic. We do a school climate survey every spring for staff and parents. The parent survey usually gets 11,000 to 12,000 responses. This survey had 46,000 parents respond. And then about 6,000 staff responded (usually only a couple thousand respond). It was huge.”  

Vivian’s office designed the surveys, collected 52,000 responses, and compiled the data into reports and a slideshow within just two weeks. 

Visualizing the Data 

Vivian color-coded the data to make the categories easier to navigate. For example, they consistently used teal for elementary schools, orange for middle schools, gold for high schools, and blue for the county. 

Vivian also drew attention to key findings by making pieces of the visuals darker or lighter: 

Vivian also said that, “On the titles of the slides, I tried to pull out what the main finding was, to highlight what they should be looking for.” 

The Reporting Model 

I personally love the reporting model that Vivian’s office followed. 

They developed two detailed reports plus a slideshow with key findings. And, the news story provided a high-level overview. There’s something available for every type of audience. 

Vivian and her colleagues have evolved their communications strategy. “When I first started there 14 years ago, we were doing the full Dusty Shelf Reports.  Over the past few years, we’ve realized that our decision makers need data to make policy and decisions within a few weeks. They don’t have time to wait for a year long, in-depth program evaluation. We’ve been kind of gearing up for a fast response model of reporting anyway, but this was really fast.” 

Two 13-Page Technical Reports 

Vivian’s office shared detailed results within two 13-page reports, one for the parent survey and one for the staff survey. 

These reports contained tables of both quantitative and qualitative survey results. 

The Slideshow 

Vivian and her colleagues also developed a slideshow, which would be presented at a school board meeting. The slideshow was viewed by school board members, administrators, staff, and parents. 

The News Story 

Finally, the news article and 90-second video provided a high-level overview of the survey results. 

Vivian said she was very surprised to see that someone on a Facebook group she’s a member of linked to the new story and said, “LCPS was on the news today!”  

“I thought, ‘I wonder what they said?’ And I clicked on it, and watched it, and I almost fell out of my chair, literally. They had used the graphs from my presentation!” she said.  

The news station used several of Vivian’s graphs, even enhancing one by circling one set of columns that they wanted to draw attention to.  

The news story combined the survey’s quantitative data with audio clips from the public comment portion of the school meeting: 

“I knew that people would be looking at the report, but I thought mainly like the school board, people who tuned in to watch the school board meeting,” Vivian mentioned. “But I didn’t realize that people would take anything from it and use it in a different way.” 

Reactions from the School Board and Parents 

And, a couple days after the school board meeting, Vivian was out shopping in a store and overheard a couple parents discussing statistics from the report. 

The school board also gave Vivian’s office good feedback on the data. 

Loudoun County Public Schools had considered three models for the 2020-2021 academic year: 

1. 100% in-person 

2. 100% virtual 

3. A hybrid model 

The school system opted for the hybrid model, in which half the students would be in school at a time. Parents will also have the option to opt-out and follow 100% virtual learning.  

Note: Vivian reached out to let us know that “as typical of the times we are in, this week the school board and superintendent changed the reopening plan to be all distance learning at first, with a phased approach to the hybrid model. You can see their revised plan here: Revised Plan for 2020-21.  

Learn More about Vivian’s Survey 

The survey results were shared publicly on the school board’s site.  

• The slides that were presented at the school board meeting in June 2020.
• The tables from the parent survey.
• The tables from the staff survey.

Read the WUSA 9 story, Loudoun County School Board votes on reopening plan, and watch the 1.5-minute video where Vivian’s work was featured.

Connect with Vivian Jefferson on LinkedIn.

Your Turn 

Comment below. Let us know which part of the conversation resonated with you the most.  

The post Can Your Dataviz Have an Influence on School Reopening Plans? appeared first on Depict Data Studio.