Data Quality 201: Data Visualization

Using graphs or charts to help visualize data can be an effective way of 

exploring and communicating important or complicated information. When 

used incorrectly however, graphs or charts can complicate, distort, or misrepresent data. Misleading graphs or charts might be intentional or might be the 

result of errors. Whatever the reason, presenting data in a misleading way can 

lead to incorrect conclusions.

This guide provides examples of misleading data graphs and charts and 

provides guidance on how to identify and avoid common errors when 

presenting data.
Misleading Bar Charts

Bar charts 

Bar charts are used with discrete 

data (e.g., number of people) 

and provide a visual display for 

comparing quantities in different 

categories or groups. They help the 

reader to see relationships quickly. 

Misleading Axis: In Figure 1 below, both bar charts show 44% of Older 

American Act Title III service recipients living alone and 56% not living 

alone. The bar chart on the left is misleading, however, since the Y axis 

starts at 40% and ends at 60% and therefore appears to show very 

large difference between the results, suggesting that most service 

recipients do not live alone. In reality the difference is much smaller, 

with only slightly more than half of service recipients not living alone. 

The bar chart on the right presents the data accurately and in context of 

the range of possible values, with the Y axis starting at zero and ending 

at 100. In addition, the bar chart on the right includes value labels, 

showing the actual percent for both categories. As a rule, bar charts 

showing percentages should end at 100%. Value labels should be used 

when they help the reader to know the individual value for each 

category or group (vs. the relative size or rank).

100%

80%

60%

40%

20%

0%

Living Alone Not Living Along

56%

ii

44%

Figure 1. Percent of Older Americans Act (OAA) Title III service recipients living alone.

60%

55%

50%

45%

40%

Living Alone Not Living Along

Accurate: Y axis starts at zero and 

displays the entire range. Bar chart 

also includes value labels.

Misleading: Y axis does not start at 

zero and shows a small range.

i
Misleading Bar Charts, Cont’d

100%

80%

60%

40%

20%

0%

Living Alone Not Living Along

56%

ii

44%

Living Alone Not Living Along

56%

i

44%

Misleading: Y axis scale is not shown. Accurate: Y axis scale is shown.

In Figure 2 below, the first chart is misleading because the scale is difference between the number of service recipients living alone and 

not shown. Removing the scale from the Y axis, as shown below in the those not living alone. 

first chart, makes it impossible to draw conclusions about the actual 

Figure 2. Percent of OAA Title III service recipients living alone.
306,867

 2000 2001 2002 2003 2004 2005

350,000

300,000

250,000

200,000

150,000

100,000

50,000

0

231,889

Misleading: Data are 

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

350,000

300,000

250,000

200,000

150,000

100,000

50,000

0

Accurate: All data are 

presented, showing the 

trend over more time.

306,867

231,889 198,502

Misleading Line Graphs

In Figure 3 below, each line graph shows the total annual number of 

complaints brought to, or initiated by, the Long-Term Care Ombudsman Program, which is required to investigate and resolve complaints 

on behalf of residents of long-term care facilities. The first line graph 

shows the total number of complaints for 2000–2005 and suggests 

a steady increase in the number of complaints over time. The presentation is misleading, however, as it covers just a small select period 

of time. The second line graph, which shows the total number of 

complaints for 2000–2018, provides more context and leads to a very 

different conclusion, with the number of complaints actually declining after 2005 and then remaining quite steady after 2012. If the start 

and end values of the data are important to know, the values should 

be added to the line graph. If the goal is to show just the slope of the 

line (i.e., the change over time), the values do not need to be shown.

Line graphs

Line graphs (line charts) are used 

with continuous data, providing a 

visual display of data or information that changes over time. They 

help to illustrate overall trends 

such as an increase or decrease in 

performance over time.

Figure 3. Total number of complaints of willful mistreatment of long-term care facility residents.

incomplete, including 

only the first few years 

of results.
 2011 2012 2013 2014 2015 2016 2017 2018 2019

80,000,000

70,000,000

60,000,000

50,000,000

40,000,000

30,000,000

20,000,000

10,000,000

0

Misleading: Y axis maximum is too high.

25,000,000

Accurate: Y axis maximum is 

appropriate to capture the range 

of values shown on the line.

20,000,000

15,000,000

10,000,000

5,000,000

0

 2011 2012 2013 2014 2015 2016 2017 2018 2019

Misleading Line Graphs, Cont’d

In Figure 4 below, each line graph shows the total units of homemaker services provided for OAA Title III recipients, using different Y axis 

maxima. The first line graph has a very high maximum (80,000,000), 

causing the graph to reflect less growth and a less steep line. 

The second line graph uses a more appropriate Y axis maximum 

(25,000,000) given the range of data points, and indicates a rather 

large growth in units of services over the years.

Figure 4. Total number of units of homemaker services provided to OAA Title III service recipients.
Figure 3. Rating of OAA Title III caregiver services. Figure 3. Rating of OAA Title III caregiver services by service recipients.

Fair 

5%

Good

16%

Poor 

2%

Excellent

45%

Very 

Good

40% Fair

5%

Good

16%

Poor

2%

Excellent

42%

Very 

Good

35%

Misleading: Percentages do not sum to 100. Accurate: Percentages sum to 100.

Title expanded.

Misleading Pie Charts

Pie charts 

Pie charts are best used for showing part–whole relationships 

(rather than comparing different 

parts). Generally, use a pie chart 

if one or two of the categories 

have a much higher value than the 

others. This type of chart allows 

the reader to see at a glance which 

categories have the largest shares 

of the pie. When creating pie 

charts, do not use more than five 

or six categories (pie slices), make 

sure there is a clear message and 

the slices add up to an even 100%, 

and label the pie slices rather than 

using a legend.

A misleading pie chart could result from using incorrect data or from 

choosing a chart format that may lead to misinterpreting the data. 

In Figure 3 below, both pie charts show how recipients of caregiver 

services rated the services (i.e., excellent, very good, good, fair, or 

poor). The pie chart on the left is misleading, however, since the 

percentages to do not sum to 100. The chart creator either used 

incorrect data or changed it (by accident or intentionally) when constructing the pie chart. Additionally, the label does not indicate who 

did the rating. The pie chart on the right presents the data accurately, 

with the percentages summing to 100 and the title expanded to 

indicate who did the rating. 
Misleading Pie Charts, Cont’d

A misleading pie chart could also result from choosing an inappropriate display format. For example, in Figure 4 below, a 3D “exploded” 

format is used for the first version, which makes it difficult to interpret 

and distorts the effect. The slice that is closest to the reader (Poor) 

appears almost as large as the one in the back (Good), even though 

it is only about two-thirds of its size (19.8% vs. 30.6%). The second 

version is a general pie chart that more accurately shows the sizes of 

the slices relative to each other.

Figure 4. Self-reported health status rating of OAA Title III case management service recipients.

Poor

19.8%

Fair

38.2%

Good 

30.6%

Excellent

1.8%

Very 

Good

9.5%

Misleading: The 3D effect distorts the results, making this slice 

appear almost as big as the one in the back.

Accurate: Regular pie chart that accurately displays the relative 

size of each slice.
Conclusion

For additional information on data quality issues, see the Data Quality 101 Infographic 

and Data Quality 202: Data Quality Standards.

For questions, contact ACL’s Office of Performance and Evaluation.

The examples provided highlight a few ways in which the 

actual presentation of data may be misleading. The 

examples do not represent an exhaustive list but are 

intended to provide general insights on how data may be 

inadvertently distorted and to identify potential pitfalls to 

avoid when creating and reviewing graphs and charts.

As a general rule, remember the following when creating 

and reviewing graphs and charts:

• Ensure that labels are complete and provide enough 

information for understanding the content of the 

graph or chart.

• Ensure that, when showing percentage data, all axes 

have labels and any axis showing percentages starts 

at zero and ends at 100%.

• Select appropriate scales for axes.

• If appropriate, include the number of people that 

the data represent.

• Include sufficient data to display an accurate 

representation of data trends. 

• Avoid using a complex design (e.g., “exploded” 

pie chart) that may distort the data.

• Accurately portray relative percentages/proportions.