Ataccama
  • Plataforma
    Enterprise Data Quality Fabric
    Enterprise Data Quality Fabric
    Arrow right
    How It Works
    Visión general de la plataforma
    Arrow right
    Calidad de los datos
    Calidad de los datos

    Comprobaciones automatizadas de calidad de datos, supervisión, detección de anomalías y corrección

    Reference Data Management
    Gestión de datos de referencia

    RDM centralizado, autoría, jerarquías y sincronización

    Master Data Management
    Gestión de datos maestros

    Dominio multidominio, administración, emparejamiento de IA, suministro flexible de datos

    Integración de datos
    Integración de datos

    Extracción, transformación y suministro flexible de datos

    Catálogo de datos
    Catálogo de datos

    Descubrimiento automatizado de datos, glosario empresarial y mercado de datos

    Historias de datos
    Historias de datos

    Cuente historias atractivas con sus datos

    Despliegue
    Opciones de despliegue Plataforma como servicio Local e híbrida Arquitectura e integraciones
  • Soluciones
    Volver
    Centrado en
    Implementación de la gobernanza de datos

    Una pila de herramientas para empezar rápido y mantener la gobernanza de los datos

    Tejido de datos

    Active los metadatos y automatice el mapeo, la extracción y el suministro de datos

    Gestión de Big Data

    Ingiera datos fiables, controle su lago de datos y procese datos.

    Vista única de los datos

    Establezca una única fuente de la verdad y cree una visión única para todos.

    Ver todas las soluciones industriales
    Desde
    Banca, Seguros, Finanzas

    Validación de datos en la entrada, Customer 360, cumplimiento normativo

    Cuidado de la salud

    Patient 360, datos fiables para pruebas y HCE, cumplimiento de la HIPAA

    Venta minorista

    Validación de datos en la entrada, Customer 360, enriquecimiento de datos, datos de referencia

    Gobierno

    Citizen 360, intercambio y protección de datos, ciudades inteligentes

    Ciencias de la vida

    MDM de productos, datos limpios para estudios clínicos, transparencia de gastos

    Telecomunicaciones

    Customer 360, enriquecimiento de datos, seguimiento de equipos, privacidad de datos

    Transporte

    Monitorización de equipos, Customer 360, datos de referencia, privacidad de datos

    Última lectura
    Data for Good: Enabling Data-Driven Altruism with Data Governance
    Data for Good: Enabling Data-Driven Altruism with Data Governance

    Using data for helping solve social causes comes with many challenges. How can social organizations use the data efficiently? Learn in this article.

  • Clientes
  • Empresa
    Volver
    Contáctenos
    Programar una llamada Contáctenos Suscríbase al boletín de noticias Chat en vivo
    Empresa
    Sobre nosotros

    Todo sobre nosotros, quiénes somos, visión, liderazgo, oficinas

    Kit de medios

    Descargue nuestros activos de marca, fotos y capturas de pantalla de productos

    Carreras

    #NotYourAverageJob

  • Recursos 1
    Volver
    Recursos

    Vídeos, artículos, consejos de nuestros expertos y líderes de opinión

    Noticias Historias de éxito Blog Monográficos Seminarios web Demos
    Todos los recursos
    Asistencia

    Obtenga respuestas a sus preguntas técnicas

    Documentación Formación Base de conocimientos Comunidad de usuarios Asistencia al cliente
    Eventos

    Asista a nuestros eventos virtuales y presenciales, próximamente

    Future of Financial Services, Melbourne 2022

    Jul 20

    Innovate VIC 2022

    Jul 21

    Elegido a mano para usted
    title
    What Is Data Quality and Why Is It Important?

    Learn what data quality is, why it is important, what costs and risks bad data carries, and how you can get started with data quality today for free.

  • Socios
    Volver
    Socios
    Hágase socio

    Conozca nuestro modelo de asociación, únase a nosotros

    Portal de socios de Ataccama

    Inicie sesión en nuestro portal de socios para acceder a todas las herramientas y recursos esenciales.

    Oportunidad de registro

    Registre el cliente potencial y obtenga una recompensa de socio

    Nuestros socios

    Vea nuestros socios tecnológicos, integradores de sistemas y socios de entrega

  • Probar ahora
    Volver
    Meeting
    Reserve una reunión

    Hable de sus necesidades y requisitos con uno de nuestros representantes de ventas.

    Herramientas gratuitas
    Perfiles web

    Creación de perfiles con un solo clic en su navegador. Simplemente arrastre y suelte un archivo.

    Analizador de calidad de datos

    Herramienta avanzada de creación de perfiles. Se instala en minutos en Windows.

    Historias de datos

    Modern data visualization. Present complex facts and wow all stakeholders.

    Ver todas las herramientas gratuitas
  • Contact
Ataccama
Login
Usuario
Iniciar sesión o registrarse
Contact
Logo with rockets
Announcing
$150 Million Growth Investment
BainCapital logo
Learn more
Blog

Why Pie Charts are Evil 

6 minutes read

Pie charts were probably the second or third graph type your math teacher introduced to you. Maybe they even forced a protractor into your hand so you could get all the angles and percent ratios correct. 

Today, pie, donut, and gauge charts have been exiled from the data analytics and visualization community. Data experts rave about how they are “inadequate,” “bad,” or even “evil.” But why do pie charts have such a bad reputation these days? Let’s find out.

Pie charts take up too much space

Whenever visualizing data, you have limited space to work with. Either in the confines of a PowerPoint slide or as one step in your data story, you have to treat that precious digital real estate with care and fill it with the most value for the viewer/reader. 

The problem with Pie, Donut, and Gauge charts is that they use more space than alternatives that provide the same value (e.g., a bar chart). This is due to two reasons: the nature of their shape and how they depict information. 

  • Pie, Donut, and Gauge charts use area to give value to a single category, whereas bar charts just use distance. 
  • These charts are circular, which creates unnecessary space around the chart object.   

Pie charts aren’t as readable as other chart types

Graphs are useful when a picture of the data makes meaningful relationships visible (patterns, trends, and exceptions) that could not be easily discerned from a table of the same data.

- Stephen Few “Save the Pies for Dessert.”   

When looking at a pie, donut, or gauge chart, it’s difficult to tell how much larger one portion is than another. This is because the human eye and mind are much better at comparing distance instead of area. After all, you only have to assess one dimension instead of two.

For example, if I asked you “how much bigger is ‘Pinot Grigio’ than ‘Tempranillo’ on the chart below, it would be challenging to give an exact answer. 

Source


However, with a bar chart, you might have an easier time finding your answer: ‘Pinot Grigio’ is about 3X larger than ‘Tempranillo.’

Source

People also have trouble with their perception of angles. It’s easier for people to judge the magnitude of a slice when it has nice round 90° angles like 0, 25, 50, 75, and 100%. However, humans can’t easily perceive the differences in angles that fall outside those numbers, and, with no scale, it becomes even more problematic. 

We often overestimate obtuse angles and underestimate acute ones. Even when you have easy-to-read values (like 90°, 180°, 360°), something as simple as rotating the chart can still throw off your perception. 

As you add more segments, this problem gets worse. Pie charts also have problems fitting labels on the graph when there are too many variables, forcing the use of legends and wasting the viewer's time switching their eyes back and forth between the legend and the chart. When the slices get too small, people like to add labels and numeric values to each slice. However, if you’re adding in names and numbers, you might as well be looking at a table. 




Source

Pie Charts can’t convey more information without becoming overly complex

Pie charts don’t allow as wide a range of options for additional data points as bar charts and other types. There are several ways to enrich bar charts with additional data points that don’t make the graph look too crowded or hard to read. You can see this in the bullet chart below, which adds additional values to display targets and ranges. 

Source

However, adding these elements to a pie chart makes it harder to read. The same can be said for 3D renders of pie charts that don’t add additional information. Instead, they will just add complexity and require you to take another dimension into consideration. They will also distort the images, as whichever slice is farther away will look smaller.


Source


Source

Best Alternatives to Pie Charts

In 90% of cases, you can use bar charts instead of pies. They can display almost any information a pie chart can, and they’re easier to read. The only question is, what type of bar chart should you use? Remember that no matter what kind of chart you choose, your decision should be based on: 

  • Your use case
  • The data you want to chart
  • The space you have available 

Many people think that percentages are best displayed on pie charts. However, bar charts are still easier to interpret for this type of data because you only have to assess one dimension. If space is limited and you only have a few values, a stacked chart can also be helpful.

On the other hand, a classic bar chart is an excellent choice when you have a lot of values and want your viewers to make a comparison quickly. 


Source

Some people choose pie charts just to add variety to their presentations. However, using the correct tooling is far more important. For data visualization, the proper tooling is always whatever is easiest to read and interpret.  Better to be understandable than exciting. If anything, having the same type of charts makes your reporting more consistent.

What are pie charts used for? 

While we do find pie charts to be inferior, no rule is written in stone. Pie, donut, and gauge charts can still fulfill a purpose. One example is the use of gauges in cars. 

Some reasons you might choose pie charts are:

  • When there is only one slice of the pie, it’s easier to show its’ share of the whole value. 
  • You have a square (not rectangular) space for visualization
  • Users are used to this chart from past visualizations
  • It’s too complicated to display the information as a bar graph (e.g., analog measuring devices).
  • Data is in %, and only two values are displayed.
    • This allows the user to see data and percentages, and they can quickly reference the dimensions based on 50% 

Tips for using pie charts: 

  • Order sections from smallest to largest starting at the 12 o’clock position
  • Don’t have more than five sections
  • Don’t use them to display change over time
  • Don’t compare pie charts to one another

Data visualization is more than charts

Charts are an excellent means for communicating the message behind your data. However, it’s even better if you can use your charts in the context of a narrative and present them in a way that tells a story. 

Our product, Data Stories, can help. Data stories is a scrollable data visualization tool that connects directly to your data sources to produce engaging presentations. It has 20+ chart options to choose from (including pie charts) and can also generate conclusions using AI insights. Try it out here! 

Start telling stories with data today

Ataccama Data Stories are free.
10 public stories • 10 datasets • 10 million data rows

Start telling data stories

Related articles

How to Tell Stories with Data: 5 Steps to Make it Work

How to Tell Stories with Data: 5 Steps to Make it Work

Blog
Ataccama Innovate 2022 Conference on Demand

Ataccama Innovate 2022 Conference on Demand

Conference
Privacy Policy Cookie Policy Terms of Use Ethics Hotline
Espanol
English Deutsche Pусский Français Espanol
© Ataccama 2022
Cookies We value your privacy

We use cookies on our website to enhance your browsing experience. By using our website, you consent to the use of cookies. To understand more how we use cookies or how to change your preference and browser settings, please see our privacy policy.

Select cookies