Types of Charts in Tableau

 

Types of Charts in Tableau


Tableau is a data visualization tool that allows drawing different charts and graphs using Show me with just simple drag and drop of features.


Heat Map, Highlighted Table, Symbol Map, Filled Map, Pie Chart, Horizontal Bar Chart, Stacked Bar Chart, Side-by-Side Bar Chart, Tree Map, Circle View, Side-by-side Circle View, Line Chart (Continuous),Line Chart Discrete, Dual Line Chart, Area Chart (Continuous), Area Chart (Discrete), Dual Combination, Scatter Plot, Histogram, Box and Whisker Plot, Gantt Chart, Bullet Graph, Packed Bubble that are available depending on the number of dimensions, measure, bins, etc.



Bar Chart

  • Represent data in rectangular bar

  • Used to compare data across categories, highlight trends, differences, and outliers

  • More effective when data can be split into multiple categories

Line Chart

  • Line chart connects individual numeric data points

  • Use to compare data over different periods

  • A straightforward way to visualize change in one value relative to another

  • Minimum Requirement: 1 Date, 0 or more dimensions, one or more measures

Pie Chart

  • Represents Segment-wise data

  • Used to show relative portion/percentage of information

  • Powerful for adding detail to other visualization

  • Distinct colors are used to describe different portions of features

Map

  • Use to show geocoded data like postal code, state, country

  • Highlights geographical trends in the most accessible and efficient way

Scatter Plot

  • Used to visualize the relationship between two measures

  • Scatter Plot investigates the relationship between different variables

  • The plot is created when both row and column shelf have at least one measure

Gantt Plot

  • Used for comparison of data between categories

  • Use for displaying a project schedule

  • It has time-series data that is available in a natural and easy to understand format

Bubble Chart

  • Use to visualize measure and dimension in bubble form

  • It shows the concentration of data along the axes

  • Having different sizes and colors, it becomes easy to analyze

Histogram Chart

  • A histogram displays the shape of the distribution

  • Represents how data is distributed across different groups

  • Used to understand the distribution of the data

Bullet Chart

  • It is an indicator to show the performance of the measure

  • Compares a primary measure to one or more other measure and present it to define a performance matrix

  • Use to evaluate the performance of a matrix against a goal

Heat Map

  • The best way to compare data across different categories is by using colors

  • It shows the relationship between two features

  • Created using one or more dimensions and a measure

Highlighted Table

  • It can be considered as an extension of the Heat map

  • Highlighted table provides detailed information on the heat map

  • It is similar to a text table, and the only difference is data is displayed using different colors

Tree Map

  • Rectangular chart representing data in nested rectangle

  • Use to show hierarchical data as a portion of a whole

  • It makes efficient use of space to display the entire data at once

Box-and-whisker Plot

  • Use to show the distribution of a set of a data

  • Box-and-Whisker plots are divided into two parts

    • Box: Consists of the median, first, and third quartile of the data 

    • Whisker: Consists of the data with 1.5 times IQR (IQR = first quartile – third quartile)

Conclusion

In this article, we have discussed different types of charts in Tableau: Bar, Line, Pie, Map, Scatter Plot, Gantt, Bubble, Histogram, Heat, Highlighted Table, Tree Map, and Box-and-Whisker Plot.

Hope this article will help you in your data analyst journey.


Important Links

Home Page 

Courses Link  

  1. Python Course  

  2. Machine Learning Course 

  3. Data Science Course 

  4. Digital Marketing Course  

  5. Python Training in Noida 

  6. ML Training in Noida 

  7. DS Training in Noida 

  8. Digital Marketing Training in Noida 

  9. Winter Training 

  10. DS Training in Bangalore 

  11. DS Training in Hyderabad  

  12. DS Training in Pune 

  13. DS Training in Chandigarh/Mohali 

  14. Python Training in Chandigarh/Mohali 

  15. DS Certification Course 

  16. DS Training in Lucknow 

  17. Machine Learning Certification Course 

  18. Data Science Training Institute in Noida

  19. Business Analyst Certification Course 

  20. DS Training in USA 

  21. Python Certification Course 

  22. Digital Marketing Training in Bangalore

  23. Internship Training in Noida

  24. ONLEI Technologies India

  25. Python Certification

  26. Best Data Science Course Training in Indore

  27. Best Data Science Course Training in Vijayawada

  28. Best Data Science Course Training in Chennai

  29. ONLEI Group

  

Popular posts from this blog

Top Six Reasons Why you should Consider Making a Career in Data Science

Image
    1) Demand for Data scientist  Shortly, the data analytics industry's size is projected to triple in the global proportion of I.T. spend, but no time scale can be provided for how much is expected to shift in the future. Employers and their workers who can use and interpret data regardless of the scale Everybody is looking to identify staff that have both the knowledge and ability to grasp and articulate data , as well as others that can present results to the management in a helpful manner that aids the business.  2) Career Growth and Salaries  Everyone is desperately in need of a fresher data scientist and a mid-level or advanced data scientist, with all job functions of the latter becoming even scarcer. Now that the Information Technology sector is poised to take the next step on the learning curve, many middle-level managers and professionals who work in many different areas are seeing their careers flat line as a result. It is critical to retain knowle...
Read more

How to Leverage Data Science Trends for Improved Decision Making

Image
  How to Leverage Data Science Trends for Improved Decision Making Data science is a rapidly evolving field that has become increasingly important in the modern business landscape. By utilizing data science techniques and tools, organizations can derive valuable insights from the vast amounts of data they collect, enabling them to make informed decisions and gain a competitive advantage. In this article, we will explore how data science trends can be leveraged to improve decision making. We will discuss the various applications of data science in decision making and highlight the best practices and techniques for incorporating data science into your organization's decision making processes. 1. Introduction to Data Science Trends The Evolution of Data Science Data Science has come a long way in recent years, with emerging technologies and breakthroughs in machine learning and artificial intelligence. It started as a simple idea: using data to understand and solve problems. Howeve...
Read more

What Skills Are Needed in Digital Marketing?

Image
  What Skills Are Needed in Digital Marketing?  Digital Marketing training will help students to create a baseline to enter into the marketing industry. ONLEI Technologies recommends all the department students to go with this training .  Data analytics skills are important for understanding how well your marketing campaigns are performing and where they can be improved. Finally, social media and other online skills are a must. You need to be skillful in writing content along with communication skills to effectively tell your product's story to your consumer base.   You may also take courses or bootcamps specifically in digital marketing. Google and Facebook generate more revenue than traditional media companies because they have more eyes on them. That's why digital marketing matters; it is where the attention is. Promoting products and services through digital media, social media platforms, and digital technology is known as digital marketing .  Digital ...
Read more