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Charting Success: A Beginner’s Guide to Data Visualization

‘Choosing the Best Chart for Visualization.’

By Syed Atheequr RahamanPublished 3 months ago 3 min read

This is my first article, and I am excited to write about a topic that the world is currently interested in: So, let’s dive deeper into my thoughts.

In the field of Data Science or analysis, there is a fascinating term called ‘Storytelling’. Can you imagine data merely as an Excel sheet with rows and columns, or can you envision it as beautiful and attractive graphs with ups and downs, such as line graphs and bar graphs? These visualizations are effective for understanding the underlying patterns in data. By looking at various charts, we can easily foresee what will happen to the data in 30 years or understand what is currently happening. This is what we refer to as storytelling.

As we all know, data visualization is best practice. However, just like the multitude of options we had after high school, there are numerous charts and diagrams available to represent data. So, how do we choose the best one? Let’s explore.

First of all, instead of opting for the best, start with the simple ones. Keep in mind that the simpler the graph, the easier it is to understand the pattern. For example, in text processing, you can visualize importance of the words as word cloud rather than opting for more complex visualization techniques. This straightforward approach helps viewers understand the importance of words in a particular document without any effort.

Before choosing a better visualization technique, observe your data. Consider the columns and how various features could be logically correlated by applying statistical methodologies and pre processing techniques. While this might seem boring initially, trust me, it becomes interesting when done repeatedly. Discovering things for yourself increases curiosity, doesn’t it?

The next step is to become familiar with certain graphs. Start with line graphs, histograms, bar charts, and scatter plots. Practice by representing some data available on the internet using these graphs. By doing so, you may immediately think of representing data in a particular graph when looking at it. For instance, if you have continuous variables, a histogram would be a good choice. If you want to show ranking, an ordered bar chart would be better. For representing the relationship between two variables, use a scatter plot, and if the variable changes over time, opt for line charts. These charts can reveal various patterns in the data, increasing its business value.

Another important consideration is your audience. Different audiences have different informational needs, and they perceive things in sometimes wildly different ways, influencing their actions. When building visualizations, ask yourself and your users, ‘What are we trying to accomplish as we analyze the dataset?’ This is why conducting user interviews, defining requirements, and wireframing are so important. Some clients may expect high-end graphs, but don’t lose hope if you are not familiar with them. If you can represent the data with a graph you are already comfortable with, search online for alternatives. If an enhanced or advanced version of the graph you’ve used before exists, it will likely visualize the same data. Remember, there’s a first time for everything you do. keep in mind that every time you open your eyes to explore the possibilities, you contribute to revealing the beauty that lies within the world of data.

In conclusion, the world of data is vast and intricate, and the art of choosing the right chart for visualization is a skill that can greatly enhance our understanding of it. Remember, as you embark on this journey of data visualization, simplicity often holds the key to effective communication. Start with the basics, observe your data, and practice with different chart types.Moreover, never forget your audience. Understanding their needs and perceptions is vital for crafting visualizations that resonate with them. Ask yourself, ‘What are we trying to accomplish as we analyze the dataset?’ This question, coupled with user interviews and careful requirements definition, ensures that your visualizations align with the intended goals.

As you progress in your data visualization journey, embrace the iterative nature of the process. You may find new and enhanced charting options that bring a fresh perspective to your data.

So, let’s continue to tell compelling stories through our visualizations, unlocking valuable insights and enriching our understanding of the data that surrounds us.

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