To Access the project Click here!
To Read More about my project on Medium Plaese click here More On Medium Blog
The ability to create eye-catching visuals is not an inherited skill. The skills required for most effectively displaying information are not intuitive and rely largely on principles that can be learned. There are, indeed, some visualization techniques that are best left to designers, but there are others, e.g., audit findings, key performance indicators (KPIs) and cyber-monitoring indicators, that do not need the designer’s touch. Scientific evidence supports the importance of data visualization. As Neil DeGrasse Tyson once said, “The good thing about science is that it’s true whether or not you believe in it.” And there is as much science behind data visualization as there is behind analytics. The brain receives 8.96 megabits of data from the eye every second. The average person comprehends 120 words per minute when reading, which is equivalent to 81.6 bits of data per second.1 Humans are not wired to read quickly; they are wired to visualize quickly. Brains perform more efficiently and more information is retained when the learning comes from visuals. A well-designed dashboard allows the viewer to analyze massive data sets at a glance. Learning how to represent data in a way that immediately tells a story, sparks an insight or provokes discussion is as important as being able to run data analytics. Data visualization is comprised of a set of tools and techniques to create graphs (also called charts or diagrams) that, when used the right way, are extremely powerful. It is not about flashy 3-dimensional rainbow graphs. Data visualization is about being simple and representing data effectively. Before considering design principles, there are important layers to be covered in preparation for the design layer. I have recently been infatuated with Plotly and Dash libraries , these visualization tools provide extraordinary capabilities to build and deploy interactive web dashboards with few lines of python code , I realized that plotly and dash have an artististic element attached to them , as they give users the ability to play with the data and tweak the output results based on their desires , my fascination with Plotly and dash is overwhelming in the sense that ever since I began to use them I never stopped , even though I always stumbled across hurdles and obstacles , but Plotly has the biggest online data science supporting community , whenever one encounters problems , they are dedicated to provide you with efficient and effective answers totally for free , and I am really delighted to be a member of this community , I do consider Plotly and dash to be the front end of data visualization as an art not like others with boring and tedious charts , Plotly provides mesmerizing plots that keep users and developers equally gravitated and fascinated with its high degree of interactivity .
When making a graphic, it is important to understand what the graphic is for. After all, you usually won’t make a chart that is a perfect depiction of your data — modern data sets tend to be too big (in terms of number of observations) and wide (in terms of number of variables) to depict every data point on a single graph. Instead, the analyst consciously chooses what elements to include in a visualization in order to identify patterns and trends in the data in the most effective manner possible. In order to make those decisions, it helps a little to think both about why and how graphics are made and not exaggerating the depicted data is also an important ethical consideration , whenever we plot a chart , it must be an honest representation of the data , whilst choosing a set of appropriate colors for chart series and backgrounds which is quintessentially a work an artist performs on a daily basis with each masterpiece they draw . The choice of colors is of paramount importance and the data scientist/analyst must take the time to choose the appropriate colors that convey the message in an effective manner without diverting the attention away from the message the dashboard intends to deliver ,colors that are too shiny will not be comforting to the human eye , unity of colors and RBG degrees are extremely important considerations in that respect .
Contrast, Repetition, Alignment and Proximity simply abbreviated as CRAP are also important considerations in designing a dashboard, Plotly and Dash with their components allow you to contrast colors , repeat themes, align and position charts in close proximity to each other by taking advantage of HLML and Bootstrap Components to satisfy CRAP requirements.
In this Project I wanted to accomplish an added interactivity by using locations on choropleth map as Input to the call back function so that whenever a user clicks on a map the rest of the charts get updated accordingly, this is an extremely important feature in data visualization, we see in my Microsoft power bi, Business intelligence analysts need this feature the most Written by :
Data Scientist / Analyst
Abha International Private Hospital Saudi Arabia
February 16 /2023
Access to the project:
The dashboard is available on this link!