Visualization means representing something in the form of images, charts, or photos. Data visualization means representing data in the form of charts, graphs. There are several data visuals in data science: histogram, pie charts, graphs, and charts. By using the visualization, we can check the behavior of data after applying certain data analytics and machine learning algorithms on the data set. For text data, data visuals are different. In the same way, for audio or video data, visuals are different. Are you looking to become a Data Scientist? Go through 360DigiTMG’s PG Diploma in Data Science and Artificial Intelligence!
The data science tools have built-in features for the visualization of data. By visualization of data, the data scientists come to know about meaningful information about the data set. Moreover, after applying the data visualization, data scientists come to know about the basic structure of data science. Then they choose a suitable machine learning algorithm for the data set according to the requirements of the scenario and structure of data. Want to learn more about data science? Enroll in the best Data Science courses in Chennai to do so. Looking forward to becoming a Data Scientist? Check out the Data Science Course and get certified today.
Techniques of Data Visualization:
Know Your Audience:
While talking about the data science visualizations, the data scientists should use the visualizations according to the audience’s understanding level. If the client or business owner doesn’t know anything about data science, then you should use various data visualizations for the understanding of the business owner or client. On the other hand, if the business owner or client understands data science, you can use some of the data visualizations to get some useful information about the data according to the situation. Also, check this Data Science Institute in Bangalore to start a career in Data Science. Earn yourself a promising career in data science by enrolling in the Data Science Classes in Pune offered by 360DigiTMG.
Choosing the right chart or graph:
The charts, graphs, or data visuals are used according to the need of the audience. The data visuals are also selected according to the algorithms’ need to know whether the specific machine learning algorithm can be applied to the data set or not. For example, if you have to compare a specific business firm’s productivity, you can use a simple line graph and pie chart for this purpose. But the pie chart will be more suitable for this situation. Hence, a data scientist can choose a data visualization way according to the business needs, understanding of the audience, and machine learning algorithms’ requirements.
Choosing the Suitable Size of the Visuals:
Many data scientists do not know about the suitable size of the data visuals. If you choose more features in the graph, chart, or pie graph, you should select the size of the data visuals more accordingly. There is no hard and fast rule for selecting the size of the figure. Even the size of the visual figure has no importance. So you can choose the proper figure size to avoid any problems in understanding the graphs or charts.
Choosing Color Of The Visual Figures:
Colors used in the graphs, charts, or pie charts don’t have much importance. The colors and size of the visual figures have nothing to do with the visual figures. But it is a common practice to use the green colors to show the positive trends of the data and the red colors to show the negative trends in the data.
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