Coding is an important part of data science, but it’s not the only aspect of it. Data science is a multidisciplinary field that combines aspects of computer science, statistics, and domain expertise. While coding is essential for cleaning, transforming, and modeling data, it’s also important for a data scientist to have strong critical thinking and problem solving skills, as well as the ability to communicate findings and insights effectively to non-technical stakeholders.
In practice, a data scientist might spend a significant portion of their time writing code to perform data analysis, but they will also spend time working with stakeholders to understand their needs, collecting and cleaning data, performing exploratory analysis, building models, and communicating results. The amount of time spent coding can vary depending on the specific project and the role of the data scientist, but it’s generally a significant part of the job.