Decision-makers generally do not use raw data to make decisions; they prefer data be summarized in easily understood formats that facilitate efficient decision-making. This course introduces data manipulation and visualization, both critical components of any data science project. This course introduces two commonly used data manipulation tools in the Python ecosystem: NumPy and Pandas. In addition, the Python ecosystem also includes a variety of data plotting packages such as Matplotlib, Seaborn, and Bokeh — each of which specialize in particular aspects of data visualization. This course will give you experience integrating NumPy, Pandas, and the plotting packages to create rich, interactive data visualizations that help drive efficient decision-making.
It is recommended to only take this course if you have completed Constructing Expressions in Python, Writing Custom Python Functions, Classes, and Workflows and Developing Data Science Applications or have equivalent experience.
How It Works
Who Should Enroll
- Data analysts and business analysts
- Database managers
- Technical and systems analysts
- Programmers interested in data science
- Business managers