Most data science projects that use Python will require you to access and integrate different types of data from a variety of external sources. This course will give you experience identifying and integrating data from spreadsheets, text files, websites, and databases. To prepare for downstream analyses, you first need to integrate any external data sources into your Python program. You will utilize existing packages and develop your own code to read data from a variety of sources. You will also practice using Python to prepare disorganized, unstructured, or unwieldy datasets for analysis by other stakeholders.
It is recommended to only take this course if you have completed Constructing Expressions in Python, Writing Custom Python Functions, Classes, and Workflows, Developing Data Science Applications, and Creating Data Arrays and Tables in Python or have equivalent experience.
Faculty AuthorChris Myers
Benefits to the Learner
- Read data from files, spreadsheets, websites, and databases
- Create a standard for organizing data within a dataset
- Filter, integrate, and prepare data for analysis
- Data analysts and business analysts
- Database managers
- Technical and systems analysts
- Programmers interested in data science
- Business managers
Applies Towards the Following Certificates
- Python for Data Science : Core Courses