Learn pandas with online courses and programs
Manipulate and analyze data effectively to gain valuable insights. Learn how to use the Python library pandas with edX.
What is pandas?
pandas is a powerful Python library used for data manipulation and analysis. It is an essential tool for anyone working with data, from data scientists to business analysts. pandas simplifies the process of loading, cleaning, transforming, and analyzing data.
It introduces two fundamental data structures: Series and DataFrames. These structures allow you to work with data in an organized and intuitive way. You can perform various operations on data using pandas, such as filtering, sorting, and aggregating, making it a versatile tool for data analysis.
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pandas course curriculum
Learners could explore a wide array of topics and techniques for effective data manipulation and analysis in a pandas course. Some examples of content include:
Installing and importing pandas
Types of data structures
Methods to read data
Data cleaning and exploration
Data manipulation methods
Visualizing data with pandas
Learning about how to use this library can supplement your knowledge of Python and data science. edX offers a variety of educational opportunities for learners interested in studying these topics, as well as a host of other disciplines. A boot camp can provide flexible hands-on learning for those who want to upskill quickly, while executive education courses are designed for busy professionals. You can also pursue a more comprehensive curriculum in a bachelor’s degree program or, for more advanced learners, a master’s degree program. Find the right learning path for you.
Explore jobs that use pandas
Understanding pandas equips learners with essential data manipulation and analysis skills, making it useful for professionals in various fields. It empowers you to efficiently work with data, extract meaningful insights, and make data-driven decisions. Some examples of careers that might use pandas include:
Data analyst: Uses pandas to clean, process, and analyze data to extract valuable insights. Data analysts might work in industries like finance, marketing, healthcare, and e-commerce.
Business intelligence analyst: Uses pandas to evaluate business processes, perform market research, and generate reports that help companies make informed strategic decisions.
Data scientist: Leverages pandas to perform advanced data analysis, build predictive models, and communicate data-driven recommendations to guide decision-making in organizations.
Machine learning engineer: Uses pandas to prepare and preprocess data for machine learning models, as well as to evaluate model performance and make predictions.
Each of these roles will have different education and skills requirements. For example, you may be able to build relevant skills in a coding boot camp. However, some employers may seek candidates with a degree in data science depending on the role. Before deciding on a specific learning path, research the positions you hope to pursue and align your coursework with your career goals.
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