Pandas is one of the most popular Python libraries, used for data analysis and manipulation. It is commonly used in data science, machine learning, and artificial intelligence.If you are going to work in any of these are as, you will want to be familiar withPandas.It's easy to use, open-source, and will allow you to work with large quantities of data. It enables fast and efficient data manipulation, aggregation, and pivoting, flexible time series functionality, and more.
This course will introduce the learner to the basics of data analysis with the Pandas library. First, you'll learn to work with two primary data structures in Pandas,Series and DataFrame. Then you will see how to read data from a file and explore input data using indexing and filtering. At this point, you are ready to start data preprocessing. You will see how to handle missing values and duplicate rows and to transform your data into a more efficient format.Next, you'll discover how to manipulate the data and do some processing. Finally, you'll delve into creating simple plots to visualize your data.
This course assumes no previous Pandas experience, but since Pandas is a package built for Python, you need to have a fundamental understanding of basic Python syntax.
Basic / intermediate experience with Microsoft Excel or another spreadsheet software (common functions, vlookups, Pivot Tables etc)
Basic experience with the Python programming language
Strong knowledge of data types (strings, integers, floating points, booleans) etc