Following our exploration of NumPy, this article introduces Pandas (Part 1): Introduction to Series and DataFrames. Pandas is a fast, powerful, flexible, and easy-to-use open-source data analysis and manipulation tool, built on top of the Python programming language.
Following our Introduction to Series and DataFrames, this article explores Pandas (Part 2): Reading and writing data (CSV, Excel). A common task in data science is to read data from various file formats and to write data out to files.
Following our lesson on Reading and writing data, this article explores Pandas (Part 3): Data selection and indexing. Selecting and filtering data is one of the most common tasks in data analysis.
Following our lesson on Data selection and indexing, this article explores Pandas (Part 4): Data cleaning and preparation. Real-world data is often messy. Data cleaning is a crucial step in any data analysis workflow.