Introduction to pandas Series: From Understanding to Practical Operations, Even Beginners Can Grasp It

A Series in pandas is a labeled one-dimensional array containing data and indices, serving as a fundamental data processing structure. It can be created in various ways: from a list (with default 0, 1... indices), a dictionary (with keys as indices), a scalar value with a specified length (resulting in repeated values), or with a custom index (e.g., dates, strings). Key attributes include values (the data array), index (the labels), name (the Series name), and shape (the dimensions). Indexing operations support label-based access (loc) and positional access (iloc). Notably, label-based slicing includes the end label, while positional slicing does not. Data operations include statistical methods like sum and mean, as well as filtering via boolean conditions. In practical applications, Series are used for time series or labeled data (e.g., passenger flow analysis), enabling quick positioning, statistics, and filtering through index manipulation. Mastering index operations is crucial for effective data processing.