Fancy indexing
Fancy indexing is selecting multiple array elements or positions with a collection of integer, Boolean, or label-based selectors.
Pandas Workout: 200 exercises to make you a stronger data analyst
Fancy indexing selects multiple positions or labels by supplying an index collection rather than a single index.
- How it is used
- Selects multiple Series positions or DataFrame rows and columns, then supports targeted retrieval and assignment.
- How deep it goes
- Explains list-based and boolean selection through loc syntax, returned shapes, mask distinctions, and multi-value assignment.
- Examples
- Uses labeled Series values, a five-by-five DataFrame, conditional selectors, and missing product sales filled by indexed assignment.
- What you can do after
- Apply it via pandas loc to retrieve or update selected positions, rows, columns, and conditionally matched cells.
Read how Pandas Workout: 200 exercises to make you a stronger data analyst explains fancy indexing →
Fast Python: High performance techniques for large datasets
- How it is used
- Selects multiple NumPy array positions using index collections for each dimension.
- How deep it goes
- Explains paired indexing and copy semantics, contrasting them with stride-based views without developing broader view mechanics.
- Examples
- Uses a 2 × 5 matrix, paired row and column lists, selected values, and np.shares_memory.
- What you can do after
- Apply it to select paired positions and verify whether the result shares storage with the source array.
Read how Fast Python: High performance techniques for large datasets explains fancy indexing →
Related concepts
- copyproduces · Copying is the creation of a separate representation of an existing value, object, or data, preserving some or all of its contents or state.
- maskcontrasts with · Masking is the selective representation, concealment, inclusion, exclusion, or restriction of parts of data or a system according to specified criteria.
- Seriesused by · A Series is pandas’ one-dimensional labeled data structure that associates values with an index.
- data frameuses · A data frame is a two-dimensional tabular data structure with labeled rows and columns that can contain values of different types.
- loc accessoruses · The loc accessor is a pandas indexing interface for selecting rows and columns by labels, label-based slices, or Boolean conditions.
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