User Guide¶
The User Guide covers all of pandas by topic area. Each of the subsections introduces a topic (such as “working with missing data”), and discusses how pandas approaches the problem, with many examples throughout.
Users brand-new to pandas should start with 10 Minutes to pandas.
Further information on any specific method can be obtained in the API Reference.
- IO Tools (Text, CSV, HDF5, …)
- Indexing and Selecting Data
- Different Choices for Indexing
- Basics
- Attribute Access
- Slicing ranges
- Selection By Label
- Selection By Position
- Selection By Callable
- IX Indexer is Deprecated
- Indexing with list with missing labels is Deprecated
- Selecting Random Samples
- Setting With Enlargement
- Fast scalar value getting and setting
- Boolean indexing
- Indexing with isin
- The
where()Method and Masking - The
query()Method - Duplicate Data
- Dictionary-like
get()method - The
lookup()Method - Index objects
- Set / Reset Index
- Returning a view versus a copy
- MultiIndex / Advanced Indexing
- Merge, join, and concatenate
- Reshaping and Pivot Tables
- Working with Text Data
- Working with missing data
- Categorical Data
- Nullable Integer Data Type
- Visualization
- Computational tools
- Group By: split-apply-combine
- Time Series / Date functionality
- Overview
- Timestamps vs. Time Spans
- Converting to Timestamps
- Generating Ranges of Timestamps
- Timestamp Limitations
- Indexing
- Iterating through groups
- Time/Date Components
- DateOffset Objects
- Time Series-Related Instance Methods
- Resampling
- Time Span Representation
- Converting Between Representations
- Representing Out-of-Bounds Spans
- Time Zone Handling
- Time Deltas
- Styling
- Options and Settings
- Enhancing Performance
- Sparse data structures
- Frequently Asked Questions (FAQ)
- Cookbook