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
- 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