Development

• Contributing to pandas
  • Where to start?
  • Bug reports and enhancement requests
  • Working with the code
  • Contributing your changes to pandas
  • Tips for a successful pull request
• Creating a development environment
  • Option 1: creating an environment without Docker
  • Option 2: creating an environment using Docker
• Contributing to the documentation
  • About the pandas documentation
  • Updating a pandas docstring
  • How to build the pandas documentation
  • Previewing changes
• Contributing to the code base
  • Code standards
  • Pre-commit
  • Optional dependencies
  • Backwards compatibility
  • Type hints
  • Testing with continuous integration
  • Test-driven development
  • Running the test suite
  • Running the performance test suite
  • Documenting your code
• pandas maintenance
  • Roles
  • Tasks
  • Issue triage
  • Closing issues
  • Reviewing pull requests
  • Backporting
  • Cleaning up old issues
  • Cleaning up old pull requests
  • Becoming a pandas maintainer
  • Merging pull requests
  • Benchmark machine
  • Release process
• Internals
  • Indexing
  • Subclassing pandas data structures
• Debugging C extensions
  • Using a debugger
  • Checking memory leaks with valgrind
• Extending pandas
  • Registering custom accessors
  • Extension types
  • Subclassing pandas data structures
  • Plotting backends
• Developer
  • Storing pandas DataFrame objects in Apache Parquet format
• Policies
  • Version policy
  • Python support
• Roadmap
  • Extensibility
  • String data type
  • Consistent missing value handling
  • Apache Arrow interoperability
  • Block manager rewrite
  • Decoupling of indexing and internals
  • Numba-accelerated operations
  • Performance monitoring
  • Roadmap evolution
  • Completed items
• Contributor community
  • Community meeting
  • New contributor meeting
  • Calendar
  • GitHub issue tracker
  • The developer mailing list
  • Community slack