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# API reference

This page gives an overview of all public pandas objects, functions and methods. All classes and functions exposed in `pandas.*` namespace are public.

The following subpackages are public.

- `pandas.errors`: Custom exception and warnings classes that are raised by pandas.

- `pandas.plotting`: Plotting public API.

- `pandas.testing`: Functions that are useful for writing tests involving pandas objects.

- `pandas.api.extensions`: Functions and classes for extending pandas objects.

- `pandas.api.indexers`: Functions and classes for rolling window indexers.

- `pandas.api.interchange`: DataFrame interchange protocol.

- `pandas.api.types`: Datatype classes and functions.

- `pandas.api.typing`: Classes that may be necessary for type-hinting. These are classes that are encountered as intermediate results but should not be instantiated directly by users. These classes are not to be confused with classes from the pandas-stubs package which has classes in addition to those that occur in pandas for type-hinting.

In addition, public functions in `pandas.io`, `pandas.tseries`, `pandas.util` submodules are explicitly mentioned in the documentation. Further APIs in these modules are not guaranteed to be stable.

Warning

The `pandas.core`, `pandas.compat` top-level modules are PRIVATE. Stable functionality in such modules is not guaranteed.

- Input/output
  - Pickling
  - Flat file
  - Clipboard
  - Excel
  - JSON
  - HTML
  - XML
  - Latex
  - HDFStore: PyTables (HDF5)
  - Feather
  - Parquet
  - Iceberg
  - ORC
  - SAS
  - SPSS
  - SQL
  - STATA
- General functions
  - Data manipulations
  - Top-level missing data
  - Top-level dealing with numeric data
  - Top-level dealing with datetimelike data
  - Top-level dealing with Interval data
  - Top-level evaluation
  - Datetime formats
  - Hashing
  - Importing from other DataFrame libraries
- Series
  - Constructor
  - Attributes
  - Conversion
  - Indexing, iteration
  - Binary operator functions
  - Unary operator functions
  - Function application, GroupBy & window
  - Computations / descriptive stats
  - Reindexing / selection / label manipulation
  - Missing data handling
  - Reshaping, sorting
  - Combining / comparing / joining / merging
  - Time Series-related
  - Accessors
  - Plotting
  - Serialization / IO / conversion
- DataFrame
  - Constructor
  - Attributes and underlying data
  - Conversion
  - Indexing, iteration
  - Binary operator functions
  - Unary operator functions
  - Function application, GroupBy & window
  - Computations / descriptive stats
  - Reindexing / selection / label manipulation
  - Missing data handling
  - Reshaping, sorting, transposing
  - Combining / comparing / joining / merging
  - Time Series-related
  - Flags
  - Metadata
  - Plotting
  - Sparse accessor
  - Serialization / IO / conversion
- pandas arrays, scalars, and data types
  - Objects
  - Utilities
- Index objects
  - Index
  - Numeric Index
  - CategoricalIndex
  - IntervalIndex
  - MultiIndex
  - DatetimeIndex
  - TimedeltaIndex
  - PeriodIndex
- Date offsets
  - BaseOffset
  - DateOffset
  - BusinessDay
  - BusinessHour
  - CustomBusinessDay
  - CustomBusinessHour
  - MonthEnd
  - MonthBegin
  - BusinessMonthEnd
  - BusinessMonthBegin
  - CustomBusinessMonthEnd
  - CustomBusinessMonthBegin
  - SemiMonthEnd
  - SemiMonthBegin
  - Week
  - WeekOfMonth
  - LastWeekOfMonth
  - BQuarterEnd
  - BQuarterBegin
  - QuarterEnd
  - QuarterBegin
  - BHalfYearEnd
  - BHalfYearBegin
  - HalfYearEnd
  - HalfYearBegin
  - BYearEnd
  - BYearBegin
  - YearEnd
  - YearBegin
  - FY5253
  - FY5253Quarter
  - Easter
  - Tick
  - Day
  - Hour
  - Minute
  - Second
  - Milli
  - Micro
  - Nano
- Frequencies
  - pandas.tseries.frequencies.to_offset
- Holiday calendars
  - pandas.tseries.holiday.AbstractHolidayCalendar
  - pandas.tseries.holiday.Holiday
- Window
  - Rolling window functions
  - Weighted window functions
  - Expanding window functions
  - Exponentially-weighted window functions
  - Window indexer
- GroupBy
  - Indexing, iteration
  - Function application helper
  - Function application
  - `DataFrameGroupBy` computations / descriptive stats
  - `SeriesGroupBy` computations / descriptive stats
  - Plotting and visualization
- Resampling
  - Indexing, iteration
  - Function application
  - Upsampling
  - Computations / descriptive stats
- Style
  - Styler constructor
  - Styler properties
  - Style application
  - Builtin styles
  - Style export and import
- Plotting
  - pandas.plotting.andrews_curves
  - pandas.plotting.autocorrelation_plot
  - pandas.plotting.bootstrap_plot
  - pandas.plotting.boxplot
  - pandas.plotting.deregister_matplotlib_converters
  - pandas.plotting.lag_plot
  - pandas.plotting.parallel_coordinates
  - pandas.plotting.plot_params
  - pandas.plotting.radviz
  - pandas.plotting.register_matplotlib_converters
  - pandas.plotting.scatter_matrix
  - pandas.plotting.table
- Options and settings
  - Working with options
  - Numeric formatting
- Extensions
  - pandas.api.extensions.register_extension_dtype
  - pandas.api.extensions.register_dataframe_accessor
  - pandas.api.extensions.register_series_accessor
  - pandas.api.extensions.register_index_accessor
  - pandas.api.extensions.ExtensionDtype
  - pandas.api.extensions.ExtensionArray
  - pandas.arrays.NumpyExtensionArray
  - pandas.api.indexers.check_array_indexer
- Testing
  - Assertion functions
  - Exceptions and warnings
  - Bug report function
  - Test suite runner
- Missing values
  - pandas.NA
  - pandas.NaT
- pandas typing aliases
  - Typing aliases