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Introduction

A Statistical Data Testing Toolkit
▶️ Try Pandera

User Guide

DataFrame Schemas
Schema Models
Series Schemas
Checks
Hypothesis Testing
Pandera Data Types
Decorators for Pipeline Integration
Schema Inference
Lazy Validation
Data Synthesis Strategies
Extensions
Data Format Conversion
Supported DataFrame Libraries
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- GeoPandas
- Dask
- Fugue
- Koalas
- Pyspark ⭐️ (New)
- Modin
Integrations
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- FastAPI
- Frictionless
- Hypothesis
- Mypy
- Pydantic

Reference

API
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- Core
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- Data Types
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  - pandera.dtypes.DataType
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  - pandera.dtypes.Bool
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  - pandera.dtypes.Timestamp
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  - pandera.dtypes.DateTime
  - pandera.dtypes.Timedelta
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  - pandera.dtypes.Category
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  - pandera.dtypes.Float
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  - pandera.dtypes.Float16
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  - pandera.dtypes.Float32
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  - pandera.dtypes.Float64
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  - pandera.dtypes.Float128
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  - pandera.dtypes.Int
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  - pandera.dtypes.Int8
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  - pandera.dtypes.Int16
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  - pandera.dtypes.Int32
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  - pandera.dtypes.Int64
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  - pandera.dtypes.UInt
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  - pandera.dtypes.UInt8
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  - pandera.dtypes.UInt16
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  - pandera.dtypes.UInt32
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  - pandera.dtypes.UInt64
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  - pandera.dtypes.Complex
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  - pandera.dtypes.Complex64
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  - pandera.dtypes.Complex128
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  - pandera.dtypes.Complex256
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  - pandera.dtypes.Decimal
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  - pandera.dtypes.String
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  - pandera.engines.pandas_engine.BOOL
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  - pandera.engines.pandas_engine.INT8
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  - pandera.engines.pandas_engine.INT16
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  - pandera.engines.pandas_engine.INT32
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  - pandera.engines.pandas_engine.INT64
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  - pandera.engines.pandas_engine.UINT8
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  - pandera.engines.pandas_engine.UINT16
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  - pandera.engines.pandas_engine.UINT32
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  - pandera.engines.pandas_engine.UINT64
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  - pandera.engines.pandas_engine.STRING
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  - pandera.engines.numpy_engine.Object
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  - pandera.engines.pandas_engine.DateTime
  - pandera.engines.pandas_engine.Date
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  - pandera.engines.pandas_engine.Decimal
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  - pandera.engines.pandas_engine.Category
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  - pandera.engines.pandas_engine.Geometry
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  - pandera.engines.pandas_engine.PydanticModel
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  - pandera.dtypes.is_subdtype
  - pandera.dtypes.is_float
  - pandera.dtypes.is_int
  - pandera.dtypes.is_uint
  - pandera.dtypes.is_complex
  - pandera.dtypes.is_numeric
  - pandera.dtypes.is_bool
  - pandera.dtypes.is_string
  - pandera.dtypes.is_datetime
  - pandera.dtypes.is_timedelta
  - pandera.dtypes.immutable
  - pandera.engines.engine.Engine
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  - pandera.engines.numpy_engine.Engine
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    - pandera.engines.numpy_engine.Engine.dtype
  - pandera.engines.pandas_engine.Engine
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    - pandera.engines.pandas_engine.Engine.dtype
    - pandera.engines.pandas_engine.Engine.numpy_dtype
- Schema Models
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  - pandera.model.SchemaModel
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  - pandera.model_components.Field
  - pandera.model_components.check
  - pandera.model_components.dataframe_check
  - pandera.typing
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    - pandera.typing.fastapi.UploadFile
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      - pandera.typing.fastapi.UploadFile.__init__
      - pandera.typing.fastapi.UploadFile.pydantic_validate
    - pandera.typing.formats.Formats
  - pandera.model.BaseConfig
- Decorators
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- Schema Inference
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  - pandera.schema_inference.infer_schema
- IO Utilities
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- Data Synthesis Strategies
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  - pandera.strategies
- Extensions
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  - pandera.extensions
- Errors
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Community

Contributing

v: v0.13.4

Versions: latest; stable; v0.13.4; v0.13.3; v0.13.2; v0.13.1; v0.13.0; v0.12.0; v0.11.0; v0.10.1; v0.10.0; v0.9.0; v0.8.1; v0.8.0; v0.7.2; v0.7.1; v0.7.0; v0.6.5; v0.6.4; v0.6.3

Downloads

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pandera.dtypes.Category.coerce#

Category.coerce(data_container)[source]#: Coerce data container to the data type.

pandera.dtypes.Category.coerce_value

pandera.dtypes.Category.check

Copyright © 2019, Niels Bantilan, Nigel Markey, Jean-Francois Zinque

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