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pandera documentation

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pandera documentation

Introduction

Welcome to Pandera
▶️ Try Pandera
Official Website

User Guide

DataFrame Schemas
DataFrame Models
Series Schemas
Data Type Validation
Validating with Checks
Hypothesis Testing
Preprocessing with Parsers
Pandera Data Types
Decorators for Pipeline Integration
Dropping Invalid Rows
Schema Inference and Persistence
Lazy Validation
Error Reports
Data Synthesis Strategies
Extensions
Data Format Conversion
Supported DataFrame Libraries
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- Polars
- Pyspark SQL
- Dask
- Modin
- Pyspark Pandas
- GeoPandas
- Fugue
Integrations
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- FastAPI
- Frictionless
- Hypothesis
- Mypy
- Pydantic
Configuration

Reference

API
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- Core
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  - pandera.api.pandas.container.DataFrameSchema
    Toggle navigation of pandera.api.pandas.container.DataFrameSchema
    - pandera.api.pandas.container.DataFrameSchema.validate
    - pandera.api.pandas.container.DataFrameSchema.__call__
  - pandera.api.pandas.array.SeriesSchema
    Toggle navigation of pandera.api.pandas.array.SeriesSchema
  - pandera.api.polars.container.DataFrameSchema
    Toggle navigation of pandera.api.polars.container.DataFrameSchema
  - pandera.api.pyspark.container.DataFrameSchema
    Toggle navigation of pandera.api.pyspark.container.DataFrameSchema
  - pandera.api.pandas.components.Column
    Toggle navigation of pandera.api.pandas.components.Column
  - pandera.api.pandas.components.Index
    Toggle navigation of pandera.api.pandas.components.Index
  - pandera.api.pandas.components.MultiIndex
    Toggle navigation of pandera.api.pandas.components.MultiIndex
  - pandera.api.polars.components.Column
    Toggle navigation of pandera.api.polars.components.Column
  - pandera.api.pyspark.components.Column
    Toggle navigation of pandera.api.pyspark.components.Column
  - pandera.api.checks.Check
    Toggle navigation of pandera.api.checks.Check
  - pandera.api.hypotheses.Hypothesis
    Toggle navigation of pandera.api.hypotheses.Hypothesis
  - pandera.api.polars.types.PolarsData
  - pandera.api.pyspark.types.PysparkDataframeColumnObject
  - pandera.config.PanderaConfig
  - pandera.config.ValidationDepth
  - pandera.config.ValidationScope
  - pandera.config.config_context
  - pandera.config.get_config_context
- Data Types
  Toggle navigation of Data Types
  - pandera.dtypes.DataType
    Toggle navigation of pandera.dtypes.DataType
  - 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.engines.polars_engine.Int8
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  - pandera.engines.polars_engine.Int16
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  - pandera.engines.polars_engine.Int32
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  - pandera.engines.polars_engine.Int64
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  - pandera.engines.polars_engine.UInt8
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  - pandera.engines.polars_engine.UInt16
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  - pandera.engines.polars_engine.UInt32
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  - pandera.engines.polars_engine.UInt64
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  - pandera.engines.polars_engine.Float32
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  - pandera.engines.polars_engine.Float64
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  - pandera.engines.polars_engine.Decimal
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  - pandera.engines.polars_engine.Date
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  - pandera.engines.polars_engine.DateTime
  - pandera.engines.polars_engine.Time
    Toggle navigation of pandera.engines.polars_engine.Time
  - pandera.engines.polars_engine.Timedelta
    Toggle navigation of pandera.engines.polars_engine.Timedelta
  - pandera.engines.polars_engine.Array
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  - pandera.engines.polars_engine.List
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  - pandera.engines.polars_engine.Struct
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  - pandera.engines.polars_engine.Bool
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  - pandera.engines.polars_engine.String
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  - pandera.engines.polars_engine.Categorical
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  - pandera.engines.polars_engine.Category
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  - pandera.engines.polars_engine.Null
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  - pandera.engines.polars_engine.Object
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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
    Toggle navigation of pandera.engines.numpy_engine.Engine
    - pandera.engines.numpy_engine.Engine.dtype
  - pandera.engines.pandas_engine.Engine
    Toggle navigation of pandera.engines.pandas_engine.Engine
    - pandera.engines.pandas_engine.Engine.dtype
    - pandera.engines.pandas_engine.Engine.numpy_dtype
- DataFrame Models
  Toggle navigation of DataFrame Models
  - pandera.api.pandas.model.DataFrameModel
    Toggle navigation of pandera.api.pandas.model.DataFrameModel
    - pandera.api.pandas.model.DataFrameModel.build_schema_
    - pandera.api.pandas.model.DataFrameModel.to_json_schema
  - pandera.api.polars.model.DataFrameModel
    Toggle navigation of pandera.api.polars.model.DataFrameModel
    - pandera.api.polars.model.DataFrameModel.build_schema_
    - pandera.api.polars.model.DataFrameModel.to_json_schema
  - pandera.api.pyspark.model.DataFrameModel
    Toggle navigation of pandera.api.pyspark.model.DataFrameModel
  - pandera.api.dataframe.model_components.Field
  - pandera.api.dataframe.model_components.check
  - pandera.api.dataframe.model_components.dataframe_check
  - pandera.api.dataframe.model_components.parser
  - pandera.api.dataframe.model_components.dataframe_parser
  - 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_v2
    - pandera.typing.formats.Formats
  - pandera.api.pandas.model_config.BaseConfig
  - pandera.api.polars.model_config.BaseConfig
  - pandera.api.pyspark.model_config.BaseConfig
- Decorators
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- Schema Inference
  Toggle navigation of Schema Inference
  - pandera.schema_inference.pandas.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: stable

Versions: latest; stable; 0.19.0; v0.18.3; v0.18.2; v0.18.1; v0.18.0; v0.17.2; v0.17.1; v0.17.0; v0.16.1; v0.16.0; v0.15.2; v0.14.5; v0.13.4

Downloads

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pandera.dtypes.Float.coerce_value¶

Float.coerce_value(value)[source]¶: Coerce an value to a particular type.

pandera.dtypes.Float.try_coerce

pandera.dtypes.Float.coerce

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pandera.dtypes.Float.coerce_value
- Float.coerce_value()