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How to use infer_series_statistics method in pandera

Best Python code snippet using pandera_python

test_schema_statistics.py

Source:test_schema_statistics.py

...202    ],203)204def test_infer_series_schema_statistics(series, expectation) -> None:205    """Test series statistics are correctly inferred."""206    statistics = schema_statistics.infer_series_statistics(series)207    _test_statistics(statistics, expectation)208@pytest.mark.parametrize(209    "null_index, series, expectation",210    [211        *[212            [213                0,214                pd.Series([1, 2, 3], dtype=str(data_type)),215                {216                    # introducing nans to integer arrays upcasts to float217                    "dtype": DEFAULT_FLOAT,218                    "nullable": True,219                    "checks": {220                        "greater_than_or_equal_to": 2,221                        "less_than_or_equal_to": 3,222                    },223                    "name": None,224                },225            ]226            for data_type in INTEGER_TYPES227        ],228        [229            # introducing nans to bool arrays upcasts to float except230            # for pandas >= 1.3.0231            0,232            pd.Series([True, False, True, False]),233            {234                "dtype": (235                    pandas_engine.Engine.dtype(pa.Object)236                    if pa.PANDAS_1_3_0_PLUS237                    else DEFAULT_FLOAT238                ),239                "nullable": True,240                "checks": (241                    None242                    if pa.PANDAS_1_3_0_PLUS243                    else {244                        "greater_than_or_equal_to": 0,245                        "less_than_or_equal_to": 1,246                    }247                ),248                "name": None,249            },250        ],251        [252            0,253            pd.Series(["a", "b", "c", "a"], dtype="category"),254            {255                "dtype": pandas_engine.Engine.dtype(pa.Category),256                "nullable": True,257                "checks": {"isin": ["a", "b", "c"]},258                "name": None,259            },260        ],261        [262            0,263            pd.Series(["a", "b", "c", "a"], name="str_series"),264            {265                "dtype": pandas_engine.Engine.dtype(str),266                "nullable": True,267                "checks": None,268                "name": "str_series",269            },270        ],271        [272            2,273            pd.Series(pd.to_datetime(["20180101", "20180102", "20180103"])),274            {275                "dtype": pandas_engine.Engine.dtype(pa.DateTime),276                "nullable": True,277                "checks": {278                    "greater_than_or_equal_to": pd.Timestamp("20180101"),279                    "less_than_or_equal_to": pd.Timestamp("20180102"),280                },281                "name": None,282            },283        ],284    ],285)286def test_infer_nullable_series_schema_statistics(287    null_index, series, expectation288):289    """Test nullable series statistics are correctly inferred."""290    series.iloc[null_index] = None291    statistics = schema_statistics.infer_series_statistics(series)292    _test_statistics(statistics, expectation)293@pytest.mark.parametrize(294    "null_values, dtype",295    (296        ([pd.NaT, pd.NaT], pandas_engine.Engine.dtype(pa.DateTime)),297        ([np.nan, np.nan], DEFAULT_FLOAT),298        ([None, None], pandas_engine.Engine.dtype(pa.Object)),299        # Mixed 'null' types300        ([pd.NaT, np.nan], pandas_engine.Engine.dtype(pa.DateTime)),301        ([None, pd.NaT], pandas_engine.Engine.dtype(pa.DateTime)),302        ([None, np.nan], DEFAULT_FLOAT),303    ),304)305def test_empty_series_schema_statistics(null_values, dtype):306    """Test 'empty' series statistics are correctly inferred."""307    series = pd.Series(null_values)308    statistics = schema_statistics.infer_series_statistics(series)309    expectation = {310        "dtype": dtype,311        "nullable": True,312        "checks": None,313        "name": None,314    }315    _test_statistics(statistics, expectation)316@pytest.mark.parametrize(317    "index, expectation",318    [319        [320            pd.RangeIndex(20),321            [322                {...

schema_inference.py

Source:schema_inference.py

...64    """Infer a SeriesSchema from a pandas DataFrame.65    :param series: Series object to infer.66    :returns: SeriesSchema67    """68    series_statistics = infer_series_statistics(series)69    schema = SeriesSchema(70        dtype=series_statistics["dtype"],71        checks=parse_check_statistics(series_statistics["checks"]),72        nullable=series_statistics["nullable"],73        name=series_statistics["name"],74        coerce=True,75    )76    schema._is_inferred = True...

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