test(clean): add tests for clean_lat_long

dataprep/tests/clean/__init__.py

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+"""
+dataprep.clean tests
+"""

dataprep/tests/clean/test_clean_lat_long.py

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+"""
+module for testing the functions clean_lat_long() and validate_lat_long()
+"""
+import logging
+
+import numpy as np
+import pandas as pd
+import pytest
+
+from ...clean import clean_lat_long, validate_lat_long
+
+LOGGER = logging.getLogger(__name__)
+
+
+@pytest.fixture(scope="module")  # type: ignore
+def df_lat_long_column() -> pd.DataFrame:
+    df = pd.DataFrame(
+        {
+            "messy_lat_long": [
+                (41.5, -81.0),
+                "41.5;-81.0",
+                "41.5,-81.0",
+                "41.5 -81.0",
+                "41.5° N, 81.0° W",
+                "41.5 S;81.0 E",
+                "-41.5 S;81.0 E",
+                "23 26m 22s N 23 27m 30s E",
+                "23 26' 22\" N 23 27' 30\" E",
+                "UT: N 39°20' 0'' / W 74°35' 0''",
+                "hello",
+                np.nan,
+                "NULL",
+            ]
+        }
+    )
+    return df
+
+
+@pytest.fixture(scope="module")  # type: ignore
+def df_separate_lat_long_columns() -> pd.DataFrame:
+    df = pd.DataFrame(
+        {
+            "messy_lat": ["30° E", "41° 30′ N", "41 S", "80", "hello", "NA"],
+            "messy_long": ["30° E", "41° 30′ N", "41 W", "80", "hello", "NA"],
+        }
+    )
+    return df
+
+
+def test_clean_default(df_lat_long_column: pd.DataFrame) -> None:
+    df_clean = clean_lat_long(df_lat_long_column, "messy_lat_long")
+    df_check = df_lat_long_column.copy()
+    df_check["messy_lat_long_clean"] = [
+        (41.5, -81.0),
+        (41.5, -81.0),
+        (41.5, -81.0),
+        (41.5, -81.0),
+        (41.5, -81.0),
+        (-41.5, 81.0),
+        np.nan,
+        (23.4394, 23.4583),
+        (23.4394, 23.4583),
+        (39.3333, -74.5833),
+        np.nan,
+        np.nan,
+        np.nan,
+    ]
+    assert df_check.equals(df_clean)
+
+
+def test_clean_output_format(df_lat_long_column: pd.DataFrame) -> None:
+    df_clean_ddh = clean_lat_long(df_lat_long_column, "messy_lat_long", output_format="ddh")
+    df_clean_dms = clean_lat_long(df_lat_long_column, "messy_lat_long", output_format="dms")
+    df_check_ddh = df_lat_long_column.copy()
+    df_check_ddh["messy_lat_long_clean"] = [
+        "41.5° N, 81.0° W",
+        "41.5° N, 81.0° W",
+        "41.5° N, 81.0° W",
+        "41.5° N, 81.0° W",
+        "41.5° N, 81.0° W",
+        "41.5° S, 81.0° E",
+        np.nan,
+        "23.4394° N, 23.4583° E",
+        "23.4394° N, 23.4583° E",
+        "39.3333° N, 74.5833° W",
+        np.nan,
+        np.nan,
+        np.nan,
+    ]
+    df_check_dms = df_lat_long_column.copy()
+    df_check_dms["messy_lat_long_clean"] = [
+        "41° 30′ 0″ N, 81° 0′ 0″ W",
+        "41° 30′ 0″ N, 81° 0′ 0″ W",
+        "41° 30′ 0″ N, 81° 0′ 0″ W",
+        "41° 30′ 0″ N, 81° 0′ 0″ W",
+        "41° 30′ 0″ N, 81° 0′ 0″ W",
+        "41° 30′ 0″ S, 81° 0′ 0″ E",
+        np.nan,
+        "23° 26′ 22″ N, 23° 27′ 30″ E",
+        "23° 26′ 22″ N, 23° 27′ 30″ E",
+        "39° 20′ 0″ N, 74° 34′ 60″ W",
+        np.nan,
+        np.nan,
+        np.nan,
+    ]
+    assert df_check_ddh.equals(df_clean_ddh)
+    assert df_check_dms.equals(df_clean_dms)
+
+
+def test_clean_split(df_lat_long_column: pd.DataFrame) -> None:
+    df_clean = clean_lat_long(df_lat_long_column, "messy_lat_long", split=True)
+    df_check = df_lat_long_column.copy()
+    df_check["latitude"] = [
+        41.5,
+        41.5,
+        41.5,
+        41.5,
+        41.5,
+        -41.5,
+        np.nan,
+        23.4394,
+        23.4394,
+        39.3333,
+        np.nan,
+        np.nan,
+        np.nan,
+    ]
+    df_check["longitude"] = [
+        -81.0,
+        -81.0,
+        -81.0,
+        -81.0,
+        -81.0,
+        81.0,
+        np.nan,
+        23.4583,
+        23.4583,
+        -74.5833,
+        np.nan,
+        np.nan,
+        np.nan,
+    ]
+    assert df_check.equals(df_clean)
+
+
+def test_clean_output_format_split(df_lat_long_column: pd.DataFrame) -> None:
+    df_clean = clean_lat_long(df_lat_long_column, "messy_lat_long", output_format="dm", split=True)
+    df_check = df_lat_long_column.copy()
+    df_check["latitude"] = [
+        "41° 30′ N",
+        "41° 30′ N",
+        "41° 30′ N",
+        "41° 30′ N",
+        "41° 30′ N",
+        "41° 30′ S",
+        np.nan,
+        "23° 26.3667′ N",
+        "23° 26.3667′ N",
+        "39° 20′ N",
+        np.nan,
+        np.nan,
+        np.nan,
+    ]
+    df_check["longitude"] = [
+        "81° 0′ W",
+        "81° 0′ W",
+        "81° 0′ W",
+        "81° 0′ W",
+        "81° 0′ W",
+        "81° 0′ E",
+        np.nan,
+        "23° 27.5′ E",
+        "23° 27.5′ E",
+        "74° 35′ W",
+        np.nan,
+        np.nan,
+        np.nan,
+    ]
+    assert df_check.equals(df_clean)
+
+
+def test_clean_inplace(df_lat_long_column: pd.DataFrame) -> None:
+    df_clean = clean_lat_long(df_lat_long_column, "messy_lat_long", inplace=True)
+    df_check = pd.DataFrame(
+        {
+            "messy_lat_long_clean": [
+                (41.5, -81.0),
+                (41.5, -81.0),
+                (41.5, -81.0),
+                (41.5, -81.0),
+                (41.5, -81.0),
+                (-41.5, 81.0),
+                np.nan,
+                (23.4394, 23.4583),
+                (23.4394, 23.4583),
+                (39.3333, -74.5833),
+                np.nan,
+                np.nan,
+                np.nan,
+            ]
+        }
+    )
+    assert df_check.equals(df_clean)
+
+
+def test_clean_split_inplace(df_lat_long_column: pd.DataFrame) -> None:
+    df_clean = clean_lat_long(df_lat_long_column, "messy_lat_long", split=True, inplace=True)
+    df_check = pd.DataFrame(
+        {
+            "latitude": [
+                41.5,
+                41.5,
+                41.5,
+                41.5,
+                41.5,
+                -41.5,
+                np.nan,
+                23.4394,
+                23.4394,
+                39.3333,
+                np.nan,
+                np.nan,
+                np.nan,
+            ],
+            "longitude": [
+                -81.0,
+                -81.0,
+                -81.0,
+                -81.0,
+                -81.0,
+                81.0,
+                np.nan,
+                23.4583,
+                23.4583,
+                -74.5833,
+                np.nan,
+                np.nan,
+                np.nan,
+            ],
+        }
+    )
+    assert df_check.equals(df_clean)
+
+
+def test_clean_lat_long_separate_columns_split(df_separate_lat_long_columns: pd.DataFrame) -> None:
+    df_clean = clean_lat_long(
+        df_separate_lat_long_columns, lat_col="messy_lat", long_col="messy_long", split=True
+    )
+    df_check = df_separate_lat_long_columns.copy()
+    df_check["messy_lat_clean"] = [np.nan, 41.5, -41.0, 80.0, np.nan, np.nan]
+    df_check["messy_long_clean"] = [30.0, np.nan, -41.0, 80.0, np.nan, np.nan]
+    assert df_check.equals(df_clean)
+
+
+def test_validate_value() -> None:
+    assert validate_lat_long("41° 30′ 0″ N") == False
+    assert validate_lat_long("41.5 S;81.0 E") == True
+    assert validate_lat_long("-41.5 S;81.0 E") == False
+    assert validate_lat_long((41.5, 81)) == True
+    assert validate_lat_long(41.5, lat_long=False, lat=True) == True
+
+
+def test_validate_series_lat_long(df_lat_long_column: pd.DataFrame) -> None:
+    srs_valid = validate_lat_long(df_lat_long_column["messy_lat_long"])
+    srs_check = pd.Series(
+        [
+            True,
+            True,
+            True,
+            True,
+            True,
+            True,
+            False,
+            True,
+            True,
+            True,
+            False,
+            False,
+            False,
+        ],
+        name="messy_lat_long",
+    )
+    assert srs_check.equals(srs_valid)
+
+
+def test_validate_series_lat(df_separate_lat_long_columns: pd.DataFrame) -> None:
+    srs_valid = validate_lat_long(
+        df_separate_lat_long_columns["messy_lat"], lat_long=False, lat=True
+    )
+    srs_check = pd.Series(
+        [
+            False,
+            True,
+            True,
+            True,
+            False,
+            False,
+        ],
+        name="messy_lat_clean",
+    )
+    assert srs_check.equals(srs_valid)