from pathlib import Path
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import numpy as np
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import pytest
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import pandas as pd
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import pandas._testing as tm
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pyreadstat = pytest.importorskip("pyreadstat")
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# TODO(CoW) - detection of chained assignment in cython
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# https://github.com/pandas-dev/pandas/issues/51315
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@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
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@pytest.mark.parametrize("path_klass", [lambda p: p, Path])
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def test_spss_labelled_num(path_klass, datapath):
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# test file from the Haven project (https://haven.tidyverse.org/)
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fname = path_klass(datapath("io", "data", "spss", "labelled-num.sav"))
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df = pd.read_spss(fname, convert_categoricals=True)
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expected = pd.DataFrame({"VAR00002": "This is one"}, index=[0])
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expected["VAR00002"] = pd.Categorical(expected["VAR00002"])
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tm.assert_frame_equal(df, expected)
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df = pd.read_spss(fname, convert_categoricals=False)
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expected = pd.DataFrame({"VAR00002": 1.0}, index=[0])
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tm.assert_frame_equal(df, expected)
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@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
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def test_spss_labelled_num_na(datapath):
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# test file from the Haven project (https://haven.tidyverse.org/)
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fname = datapath("io", "data", "spss", "labelled-num-na.sav")
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df = pd.read_spss(fname, convert_categoricals=True)
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expected = pd.DataFrame({"VAR00002": ["This is one", None]})
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expected["VAR00002"] = pd.Categorical(expected["VAR00002"])
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tm.assert_frame_equal(df, expected)
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df = pd.read_spss(fname, convert_categoricals=False)
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expected = pd.DataFrame({"VAR00002": [1.0, np.nan]})
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tm.assert_frame_equal(df, expected)
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@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
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def test_spss_labelled_str(datapath):
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# test file from the Haven project (https://haven.tidyverse.org/)
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fname = datapath("io", "data", "spss", "labelled-str.sav")
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df = pd.read_spss(fname, convert_categoricals=True)
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expected = pd.DataFrame({"gender": ["Male", "Female"]})
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expected["gender"] = pd.Categorical(expected["gender"])
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tm.assert_frame_equal(df, expected)
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df = pd.read_spss(fname, convert_categoricals=False)
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expected = pd.DataFrame({"gender": ["M", "F"]})
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tm.assert_frame_equal(df, expected)
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@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
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def test_spss_umlauts(datapath):
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# test file from the Haven project (https://haven.tidyverse.org/)
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fname = datapath("io", "data", "spss", "umlauts.sav")
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df = pd.read_spss(fname, convert_categoricals=True)
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expected = pd.DataFrame(
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{"var1": ["the ä umlaut", "the ü umlaut", "the ä umlaut", "the ö umlaut"]}
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)
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expected["var1"] = pd.Categorical(expected["var1"])
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tm.assert_frame_equal(df, expected)
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df = pd.read_spss(fname, convert_categoricals=False)
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expected = pd.DataFrame({"var1": [1.0, 2.0, 1.0, 3.0]})
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tm.assert_frame_equal(df, expected)
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def test_spss_usecols(datapath):
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# usecols must be list-like
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fname = datapath("io", "data", "spss", "labelled-num.sav")
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with pytest.raises(TypeError, match="usecols must be list-like."):
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pd.read_spss(fname, usecols="VAR00002")
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def test_spss_umlauts_dtype_backend(datapath, dtype_backend):
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# test file from the Haven project (https://haven.tidyverse.org/)
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fname = datapath("io", "data", "spss", "umlauts.sav")
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df = pd.read_spss(fname, convert_categoricals=False, dtype_backend=dtype_backend)
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expected = pd.DataFrame({"var1": [1.0, 2.0, 1.0, 3.0]}, dtype="Int64")
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if dtype_backend == "pyarrow":
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pa = pytest.importorskip("pyarrow")
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from pandas.arrays import ArrowExtensionArray
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expected = pd.DataFrame(
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{
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col: ArrowExtensionArray(pa.array(expected[col], from_pandas=True))
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for col in expected.columns
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}
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)
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tm.assert_frame_equal(df, expected)
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def test_invalid_dtype_backend():
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msg = (
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"dtype_backend numpy is invalid, only 'numpy_nullable' and "
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"'pyarrow' are allowed."
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)
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with pytest.raises(ValueError, match=msg):
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pd.read_spss("test", dtype_backend="numpy")
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