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| import numpy as np
|
| import pandas as pd
| from pandas import (
| Categorical,
| DataFrame,
| Index,
| Series,
| Timestamp,
| )
| import pandas._testing as tm
| from pandas.core.arrays import IntervalArray
|
|
| class TestGetNumericData:
| def test_get_numeric_data_preserve_dtype(self):
| # get the numeric data
| obj = DataFrame({"A": [1, "2", 3.0]})
| result = obj._get_numeric_data()
| expected = DataFrame(dtype=object, index=pd.RangeIndex(3), columns=[])
| tm.assert_frame_equal(result, expected)
|
| def test_get_numeric_data(self):
| datetime64name = np.dtype("M8[ns]").name
| objectname = np.dtype(np.object_).name
|
| df = DataFrame(
| {"a": 1.0, "b": 2, "c": "foo", "f": Timestamp("20010102")},
| index=np.arange(10),
| )
| result = df.dtypes
| expected = Series(
| [
| np.dtype("float64"),
| np.dtype("int64"),
| np.dtype(objectname),
| np.dtype(datetime64name),
| ],
| index=["a", "b", "c", "f"],
| )
| tm.assert_series_equal(result, expected)
|
| df = DataFrame(
| {
| "a": 1.0,
| "b": 2,
| "c": "foo",
| "d": np.array([1.0] * 10, dtype="float32"),
| "e": np.array([1] * 10, dtype="int32"),
| "f": np.array([1] * 10, dtype="int16"),
| "g": Timestamp("20010102"),
| },
| index=np.arange(10),
| )
|
| result = df._get_numeric_data()
| expected = df.loc[:, ["a", "b", "d", "e", "f"]]
| tm.assert_frame_equal(result, expected)
|
| only_obj = df.loc[:, ["c", "g"]]
| result = only_obj._get_numeric_data()
| expected = df.loc[:, []]
| tm.assert_frame_equal(result, expected)
|
| df = DataFrame.from_dict({"a": [1, 2], "b": ["foo", "bar"], "c": [np.pi, np.e]})
| result = df._get_numeric_data()
| expected = DataFrame.from_dict({"a": [1, 2], "c": [np.pi, np.e]})
| tm.assert_frame_equal(result, expected)
|
| df = result.copy()
| result = df._get_numeric_data()
| expected = df
| tm.assert_frame_equal(result, expected)
|
| def test_get_numeric_data_mixed_dtype(self):
| # numeric and object columns
|
| df = DataFrame(
| {
| "a": [1, 2, 3],
| "b": [True, False, True],
| "c": ["foo", "bar", "baz"],
| "d": [None, None, None],
| "e": [3.14, 0.577, 2.773],
| }
| )
| result = df._get_numeric_data()
| tm.assert_index_equal(result.columns, Index(["a", "b", "e"]))
|
| def test_get_numeric_data_extension_dtype(self):
| # GH#22290
| df = DataFrame(
| {
| "A": pd.array([-10, np.nan, 0, 10, 20, 30], dtype="Int64"),
| "B": Categorical(list("abcabc")),
| "C": pd.array([0, 1, 2, 3, np.nan, 5], dtype="UInt8"),
| "D": IntervalArray.from_breaks(range(7)),
| }
| )
| result = df._get_numeric_data()
| expected = df.loc[:, ["A", "C"]]
| tm.assert_frame_equal(result, expected)
|
|
