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184 lines
4.5 KiB
Python
184 lines
4.5 KiB
Python
from datetime import datetime
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import numpy as np
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import pytest
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from pandas import (
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DataFrame,
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Series,
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bdate_range,
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notna,
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)
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@pytest.fixture
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def series():
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"""Make mocked series as fixture."""
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arr = np.random.randn(100)
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locs = np.arange(20, 40)
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arr[locs] = np.NaN
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series = Series(arr, index=bdate_range(datetime(2009, 1, 1), periods=100))
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return series
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@pytest.fixture
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def frame():
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"""Make mocked frame as fixture."""
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return DataFrame(
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np.random.randn(100, 10),
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index=bdate_range(datetime(2009, 1, 1), periods=100),
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columns=np.arange(10),
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)
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# create the data only once as we are not setting it
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def _create_consistency_data():
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def create_series():
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return [
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Series(dtype=object),
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Series([np.nan]),
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Series([np.nan, np.nan]),
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Series([3.0]),
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Series([np.nan, 3.0]),
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Series([3.0, np.nan]),
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Series([1.0, 3.0]),
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Series([2.0, 2.0]),
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Series([3.0, 1.0]),
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Series(
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[5.0, 5.0, 5.0, 5.0, np.nan, np.nan, np.nan, 5.0, 5.0, np.nan, np.nan]
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),
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Series(
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[
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np.nan,
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5.0,
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5.0,
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5.0,
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np.nan,
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np.nan,
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np.nan,
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5.0,
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5.0,
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np.nan,
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np.nan,
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]
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),
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Series(
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[
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np.nan,
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np.nan,
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5.0,
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5.0,
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np.nan,
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np.nan,
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np.nan,
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5.0,
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5.0,
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np.nan,
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np.nan,
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]
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),
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Series(
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[
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np.nan,
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3.0,
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np.nan,
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3.0,
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4.0,
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5.0,
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6.0,
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np.nan,
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np.nan,
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7.0,
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12.0,
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13.0,
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14.0,
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15.0,
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]
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),
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Series(
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[
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np.nan,
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5.0,
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np.nan,
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2.0,
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4.0,
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0.0,
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9.0,
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np.nan,
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np.nan,
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3.0,
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12.0,
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13.0,
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14.0,
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15.0,
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]
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),
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Series(
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[
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2.0,
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3.0,
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np.nan,
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3.0,
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4.0,
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5.0,
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6.0,
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np.nan,
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np.nan,
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7.0,
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12.0,
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13.0,
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14.0,
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15.0,
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]
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),
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Series(
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[
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2.0,
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5.0,
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np.nan,
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2.0,
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4.0,
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0.0,
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9.0,
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np.nan,
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np.nan,
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3.0,
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12.0,
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13.0,
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14.0,
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15.0,
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]
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),
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Series(range(10)),
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Series(range(20, 0, -2)),
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]
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def create_dataframes():
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return [
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DataFrame(),
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DataFrame(columns=["a"]),
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DataFrame(columns=["a", "a"]),
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DataFrame(columns=["a", "b"]),
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DataFrame(np.arange(10).reshape((5, 2))),
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DataFrame(np.arange(25).reshape((5, 5))),
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DataFrame(np.arange(25).reshape((5, 5)), columns=["a", "b", 99, "d", "d"]),
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] + [DataFrame(s) for s in create_series()]
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def is_constant(x):
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values = x.values.ravel("K")
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return len(set(values[notna(values)])) == 1
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def no_nans(x):
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return x.notna().all().all()
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# data is a tuple(object, is_constant, no_nans)
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data = create_series() + create_dataframes()
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return [(x, is_constant(x), no_nans(x)) for x in data]
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@pytest.fixture(params=_create_consistency_data())
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def consistency_data(request):
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"""Create consistency data"""
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return request.param
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