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remove conditional pandas
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tests/test_optional/test_figure_factory/test_validate_gantt.py

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@@ -22,7 +22,6 @@ def test_valid_list_of_dicts():
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assert all(isinstance(x, dict) for x in result)
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_valid_dataframe():
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df = pd.DataFrame(
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[
@@ -48,7 +47,6 @@ def test_valid_list_with_extra_keys():
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assert all("Resource" in row for row in result)
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_valid_dataframe_with_extra_keys():
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df = pd.DataFrame(
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[
@@ -83,7 +81,6 @@ def test_missing_required_key_in_list():
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assert result is input_data
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_missing_required_key_in_dataframe():
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df = pd.DataFrame(
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[
@@ -104,15 +101,13 @@ def test_input_is_not_list_or_dataframe():
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validate_gantt("Not a list or DataFrame")
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_dataframe_with_no_rows():
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df = pd.DataFrame(columns=["Task", "Start", "Finish"])
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result = validate_gantt(df)
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assert isinstance(result, list)
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assert result == []
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_dataframe_with_extra_rows_and_missing_keys():
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df = pd.DataFrame(
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[
@@ -131,7 +126,6 @@ def test_list_with_dict_missing_all_keys():
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assert result is input_data
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_dataframe_with_only_required_keys():
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df = pd.DataFrame(
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[
@@ -160,7 +154,6 @@ def test_large_list_of_dicts():
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assert len(result) == 1000
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_large_dataframe():
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df = pd.DataFrame(
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[
@@ -178,7 +171,6 @@ def test_large_dataframe():
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assert set(result[0].keys()) == set(df.columns)
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_large_dataframe_missing_key():
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df = pd.DataFrame(
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[
@@ -241,7 +233,6 @@ def test_determinism_multiple_calls_list():
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assert out2 is input_data
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@pytest.mark.skipif(pd is None, reason="pandas is not available")
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def test_dataframe_column_order_and_index():
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df = pd.DataFrame(
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[

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