Exemple #1
0
def test_numeric_frequencies():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["frequencies"] == [(3, 3), (2, 3), (4, 1), (1, 1)]
Exemple #2
0
def test_numeric_range():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["range"] == (test_series.max() - test_series.min())
Exemple #3
0
def test_numeric_unique_count():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["unique_count"] == 4
Exemple #4
0
def test_numeric_upperQ():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["75%"] == test_series.quantile(0.75)
Exemple #5
0
def test_numeric_middleQ():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["50%"] == test_series.quantile(0.50)
def test_numeric_mean():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["mean"] == test_series.mean()
Exemple #7
0
def test_numeric_mean():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["mean"] == test_series.mean()
def test_numeric_mode():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["mode"] == [3]
def test_numeric_mode_count():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["mode_frequency"] == 3
def test_numeric_unique_count():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["unique_count"] == 4
def test_numeric_frequencies():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["frequencies"] == [(3, 3), (2, 3), (4, 1), (1, 1)]
def test_numeric_range():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["range"] == (test_series.max() - test_series.min())
def test_numeric_middleQ():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["50%"] == test_series.quantile(0.50)
def test_numeric_upperQ():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["75%"] == test_series.quantile(0.75)
Exemple #15
0
def test_numeric_mode():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["mode"] == [3]
Exemple #16
0
def test_numeric_sd():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["std"] == test_series.std()
Exemple #17
0
def test_numeric_mode_count():
    test_series = df['col1']
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["mode_frequency"] == 3
def test_numeric_sd():
    test_series = df["col1"]
    test_analysis = analyze.numericalAnalysis(test_series)
    assert test_analysis["std"] == test_series.std()