Python statistics 模块，median_grouped() 实例源码

def MEDIAN_GROUPED(df, n, price='Close', interval=1):
    """
    Median, or 50th percentile, of grouped data
    """
    median_grouped_list = []
    i = 0
    while i < len(df[price]):
        if i + 1 < n:
            median_grouped = float('NaN')
        else:
            start = i + 1 - n
            end = i + 1
            median_grouped = statistics.median_grouped(df[price][start:end], interval)
        median_grouped_list.append(median_grouped)
        i += 1
    return median_grouped_list

def main():
    print(stats.mean(range(6)))
    print(stats.median(range(6)))
    print(stats.median_low(range(6)))
    print(stats.median_high(range(6)))
    print(stats.median_grouped(range(6)))
    try:
        print(stats.mode(range(6)))
    except Exception as e:
        print(e)
    print(stats.mode(list(range(6)) + [3]))
    print(stats.pstdev(list(range(6)) + [3]))
    print(stats.stdev(list(range(6)) + [3]))
    print(stats.pvariance(list(range(6)) + [3]))
    print(stats.variance(list(range(6)) + [3]))

def test_repeated_single_value(self):
        # Override method from AverageMixin.
        # Yet again, failure of median_grouped to conserve the data type
        # causes me headaches :-(
        for x in (5.3, 68, 4.3e17, Fraction(29, 101), Decimal('32.9714')):
            for count in (2, 5, 10, 20):
                data = [x]*count
                self.assertEqual(self.func(data), float(x))

def test_odd_fractions(self):
        # Test median_grouped works with an odd number of Fractions.
        F = Fraction
        data = [F(5, 4), F(9, 4), F(13, 4), F(13, 4), F(17, 4)]
        assert len(data)%2 == 1
        random.shuffle(data)
        self.assertEqual(self.func(data), 3.0)

def test_even_fractions(self):
        # Test median_grouped works with an even number of Fractions.
        F = Fraction
        data = [F(5, 4), F(9, 4), F(13, 4), F(13, 4), F(17, 4), F(17, 4)]
        assert len(data)%2 == 0
        random.shuffle(data)
        self.assertEqual(self.func(data), 3.25)

def test_odd_decimals(self):
        # Test median_grouped works with an odd number of Decimals.
        D = Decimal
        data = [D('5.5'), D('6.5'), D('6.5'), D('7.5'), D('8.5')]
        assert len(data)%2 == 1
        random.shuffle(data)
        self.assertEqual(self.func(data), 6.75)

def test_even_decimals(self):
        # Test median_grouped works with an even number of Decimals.
        D = Decimal
        data = [D('5.5'), D('5.5'), D('6.5'), D('6.5'), D('7.5'), D('8.5')]
        assert len(data)%2 == 0
        random.shuffle(data)
        self.assertEqual(self.func(data), 6.5)
        #---
        data = [D('5.5'), D('5.5'), D('6.5'), D('7.5'), D('7.5'), D('8.5')]
        assert len(data)%2 == 0
        random.shuffle(data)
        self.assertEqual(self.func(data), 7.0)

def test_repeated_single_value(self):
        # Override method from AverageMixin.
        # Yet again, failure of median_grouped to conserve the data type
        # causes me headaches :-(
        for x in (5.3, 68, 4.3e17, Fraction(29, 101), Decimal('32.9714')):
            for count in (2, 5, 10, 20):
                data = [x]*count
                self.assertEqual(self.func(data), float(x))

def test_odd_fractions(self):
        # Test median_grouped works with an odd number of Fractions.
        F = Fraction
        data = [F(5, 4), F(9, 4), F(13, 4), F(13, 4), F(17, 4)]
        assert len(data)%2 == 1
        random.shuffle(data)
        self.assertEqual(self.func(data), 3.0)

def test_even_fractions(self):
        # Test median_grouped works with an even number of Fractions.
        F = Fraction
        data = [F(5, 4), F(9, 4), F(13, 4), F(13, 4), F(17, 4), F(17, 4)]
        assert len(data)%2 == 0
        random.shuffle(data)
        self.assertEqual(self.func(data), 3.25)

def test_odd_decimals(self):
        # Test median_grouped works with an odd number of Decimals.
        D = Decimal
        data = [D('5.5'), D('6.5'), D('6.5'), D('7.5'), D('8.5')]
        assert len(data)%2 == 1
        random.shuffle(data)
        self.assertEqual(self.func(data), 6.75)

def test_even_decimals(self):
        # Test median_grouped works with an even number of Decimals.
        D = Decimal
        data = [D('5.5'), D('5.5'), D('6.5'), D('6.5'), D('7.5'), D('8.5')]
        assert len(data)%2 == 0
        random.shuffle(data)
        self.assertEqual(self.func(data), 6.5)
        #---
        data = [D('5.5'), D('5.5'), D('6.5'), D('7.5'), D('7.5'), D('8.5')]
        assert len(data)%2 == 0
        random.shuffle(data)
        self.assertEqual(self.func(data), 7.0)

def median_grouped(text):
    """
    Finds the grouped median of a space-separated list of numbers.

    Calculates the median of grouped continuous data, calculated as the 50th percentile, using interpolation.

    Example::

        /median grouped 33 54 43 65 43 62
    """
    return format_output(statistics.median_grouped(parse_numeric_list(text)))

def setup():
    commands.add(mean)
    commands.add(median)
    commands.add(median_low)
    commands.add(median_high)
    commands.add(median_grouped)
    commands.add(mode)
    commands.add(pstdev)
    commands.add(pvariance)
    commands.add(stdev)
    commands.add(variance)