Python statistics.median_grouped() Examples
The following are 22
code examples of statistics.median_grouped().
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Example #1
| Source File: test_statistics.py From Project-New-Reign---Nemesis-Main with GNU General Public License v3.0 | 5 votes |
|
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))
Example #2
| Source File: test_statistics.py From android_universal with MIT License | 5 votes |
|
def test_data_type_error(self):
# Test median_grouped with str, bytes data types for data and interval
data = ["", "", ""]
self.assertRaises(TypeError, self.func, data)
#---
data = [b"", b"", b""]
self.assertRaises(TypeError, self.func, data)
#---
data = [1, 2, 3]
interval = ""
self.assertRaises(TypeError, self.func, data, interval)
#---
data = [1, 2, 3]
interval = b""
self.assertRaises(TypeError, self.func, data, interval)
Example #3
| Source File: test_statistics.py From android_universal with MIT License | 5 votes |
|
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)
Example #4
| Source File: test_statistics.py From android_universal with MIT License | 5 votes |
|
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)
Example #5
| Source File: test_statistics.py From android_universal with MIT License | 5 votes |
|
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)
Example #6
| Source File: test_statistics.py From android_universal with MIT License | 5 votes |
|
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)
Example #7
| Source File: test_statistics.py From android_universal with MIT License | 5 votes |
|
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))
Example #8
| Source File: test_statistics.py From Project-New-Reign---Nemesis-Main with GNU General Public License v3.0 | 5 votes |
|
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)
Example #9
| Source File: test_statistics.py From Project-New-Reign---Nemesis-Main with GNU General Public License v3.0 | 5 votes |
|
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)
Example #10
| Source File: test_statistics.py From Project-New-Reign---Nemesis-Main with GNU General Public License v3.0 | 5 votes |
|
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)
Example #11
| Source File: test_statistics.py From Project-New-Reign---Nemesis-Main with GNU General Public License v3.0 | 5 votes |
|
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)
Example #12
| Source File: test_statistics.py From Fluid-Designer with GNU General Public License v3.0 | 5 votes |
|
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))
Example #13
| Source File: statistic_functions.py From jhTAlib with GNU General Public License v3.0 | 5 votes |
|
def MEDIAN_GROUPED(df, n, price='Close', interval=1):
"""
Median, or 50th percentile, of grouped data
Returns: list of floats = jhta.MEDIAN_GROUPED(df, n, price='Close', interval=1)
"""
median_grouped_list = []
if n == len(df[price]):
start = None
for i in range(len(df[price])):
if df[price][i] != df[price][i]:
median_grouped = float('NaN')
else:
if start is None:
start = i
end = i + 1
median_grouped = statistics.median_grouped(df[price][start:end], interval)
median_grouped_list.append(median_grouped)
else:
for i in range(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)
return median_grouped_list
Example #14
| Source File: test_statistics.py From ironpython3 with Apache License 2.0 | 5 votes |
|
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)
Example #15
| Source File: test_statistics.py From ironpython3 with Apache License 2.0 | 5 votes |
|
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)
Example #16
| Source File: test_statistics.py From ironpython3 with Apache License 2.0 | 5 votes |
|
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)
Example #17
| Source File: test_statistics.py From ironpython3 with Apache License 2.0 | 5 votes |
|
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)
Example #18
| Source File: test_statistics.py From ironpython3 with Apache License 2.0 | 5 votes |
|
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))
Example #19
| Source File: test_statistics.py From Fluid-Designer with GNU General Public License v3.0 | 5 votes |
|
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)
Example #20
| Source File: test_statistics.py From Fluid-Designer with GNU General Public License v3.0 | 5 votes |
|
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)
Example #21
| Source File: test_statistics.py From Fluid-Designer with GNU General Public License v3.0 | 5 votes |
|
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)
Example #22
| Source File: test_statistics.py From Fluid-Designer with GNU General Public License v3.0 | 5 votes |
|
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)
