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6kyuRainfall.py
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6kyuRainfall.py
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import re
def mean(town, strng):
for row in strng.split('\n'):
d = row.split(':')
if d[0] == town:
nums = [float(i) for i in re.findall(r'\d+\.\d+', d[1])]
return sum(nums) / len(nums)
return -1
def variance(town, strng):
for row in strng.split('\n'):
d = row.split(':')
if d[0] == town:
nums = [float(i) for i in re.findall(r'\d+\.\d+', d[1])]
avg = sum(nums) / len(nums)
variance = sum([(i - avg) ** 2 for i in nums]) / len(nums)
return variance
return -1
data = """Rome:Jan 81.2,Feb 63.2,Mar 70.3,Apr 55.7,May 53.0,Jun 36.4,Jul 17.5,Aug 27.5,Sep 60.9,Oct 117.7,Nov 111.0,Dec 97.9
London:Jan 48.0,Feb 38.9,Mar 39.9,Apr 42.2,May 47.3,Jun 52.1,Jul 59.5,Aug 57.2,Sep 55.4,Oct 62.0,Nov 59.0,Dec 52.9
Paris:Jan 182.3,Feb 120.6,Mar 158.1,Apr 204.9,May 323.1,Jun 300.5,Jul 236.8,Aug 192.9,Sep 66.3,Oct 63.3,Nov 83.2,Dec 154.7
NY:Jan 108.7,Feb 101.8,Mar 131.9,Apr 93.5,May 98.8,Jun 93.6,Jul 102.2,Aug 131.8,Sep 92.0,Oct 82.3,Nov 107.8,Dec 94.2
Vancouver:Jan 145.7,Feb 121.4,Mar 102.3,Apr 69.2,May 55.8,Jun 47.1,Jul 31.3,Aug 37.0,Sep 59.6,Oct 116.3,Nov 154.6,Dec 171.5
Sydney:Jan 103.4,Feb 111.0,Mar 131.3,Apr 129.7,May 123.0,Jun 129.2,Jul 102.8,Aug 80.3,Sep 69.3,Oct 82.6,Nov 81.4,Dec 78.2
Bangkok:Jan 10.6,Feb 28.2,Mar 30.7,Apr 71.8,May 189.4,Jun 151.7,Jul 158.2,Aug 187.0,Sep 319.9,Oct 230.8,Nov 57.3,Dec 9.4
Tokyo:Jan 49.9,Feb 71.5,Mar 106.4,Apr 129.2,May 144.0,Jun 176.0,Jul 135.6,Aug 148.5,Sep 216.4,Oct 194.1,Nov 95.6,Dec 54.4
Beijing:Jan 3.9,Feb 4.7,Mar 8.2,Apr 18.4,May 33.0,Jun 78.1,Jul 224.3,Aug 170.0,Sep 58.4,Oct 18.0,Nov 9.3,Dec 2.7
Lima:Jan 1.2,Feb 0.9,Mar 0.7,Apr 0.4,May 0.6,Jun 1.8,Jul 4.4,Aug 3.1,Sep 3.3,Oct 1.7,Nov 0.5,Dec 0.7"""
print(mean("London", data))
print(variance('London', data))