-
Notifications
You must be signed in to change notification settings - Fork 0
/
import-error.json
22 lines (22 loc) · 1.31 KB
/
import-error.json
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
[
"\nmean = reduce(lambda x, y: x + y, arr1) / len(arr1)",
"\nmean = np.sum(arr1) / np.size(arr1)",
"\ntotal = reduce(lambda x, y: x + y, arr1)\nmean = total / len(arr1)",
"\nmean = reduce(lambda a, b: a + b, arr1) / len(arr1)",
"\nmean = np.divide(np.sum(arr1), np.size(arr1))",
"\nmean = reduce(lambda a, b: a + b, arr1) / float(len(arr1))",
"from operator import add\nmean = reduce(add, arr1) / len(arr1)",
"\nmean = gz1 = reduce(lambda x, y: x + y, arr1) / len(arr1)",
"\nmean = sum([numpy.double(i) for i in arr1]) / len(arr1)",
"\nmean = reduce(operator.add, arr1) / len(arr1)",
"from scipy import stats\nmean = stats.tmean(arr1)",
"\nmean = reduce(lambda total, value: total + value, arr1) / float(len(arr1))",
"\nmean = arr1[0]\nfor i in rangye(1, len(arr1)):\n mean += value\nmean /= len(arr1)",
"\nmean = functools.reduce(lambda a, b: a + b, arr1) / float(len(arr1))",
"\nmean = 0\nmean = reduce(lambda x, y: x + y, arr1) / len(arr1)",
"\nmean = np.average(arr1) if arr1 else np.nan",
"\nmean = np.nan\nif arr1:\n total = 0\n for num in arr1:\n total += num\n mean = total / len(arr1)",
"\nmean = np.nan\nif arr1:\n mean = reduce(lambda x, y: x + y, arr1) / len(arr1)",
"import scipy.stats\nmean = scipy.stats.tmean(arr1)",
"\narr1_np = np.array(arr1)\nmean = arr1_np.sum() / arr1_np.size"
]