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| import matplotlib.pyplot as plt | |
| from statistics import mean | |
| def chunks(l, n=2): | |
| """Yield successive n-sized chunks from l.""" | |
| for i in range(0, len(l), n): | |
| yield l[i:i + n] | |
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| ttctcatgtttgacagcttatcatcgataagctttaatgcggtagtttatcacagttaaattgctaacgcagtcaggcac | |
| cgtgtatgaaatctaacaatgcgctcatcgtcatcctcggcaccgtcaccctggatgctgtaggcataggcttggttatg | |
| ccggtactgccgggcctcttgcgggatatcgtccattccgacagcatcgccagtcactatggcgtgctgctagcgctata | |
| tgcgttgatgcaatttctatgcgcacccgttctcggagcactgtccgaccgctttggccgccgcccagtcctgctcgctt | |
| cgctacttggagccactatcgactacgcgatcatggcgaccacacccgtcctgtggatcctctacgccggacgcatcgtg | |
| gccggcatcaccggcgccacaggtgcggttgctggcgcctatatcgccgacatcaccgatggggaagatcgggctcgcca | |
| cttcgggctcatgagcgcttgtttcggcgtgggtatggtggcaggccccgtggccgggggactgttgggcgccatctcct | |
| tgcatgcaccattccttgcggcggcggtgctcaacggcctcaacctactactgggctgcttcctaatgcaggagtcgcat | |
| aagggagagcgtcgaccgatgcccttgagagccttcaacccagtcagctccttccggtgggcgcggggcatgactatcgt | |
| cgccgcacttatgactgtcttctttatcatgcaactcgtaggacaggtgccggcagcgctctgggtcattttcggcgagg |
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| import numpy as np | |
| from itertools import chain | |
| from statistics import mean | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| import statsmodels.formula.api as sfa | |
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| import numpy as np | |
| def horizontal_index(n, offset=0): | |
| """Create horizontal index with vertically aligned numbers""" | |
| index = [' ' * offset for _ in range(len(str(n)))] | |
| for number in map(str, range(n)): | |
| for idx, n in enumerate(number): | |
| index[idx] += n + '|' | |
| pad = max(map(len, index)) | |
| return '\n'.join(i.rjust(pad, ' ') for i in reversed(index)) |
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| import asyncio | |
| from time import time | |
| from async_v20 import OandaClient | |
| class Time(object): | |
| def __enter__(self): | |
| self.start = time() | |
| return self |