github_39605284的博客

import matplotlib as mplimport numpy as npimport sklearnimport pandas as pdimport osimport sysimport timeimport tensorflow as tffrom tensorflow import kerasprint(tf.__version__)print(sys.version_info)for module in mpl, np, pd, sklearn, tf, ker

a = [(1,2), (3, 4), (5, 6)]c, d = zip(*a)print(c, d)(1, 3, 5) (2, 4, 6)

>>> import unicodedata>>> import sys>>> cmb_chrs = dict.fromkeys(c for c in range(sys.maxunicode)... if unicodedata.combining(chr(c)))...>>> b = unicodedata.normalize('NFD', a)>>> b

np.random.randint(2, size=10)array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0]) # randomnp.random.randint(1, size=10)array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])numpy.random.randint¶

不设置指定位置，按默认顺序设置指定位置字典设置参数列表索引设置参数传入对象str.format() 格式化数字>>>"{} {}".format("hello", "world") # 不设置指定位置，按默认顺序'hello world' >>> "{0} {1}".format("hello", "world") # 设置指定位置'hello world' >>> "{1} {0} {1}".format("hell.