python日期处理总结

对Pyton常用日期做了简单总结：

  1 # coding: utf-8
  2 
  3 # # Python的日期和时间处理 
  4 
  5 # ## datetime模块
  6 
  7 # In[2]:
  8 
  9 from datetime import datetime
 10 
 11 
 12 # In[3]:
 13 
 14 now = datetime.now()
 15 print(now)
 16 
 17 
 18 # In[4]:
 19 
 20 print('年: {}, 月: {}, 日: {}'.format(now.year, now.month, now.day))
 21 
 22 
 23 # In[5]:
 24 
 25 diff = datetime(2017, 3, 4, 17) - datetime(2017, 2, 18, 15)
 26 print(type(diff))
 27 print(diff)
 28 print('经历了{}天, {}秒。'.format(diff.days, diff.seconds))
 29 
 30 
 31 # ## 字符串和datetime转换
 32 # 
 33 
 34 # ### datetime -> str
 35 
 36 # In[6]:
 37 
 38 # str()
 39 dt_obj = datetime(2017, 3, 4)
 40 str_obj = str(dt_obj)
 41 print(type(str_obj))
 42 print(str_obj)
 43 
 44 
 45 # In[7]:
 46 
 47 # datetime.strftime()
 48 str_obj2 = dt_obj.strftime('%d-%m-%Y')
 49 print(str_obj2)
 50 
 51 
 52 # ### str -> datetime
 53 
 54 # In[ ]:
 55 
 56 # strptime
 57 dt_str = '2017-02-18'
 58 dt_obj2 = datetime.strptime(dt_str, '%Y-%m-%d')
 59 print(type(dt_obj2))
 60 print(dt_obj2)
 61 
 62 
 63 # In[ ]:
 64 
 65 # dateutil.parser.parse
 66 from dateutil.parser import parse
 67 dt_str2 = '2017/02/18'
 68 dt_obj3 = parse(dt_str2)
 69 print(type(dt_obj3))
 70 print(dt_obj3)
 71 
 72 
 73 # In[ ]:
 74 
 75 # pd.to_datetime
 76 import pandas as pd
 77 s_obj = pd.Series(['2017/02/18', '2017/02/19', '2017-02-25', '2017-02-26'], name='course_time')
 78 print(s_obj)
 79 
 80 
 81 # In[ ]:
 82 
 83 s_obj2 = pd.to_datetime(s_obj)
 84 print(s_obj2)
 85 
 86 
 87 # In[ ]:
 88 
 89 # 处理缺失值
 90 s_obj3 = pd.Series(['2017/02/18', '2017/02/19', '2017-02-25', '2017-02-26'] + [None], 
 91                    name='course_time')
 92 print(s_obj3)
 93 
 94 
 95 # In[ ]:
 96 
 97 s_obj4 = pd.to_datetime(s_obj3)
 98 print(s_obj4) # NAT-> Not a Time
 99 
100 
101 # In[ ]:

 

posted @ 2017-03-31 09:49  Meek  阅读(299)  评论(0)    收藏  举报