0

my data

data= [{"content": "11", "title": "刘德华", "info": "2020-01-13", "time": 1578877014},
                  {"content": "22", "title": "刘德", "info": "2020-01-24", "time": 1579877014},
                  {"content": "33", "title": "apple", "info": "2020-02-28", "time": 1582877014},
                  {"content": "55", "title": "app", "info": "2020-02-17", "time": 1581877014},
                  {"content": "66", "title": "appstore", "info": "2019-06-30", "time": 1561877014},
                  {"content": "44", "title": "banana", "info": "2020-02-28", "time": 1582876014},
                  {"content": "aa", "title": "banana", "info": "2020-03-12 eee", "time": 1584000882},
                  {"content": "bb", "title": "Thursday data", "info": "2018-03-12 vvvv", "time": 1520842482},
                  {"content": "cc", "title": "banana", "info": "2020-03-14 xxx", "time": 1584154305},
                  {"content": "cc", "title": "banana", "info": "2019-03-14 aa", "time": 1552531905},
                  {"content": "cc", "title": "Thursday data", "info": "2020-03-19 data", "time": 1584586305},
                  {"content": "cc", "title": "Thursday data", "info": "2019-11-07 aaa", "time": 1573095105},

                  ]

i want to get all Thursday data,not only contain this year i hope data is 

                  {"content": "bb", "title": "Thursday data", "info": "2018-03-12 bbb", "time": 1520842482},
                  {"content": "cc", "title": "Thursday data", "info": "2020-03-19 aaa ", "time": 1584586305},
                  {"content": "cc", "title": "Thursday data", "info": "2019-11-07 
 aaa", "time": 1573095105},

Trouble providing ideas, thank you

xin.chen
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    https://stackoverflow.com/questions/17071871/how-to-select-rows-from-a-dataframe-based-on-column-values – ab123 Mar 19 '20 at 08:53
  • This [blog](https://cmdlinetips.com/2018/02/how-to-subset-pandas-dataframe-based-on-values-of-a-column/) provides a comprehensive introduction to Pandas filtering and selecting subsets based on column value. Have a look. – nishant Mar 19 '20 at 08:59
  • Do you need working with `Series` ? Or should be Dataframe? – jezrael Mar 19 '20 at 09:03
  • @ jezrael use series – xin.chen Mar 19 '20 at 09:07

1 Answers1

1

Use Series.str.get with compare by Series.eq with datetimes and Series.dt.day_name:

s = pd.Series(L)

s1 = s[pd.to_datetime(s.str.get('time'), unit='s').dt.day_name() == 'Thursday']
print (s1)
6     {'content': 'aa', 'title': 'banana', 'info': '...
9     {'content': 'cc', 'title': 'banana', 'info': '...
10    {'content': 'cc', 'title': 'Thursday data', 'i...
11    {'content': 'cc', 'title': 'Thursday data', 'i...
dtype: object

Details:

print (s.str.get('time'))
0     1578877014
1     1579877014
2     1582877014
3     1581877014
4     1561877014
5     1582876014
6     1584000882
7     1520842482
8     1584154305
9     1552531905
10    1584586305
11    1573095105
dtype: int64

print (pd.to_datetime(s.str.get('time'), unit='s'))
0    2020-01-13 00:56:54
1    2020-01-24 14:43:34
2    2020-02-28 08:03:34
3    2020-02-16 18:16:54
4    2019-06-30 06:43:34
5    2020-02-28 07:46:54
6    2020-03-12 08:14:42
7    2018-03-12 08:14:42
8    2020-03-14 02:51:45
9    2019-03-14 02:51:45
10   2020-03-19 02:51:45
11   2019-11-07 02:51:45
dtype: datetime64[ns]

print (pd.to_datetime(s.str.get('time'), unit='s').dt.day_name())
0       Monday
1       Friday
2       Friday
3       Sunday
4       Sunday
5       Friday
6     Thursday
7       Monday
8     Saturday
9     Thursday
10    Thursday
11    Thursday
dtype: object
jezrael
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