Python 3.x 熊猫系列获得所有周一数据？

我的数据

我想得到所有周四的数据，而不仅仅是今年的数据 我希望数据是正确的

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},

                  ]

提供想法有困难，谢谢您使用compare by datetimes和：

详细信息：

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

---

---

本文全面介绍了如何根据列值筛选和选择子集。看看。您是否需要使用

系列

？还是应该是Dataframe？@jezrael use seriessorry，标题是我写的假数据，实际上不是星期四，必须根据时间字段确定是否是星期四？不在

标题中

？@xin.chen-一些问题？@xin.chen-添加日期时间，如何验证？因为有时候可能错过不同的一年。

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

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