本文介绍了python大 pandas 提取独特的日期从时间序列的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个包含很多日内数据的DataFrame,DataFrame有几天的数据,日期不连续。 2012-10-08 07:12:22 0.0 0 0 2315.6 0 0.0 0
2012-10-08 09:14:00 2306.4 20 326586240 2306.4 472 2306.8 4
2012-10-08 09:15:00 2306.8 34 249805440 2306.8 361 2308.0 26
2012-10-08 09:15:01 2308.0 1 53309040 2307.4 77 2308.6 9
2012-10-08 09:15:01.500000 2308.2 1 124630140 2307.0 180 2308.4 1
2012-10-08 09:15:02 2307.0 5 85846260 2308.2 124 2308.0 9
2012-10-08 09:15:02.500000 2307.0 3 128073540 2307.0 185 2307.6 11
......
2012-10-10 07:19:30 0.0 0 0 2276.6 0 0.0 0
2012-10-10 09:14:00 2283.2 80 98634240 2283.2 144 2283.4 1
2012-10-10 09:15:00 2285.2 18 126814260 2285.2 185 2285.6 3
2012-10-10 09 :15:01 2285.8 6 98719560 2286.8 144 2287.0 25
2012-10-10 09:15:01.500000 2287.0 36 1447 59420 2288.8 211 2289.0 4
2012-10-10 09:15:02 2287.4 6 109829280 2287.4 160 2288.6 5
......
如何从上述DataFrame中提取datetime格式的唯一日期?要结果像 [2012-10-08,2012-10-10]
解决方案
如果您有系列
,请执行以下操作:
[116]:df [Date]
输出[116]:
0 2012-10-08 07:12:22
1 2012-10-08 09:14:00
2 2012-10-08 09:15:00
3 2012-10-08 09:15:01
4 2012-10-08 09:15:01.500000
5 2012 -10-08 09:15:02
6 2012-10-08 09:15:02.500000
7 2012-10-10 07:19:30
8 2012-10-10 09 :14:00
9 2012-10-10 09:15:00
10 2012-10-10 09:15:01
11 2012-10-10 09:15:01.500000
12 2012-10-10 09:15:02
名称:日期
每个对象是一个 Timestamp
:
在[117]中:df [Date] [0]
Out [117]:< Timestamp:2012-10-08 07:12:22>
只能通过调用 .date()$获取日期c $ c>:
在[118]中:df [Date] [0] .date()
Out [118]:datetime.date(2012,10,8)
code> .unique()方法。所以你可以使用 map
和 lambda
:
在[126]中:df [Date]。map(lambda t:t.date())。unique()
Out [126]:array([2012- 10-08,2012-10-10],dtype = object)
或使用 Timestamp.date
方法:
在[127]中:df [Date] .map(pd.Timestamp.date).unique()
Out [127]:array([2012-10-08,2012-10-10],dtype = object)
I have a DataFrame which contains a lot of intraday data, the DataFrame has several days of data, dates are not continuous.
2012-10-08 07:12:22 0.0 0 0 2315.6 0 0.0 0
2012-10-08 09:14:00 2306.4 20 326586240 2306.4 472 2306.8 4
2012-10-08 09:15:00 2306.8 34 249805440 2306.8 361 2308.0 26
2012-10-08 09:15:01 2308.0 1 53309040 2307.4 77 2308.6 9
2012-10-08 09:15:01.500000 2308.2 1 124630140 2307.0 180 2308.4 1
2012-10-08 09:15:02 2307.0 5 85846260 2308.2 124 2308.0 9
2012-10-08 09:15:02.500000 2307.0 3 128073540 2307.0 185 2307.6 11
......
2012-10-10 07:19:30 0.0 0 0 2276.6 0 0.0 0
2012-10-10 09:14:00 2283.2 80 98634240 2283.2 144 2283.4 1
2012-10-10 09:15:00 2285.2 18 126814260 2285.2 185 2285.6 3
2012-10-10 09:15:01 2285.8 6 98719560 2286.8 144 2287.0 25
2012-10-10 09:15:01.500000 2287.0 36 144759420 2288.8 211 2289.0 4
2012-10-10 09:15:02 2287.4 6 109829280 2287.4 160 2288.6 5
......
How can I extract the unique date in the datetime format from the above DataFrame? To have result like [2012-10-08, 2012-10-10]
解决方案
If you have a Series
like:
In [116]: df["Date"]
Out[116]:
0 2012-10-08 07:12:22
1 2012-10-08 09:14:00
2 2012-10-08 09:15:00
3 2012-10-08 09:15:01
4 2012-10-08 09:15:01.500000
5 2012-10-08 09:15:02
6 2012-10-08 09:15:02.500000
7 2012-10-10 07:19:30
8 2012-10-10 09:14:00
9 2012-10-10 09:15:00
10 2012-10-10 09:15:01
11 2012-10-10 09:15:01.500000
12 2012-10-10 09:15:02
Name: Date
where each object is a Timestamp
:
In [117]: df["Date"][0]
Out[117]: <Timestamp: 2012-10-08 07:12:22>
you can get only the date by calling .date()
:
In [118]: df["Date"][0].date()
Out[118]: datetime.date(2012, 10, 8)
and Series have a .unique()
method. So you can use map
and a lambda
:
In [126]: df["Date"].map(lambda t: t.date()).unique()
Out[126]: array([2012-10-08, 2012-10-10], dtype=object)
or use the Timestamp.date
method:
In [127]: df["Date"].map(pd.Timestamp.date).unique()
Out[127]: array([2012-10-08, 2012-10-10], dtype=object)
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