如何解析不同的字符串日期格式? [英] How to parse different string date formats?
问题描述
使用混合了不同字符串的表进行工作,从而可以得出日期.
Working on a table with a mix of different strings where it's possible to derive a date.
period
0 Q2 '20 Base
1 Q3 '20 Base
2 Q1 '21 Base
3 February '20 Base
4 March '20 Peak
5 Summer 22 Base
6 Winter 20 Peak
7 Summer 21 Base
8 Year 2021
9 October '21 Peak
我希望能够将其解析为时间戳,以便在python中进行分析.首先,理想情况下,我想解析为4个新列:1)天2)月3)季度4)年.然后使用这些列创建日期时间(DD-MM-YYYY).
I'd like to be able to parse this into a timestamp for analysis in python. First, ideally I want to parse into 4 new columns 1) day 2) month 3) quarter 4) year. Then use these columns to make a datetime (DD-MM-YYYY).
period day month quarter year
0 Q2 '20 Base 01 04 1 2020
1 Q3 '20 Peak 01 07 3 2020
2 Q1 '21 Base 01 01 1 2021
3 February '20 Base 01 02 1 2020
4 March '20 Peak 01 03 1 2020
5 Summer 22 Base 01 04 2 2022
6 Winter 20 Peak 01 10 4 2020
7 Summer 21 Base 01 04 2 2021
8 Year 2021 01 01 1 2021
9 October '21 Base 01 10 4 2021
如何将其解析为4个新列?
How can I parse this into the 4 new columns?
推荐答案
我的想法是为您的标识符设置字典数据结构,如下所示:
My idea is to set up a dictionary data structure for your identifiers like this:
datemap = { 'January' : {'day' : 1, 'month' : 1, 'quarter' : 1},
'February' : {'day' : 1, 'month' : 2, 'quarter' : 1},
'March' : {'day' : 1, 'month' : 3, 'quarter' : 1},
# and so on ...
'Spring' : {'day' : 1, 'month' : 1, 'quarter' : 1},
'Summer' : {'day' : 1, 'month' : 4, 'quarter' : 2},
'Fall' : {'day' : 1, 'month' : 7, 'quarter' : 3},
'Winter' : {'day' : 1, 'month' : 10, 'quarter' : 4},
'Q1' : {'day' : 1, 'month' : 1, 'quarter' : 1},
'Q2' : {'day' : 1, 'month' : 4, 'quarter' : 2},
'Q3' : {'day' : 1, 'month' : 7, 'quarter' : 3},
'Q4' : {'day' : 1, 'month' : 10, 'quarter' : 4},
'Year' : {'day' : 1, 'month' : 1, 'quarter' : 1} }
然后,您可以通过查看第一个单词r['period'].split()[0]
(或年份的第二个单词)来转换给定值r['period']
,如下所示:
Then you can transform a given value r['period']
by looking at the first word r['period'].split()[0]
(or second word for the year) like this:
df['day'] = df.apply (lambda r: datemap[r['period'].split()[0]]['day'], axis=1)
df['month'] = df.apply (lambda r: datemap[r['period'].split()[0]]['month'], axis=1)
df['quarter'] = df.apply (lambda r: datemap[r['period'].split()[0]]['quarter'], axis=1)
df['year'] = df.apply (lambda r: "20" + r['period'].split()[1][-2:], axis=1)
这篇关于如何解析不同的字符串日期格式?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!