CODEWITHSUNDEEP
pythonpandascsvdataframedatetime
nickp
nickp

Reputation: 43

Convert CSV values to datetime and create function from that in python

I have tried searching other posts on here, but can't seem to solve this problem. I have a CSV file in which Year, Crash_Month, Crash_Day and Crash_Time are all seperate columns in the CSV 'data_dict'. I am trying to solve the below question. How would I go about this? I have tried to use a data frame, and pandas convert to datetime, but I'm not sure if this is the right approach. Many thanks

Here's the data frame I'm trying to assign datetime to

    year  month  day       time
0   2000      1    1   4:30:59 
1   2000      1    1   0:07:35 
2   2000      1    1   4:51:37 
3   2000      1    1   4:27:56 
4   2000      1    1   2:16:31 
5   2000      1    1   0:37:21 
6   2000      1    1   0:52:57 
7   2000      1    1   3:35:14 
8   2000      1    1   2:41:58 
9   2000      1    1   3:43:02 
10  2000      1    1   3:49:19 
11  2000      1    1   3:03:55 
12  2000      1    1   4:46:01 
13  2000      1    1   1:07:24 
14  2000      1    1   8:29:04 
15  2000      1    1   6:35:21 
16  2000      1    1   6:06:25 
17  2000      1    1   7:10:13 
18  2000      1    1   10:57:24 
19  2000      1    1   7:54:38

So far, I have coded this.

import pandas as pd

df = pd.DataFrame({'year': (data_dict['Year']),
                   'month': (data_dict['Crash_Month']),
                   'day': (data_dict['Crash_Day']),
                   'time': (data_dict['Crash_Time'])})

date=pd.to_datetime(df[["year", "month", "day", "time"]],format='%YYYY%mm%dd, %HH%MM%SS')
print(date)

day_of_week = {0 : 'Monday',
              1: 'Tuesday',
              2: 'Wednesday',
              3: 'Thursday',
              4: 'Friday',
              5: 'Saturday',
              6: 'Sunday'}

month_season= {1: 'Summer',
              2: 'Summer',
              3: 'Autumn',
              4: 'Autumn',
              5: 'Autumn',
              6: 'Winter',
              7: 'Winter',
              8: 'Winter',
              9: 'Spring',
              10: 'Spring',
              11: 'Spring',
              12: 'Summer'}

Upvotes: 0

Views: 178

Answers (1)

Umar.H
Umar.H

Reputation: 23099

We can use str.zfill and string concenation with pd.to_datetime to build up your datetime.

df2['date'] = pd.to_datetime(df2['year'].astype(str) 
               + df2['month'].astype(str).str.zfill(2)
               + df2['day'].astype(str).str.zfill(2)
               + ' '
               + df2['time'].astype(str),format='%Y%m%d %H:%M:%S'
              )

    year  month  day       time                date
0   2000      1    1   4:30:59  2000-01-01 04:30:59
1   2000      1    1   0:07:35  2000-01-01 00:07:35
2   2000      1    1   4:51:37  2000-01-01 04:51:37
3   2000      1    1   4:27:56  2000-01-01 04:27:56
4   2000      1    1   2:16:31  2000-01-01 02:16:31
5   2000      1    1   0:37:21  2000-01-01 00:37:21
6   2000      1    1   0:52:57  2000-01-01 00:52:57
7   2000      1    1   3:35:14  2000-01-01 03:35:14
8   2000      1    1   2:41:58  2000-01-01 02:41:58
9   2000      1    1   3:43:02  2000-01-01 03:43:02
10  2000      1    1   3:49:19  2000-01-01 03:49:19
11  2000      1    1   3:03:55  2000-01-01 03:03:55
12  2000      1    1   4:46:01  2000-01-01 04:46:01
13  2000      1    1   1:07:24  2000-01-01 01:07:24
14  2000      1    1   8:29:04  2000-01-01 08:29:04
15  2000      1    1   6:35:21  2000-01-01 06:35:21
16  2000      1    1   6:06:25  2000-01-01 06:06:25
17  2000      1    1   7:10:13  2000-01-01 07:10:13
18  2000      1    1  10:57:24  2000-01-01 10:57:24
19  2000      1    1   7:54:38  2000-01-01 07:54:38

Upvotes: 1

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