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import datetime as datetime
datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S')
produces
AttributeError Traceback (most recent call last) in () 1 import datetime as datetime ----> 2 datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S') 3 z = minidf['Dates'] 4 z
AttributeError: 'module' object has no attribute 'strptime'
my goal is to convert a pandas dataframe column whose format is still a data object
import datetime as datetime
#datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S')
z = minidf['Dates']
0 2015-05-13 23:53:00
1 2015-05-13 23:53:00
2 2015-05-13 23:33:00
3 2015-05-13 23:30:00
4 2015-05-13 23:30:00
5 2015-05-13 23:30:00
6 2015-05-13 23:30:00
7 2015-05-13 23:30:00
8 2015-05-13 23:00:00
9 2015-05-13 23:00:00
10 2015-05-13 22:58:00
Name: Dates, dtype: object
the bonus question is, i got this column using pd.read_csv function from a larger file with more columns. Is it possible to pass parameters such that pd.read_csv directly converts this to dtype: datetime64[ns] format
678
Function usedstrftime() can change the date format in python.
The strptime() function in Python is used to format and return a string representation of date and time. It takes in the date, time, or both as an input, and parses it according to the directives given to it. It raises ValueError if the string cannot be formatted according to the provided directives.
The strptime() function converts the character string pointed to by buf to values which are stored in the tm structure pointed to by tm, using the format specified by format. The format is composed of zero or more directives.
The strftime() method returns a string representing date and time using date, time or datetime object.
I think you can use for converting to_datetime:
print pd.to_datetime('2013-01-01 09:10:12', format='%Y-%m-%d %H:%M:%S')
2013-01-01 09:10:12
print pd.to_datetime('2013-01-01 09:10:12')
2013-01-01 09:10:12
If you need convert in function read_csv, add parameter parse_dates:
df = pd.read_csv('filename', parse_dates=['Dates'])
Sample:
import pandas as pd
import io
temp=u"""Dates
2015-05-13 23:53:00
2015-05-13 23:53:00
2015-05-13 23:33:00
2015-05-13 23:30:00
2015-05-13 23:30:00
2015-05-13 23:30:00
2015-05-13 23:30:00
2015-05-13 23:30:00
2015-05-13 23:00:00
2015-05-13 23:00:00
2015-05-13 22:58:00
"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), parse_dates=['Dates'])
print df
Dates
0 2015-05-13 23:53:00
1 2015-05-13 23:53:00
2 2015-05-13 23:33:00
3 2015-05-13 23:30:00
4 2015-05-13 23:30:00
5 2015-05-13 23:30:00
6 2015-05-13 23:30:00
7 2015-05-13 23:30:00
8 2015-05-13 23:00:00
9 2015-05-13 23:00:00
10 2015-05-13 22:58:00
print df.dtypes
Dates datetime64[ns]
dtype: object
Another solution with to_datetime:
print pd.to_datetime(df['Dates'])
Sample:
print df
Dates
0 2015-05-13 23:53:00
1 2015-05-13 23:53:00
2 2015-05-13 23:33:00
3 2015-05-13 23:30:00
4 2015-05-13 23:30:00
5 2015-05-13 23:30:00
6 2015-05-13 23:30:00
7 2015-05-13 23:30:00
8 2015-05-13 23:00:00
9 2015-05-13 23:00:00
10 2015-05-13 22:58:00
print df.dtypes
Dates object
df['Dates'] = pd.to_datetime(df['Dates'])
print df
Dates
0 2015-05-13 23:53:00
1 2015-05-13 23:53:00
2 2015-05-13 23:33:00
3 2015-05-13 23:30:00
4 2015-05-13 23:30:00
5 2015-05-13 23:30:00
6 2015-05-13 23:30:00
7 2015-05-13 23:30:00
8 2015-05-13 23:00:00
9 2015-05-13 23:00:00
10 2015-05-13 22:58:00
print df.dtypes
Dates datetime64[ns]
dtype: object
AttributeError: 'module' object has no attribute 'strptime'
strptime is not available on datetime but on datetime.datetime
>>> from datetime import datetime
>>> datetime.strptime('2013-01-01 09:10:12', '%Y-%m-%d %H:%M:%S')
datetime.datetime(2013, 1, 1, 9, 10, 12)
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