Below is the first row of my csv DateTime column:
Mon Nov 02 20:37:10 GMT+00:00 2015
The DateTime column is currently an object and I want to convert it to datetime format so that I can get the date to appear as 2015-11-02 and I will create a separate column for the time.
The code I am using to convert the column to date time format is:
for item, frame in df['DateTime'].iteritems():
datetime.datetime.strptime(df['DateTime'], "%a-%b-%d-%H-%M-%S-%Z-%Y")
I am getting this error:
> TypeError: must be str, not Series
Any help would be greatly appreciated!
The date column is indeed a string, which—remember—is denoted as an object type in Python. You can convert it to the datetime type with the . to_datetime() method in pandas .
We can use time() function alongwith strptime() function to convert string to time object.
Timedelta('1 days 2 hours') do to DatetimeIndex object d, defined below? d = pd.
Use pd.to_datetime()
:
df['DateTime'] = pd.to_datetime(df['DateTime'])
For example,
pd.to_datetime('Mon Nov 02 20:37:10 GMT+00:00 2015')
produces Timestamp('2015-11-02 20:37:10')
.
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