I have the following Pandas dataframe in Python 2.7.
import pandas as pd
trial_num = [1,2,3,4,5]
sail_rem_time = ['11:33:11','16:29:05','09:37:56','21:43:31','17:42:06']
dfc = pd.DataFrame(zip(*[trial_num,sail_rem_time]),columns=['Temp_Reading','Time_of_Sail'])
print dfc
The dataframe looks like this:
Temp_Reading Time_of_Sail
1 11:33:11
2 16:29:05
3 09:37:56
4 21:43:31
5 17:42:06
This dataframe comes from a *.csv file. I use Pandas to read in the *.csv file as a Pandas dataframe. When I use print dfc.dtypes
, it shows me that the column Time_of_Sail
has a datatype object
. I would like to convert this column to datetime
datatype BUT I only want the time part - I don't want the year, month, date.
I can try this:
dfc['Time_of_Sail'] = pd.to_datetime(dfc['Time_of_Sail'])
dfc['Time_of_Sail'] = [time.time() for time in dfc['Time_of_Sail']]
but the problem is that the when I run print dfc.dtypes
it still shows that the column Time_of_Sail
is object
.
Is there a way to convert this column into a datetime format that only has the time?
Additional Information:
To create the above dataframe and output, this also works:
import pandas as pd
trial_num = [1,2,3,4,5]
sail_rem_time = ['11:33:11','16:29:05','09:37:56','21:43:31','17:42:06']
data = [
[trial_num[0],sail_rem_time[0]],
[trial_num[1],sail_rem_time[1]],[trial_num[2],sail_rem_time[2]],
[trial_num[3],sail_rem_time[3]]
]
dfc = pd.DataFrame(data,columns=['Temp_Reading','Time_of_Sail'])
dfc['Time_of_Sail'] = pd.to_datetime(dfc['Time_of_Sail'])
dfc['Time_of_Sail'] = [time.time() for time in dfc['Time_of_Sail']]
print dfc
print dfc.dtypes
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