I have a df that looks like this:
2015-01-29 08:30:00-05:00 199425 199950 199375 199825
2015-01-29 08:45:00-05:00 199825 199850 199650
This is an old question from Jan 2015. But since there is no answer yet (although lots of comments), here is an answer in Oct 2019. The original questioner probably found an answer already but just as a reference for the future.
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.to_datetime.html
https://docs.python.org/3/library/datetime.html#strftime-and-strptime-behavior
import pandas as pd
# create dataframe
df = pd.DataFrame({
'date_original': ['2015-01-29 08:30:00-05:00', '2015-01-29 08:45:00-05:00', '2015-01-29 09:00:00-05:00'],
'measurement': [199425, 199825, 199825]
})
# make sure to convert date column to datetime, not string
df['date_original'] = pd.to_datetime(df['date_original'])
print('Original dataframe:')
print(df)
print()
# remove the suffix from the date
df['date_transform'] = pd.to_datetime(df['date_original']).dt.strftime('%Y-%m-%d %H:%M:%S')
print('Transformed dataframe:')
print(df)
print()
df