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df['date_only'] = df['date_time_column'].dt.date
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df['date_column'] = pd.to_datetime(df['datetime_column']).dt.date
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# This is a way to convert a dataframe into time series
# A dataframe is turned into time series once we make the dataframe's index into datetime datatype
# If the "date_col" is not converted to datetime type
df.index = pd.to_datetime(df["date_col"], errors='coerce')
# If the "date_col" is already converted to datetime type
df.index = df["date_col"]
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#Converting column to datetime dtype while loading file.
#Create a date parser function
d_parser = lambda x: pd.to_datetime(x)
df = pd.read_csv(file_name.csv, parse_dates=['date_column'], date_parser=d_parser)
#If date is not in parseable format, use
pd.to_datetime.strptime(x, format)
#Eg. format for '2017-03-13 04-PM' is '%Y-%M-%D %I-%p'
#Datetime Formatting Codes - http://bit.ly/python-dt-fmt