Change column from Pandas date object to python datetime
type(data_raw['pandas_date']) will always return pandas.core.series.Series, because the object data_raw['pandas_date'] is of type pandas.core.series.Series. What you want is to get the dtype, so you could just do data_raw['pandas_date'].dtype.

data_raw['pandas_date'] = pd.to_datetime(data_raw['pandas_date'])

This is correct, and if you do data_raw['pandas_date'].dtype again afterwards, you will see that it is datetime[64].
I have a dataset with the first column as date in the format: 2011-01-01 and type(data_raw['pandas_date']) gives me pandas.core.series.Series
I want to convert the whole column into date time object so I can extract and process year/month/day from each row as required.
I used pd.to_datetime(data_raw['pandas_date']) and it printed output with dtype: datetime64[ns] in the last line of the output. I assume that values were converted to datetime.
but when I run type(data_raw['pandas_date']) again, it still says pandas.core.series.Series and anytime I try to run .dt function on it, it gives me an error saying this is not a datetime object.
So, my question is - it looks like to_datetime function changed my data into datetime object, but how to I apply/save it to the pandas_date column? I tried 
data_raw['pandas_date'] = pd.to_datetime(data_raw['pandas_date'])
but this doesn't work either, I get the same result when I check the type. Sorry if this is too basic.