How to split a timestamp field into Year, Month, Day, etc with Data Refinery?

Question

I have a timestamp field with this definition:

Time interval: the beginning of the time interval expressed as the number of millisecond elapsed from the Unix Epoch on January 1st, 1970 at UTC. The end of the time interval can be obtained by adding 600000 milliseconds (10 minutes) to this value. TYPE: numeric

Is there a way in refinery to create separate columns for year, month, day, day of week, etc?

The equivalent in pandas is:

df['Datetime'] = pd.to_datetime(df['Time interval'].astype(int))

df['Year'] = df['Datetime'].dt.year
df['Month'] = df['Datetime'].dt.month
df['Day'] = df['Datetime'].dt.day
df['DayOfWeek'] = df['Datetime'].dt.dayofweek

Answer 1

This currently isn't possible with Data Refinery. I used a notebook and Pandas to do this data processing.