I would like to convert my date column into an indicator of the quarter of that particular year, say 2018q1 or 2018q2 etc.
My data looks like this, I have stock returns once per quarter (not showing the return column here), and a corresponding date, the column quarter is what I would like to get (or something similar)
data = [
{'date': '3/22/18', 'quarter': 1},
{'date': '3/22/18', 'quarter': 1},
{'date': '6/22/18', 'quarter': 3},
{'date': '6/22/18', 'quarter': 3},
{'date': '9/22/18', 'quarter': 2},
{'date': '9/22/18', 'quarter': 2}]
df = pd.DataFrame(data, index=['s1', 's2','s1','s2','s1','s2'])
date quarter
s1 3/22/13 2013q1
s2 3/24/13 2013q1
s1 6/21/13 2013q2
s2 6/26/13 2013q2
s1 9/21/13 2013q3
s2 9/28/13 2013q3
Pandas has a method to help you, it's called pd.PeriodIndex(monthcolumn, freq= 'Q'). You may need to convert your month column to datatype first by using datetime libray.
Pandas also have a method called 'to_date' that you can use to convert a column to a date column.
For example:
df["year"] = pd.to_date(df["year"])