Fetch the value for the latest date in the index row

Question

my table looks something like this:

Sector	4/1/2022	5/1/2022	6/1/2022	1Y Min
A	10	05	12	05
B	18	20	09	09
C	02	09	12	02

I want to add a new column "Bps away from 1Y Min" such that values of the new column is calculated using the formula: (Value as of the latest date – 1Y Min)
I want to keep the latest date column dynamic within the formula such that it gets updated whenever a column with a new date is available.

For eg:-

Sector	4/1/2022	5/1/2022	6/1/2022	1Y Min	Bps away from 1Y Min
A	10	05	12	05	7
B	18	20	09	09	0
C	02	09	12	02	10

Asked By: Saanchi

||

Source

Answer 1

You can use a helper function to find the max date from the column names (and assigning suitably low values for non-dates), and then it’s just pandas.

import datetime
def dt_helper(dt_string):
    try:
        return datetime.datetime.strptime(dt_string, '%d/%m/%Y').date()
    except:
        return datetime.date(1900,1,1)

df['Bps away from 1Y Min'] = df[max(df.columns, key=dt_helper)] - df['1Y Min']

It’s not clear if your dates are dd/mm/yyyy or mm/dd/yyyy, I’ve assumed the former, but if the latter then change the date pattern to '%m/%d/%Y'

Answered By: bn_ln

Fetch the value for the latest date in the index row

Question:

Answers: