[FIXED] Finding YTD Change and MoM Change

Issue

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

1. I want to add a new column "1m change" such that values of the new column is calculated using the formula: (Value as of the latest date - Value as of one month prior to the latest date)

2. I want to add a new column "YTD change" such that values of the new column is calculated using the formula: (Value as of the latest date - Value as of first date of the year)

I want to keep both the formulas dynamic such that it gets updated whenever a column with a new date is available.

For eg:-

Sector	1/1/2022	5/1/2022	6/1/2022	1Y Min	1M Change	YTD Chg
A	10	05	12	05	7	2
B	20	20	60	09	40	40
C	02	09	12	02	3	10

Solution

Try doing this:

import numpy as np
import pandas as pd

df['1M Change'] = np.nan
df['YTD Chg'] = np.nan


df['1M Change'] = df.iloc[:, -4] - df.iloc[:, -5]
df['YTD Chg'] = df.iloc[:, -4] - df.iloc[:, 1]

def aaa():
    df['1M Change'] = df.iloc[:, -4] - df.iloc[:, -5]
    df['YTD Chg'] = df.iloc[:, -4] - df.iloc[:, 1]

df.insert(1, "lost", [2, 1, 3], True)
aaa()

print(df)

Immediately added columns: 1M Change, YTD Chg and filled them with empty values. Implicit iloc indexing is used (row index numbers on the left, column index numbers on the right). At the end, I added a column and called in the function to update the columns 1M Change, YTD Chg.

Answered By - inquirer