Extract several values from a row when a certain value is found using a list

I have a .csv file with 29 columns and 1692 rows.
The columns D_INT_1 and D_INT_2 are just dates.
I want to check for these 2 columns if there is dates between :>= "2022-03-01" and <= "2024-12-31.
And, if a value is found, I want to display the date found + the value of the column "NAME" that is located on the same row of said found value.

This is what I did right now, but it only grab the dates and not the adjacent value ('NAME').

# importing module
import pandas as pd
# reading CV file
df = pd.read_csv("scratch_2.csv")

# converting column data to list
D_INT_1 = df['D_INT_1'].tolist()
D_INT_2 = df['D_INT_2'].tolist()



ext = []

ext = [i for i in D_INT_1 + D_INT_2 if i >= "2022-03-01" and i <= "2024-12-31"]

print(*ext, sep="\n")

This is what I would like to get:

Example of DF:

NAME, ADDRESS, D_INT_1, D_INT_2
Mark, H4N1V8, 2023-01-02, 2019,-01-01

Expected output:

MARK, 2023-01-02

>Solution :

First for performance dont use loops, because exist vectorized alternatives unpivot by DataFrame.melt and filter by Series.between with DataFrame.loc:

df = df.melt(id_vars='NAME', value_vars=['D_INT_1','D_INT_2'], value_name='Date')

df1 = df.loc[df['Date'].between("2022-03-01","2024-12-31"), ['NAME','Date']]

print (df1)
   NAME       Date
0  Mark 2023-01-02

Or filter original DataFrame and last join in concat:

df1 = df.loc[df['D_INT_1'].between("2022-03-01","2024-12-31"), ['NAME','D_INT_1']]
df2 = df.loc[df['D_INT_2'].between("2022-03-01","2024-12-31"), ['NAME','D_INT_2']]

df = pd.concat([df1.rename(columns={'D_INT_1':'date'}), 
                df2.rename(columns={'D_INT_2':'date'})])

print (df)
   NAME       date
0  Mark 2023-01-02

Last if need loops output with print:

for i in df.itertuples():
    print (i.NAME, i.Date)
    
Mark 2023-01-02 00:00:00
Mark 2019-01-01 00:00:00