-please solve this simple Python question asap, and I'll give thumbs up directly.

- the excel links are not accesible here, but i have screenshots along with the links (to copy the adress ).

link 1:

loandata.csv

link 2:

loandata.xlsx

Lab Objectives - Introduction to Pandas library Series and DataFrame. Lab Exercise You have two files: "loandata.csv","loandata.xlsx". Write Python code blocks that do the following: 1. Read data from the two files. 2. Display the contents of the two files. 3. Display the 2nd and 4th columns from loandata.csv" file. Find out and display information of who has (Loan Status = Y) from loandata.csv"file. s. Insert a column in the third position of the "loandata.xlsx" and fill it with 'nan' values. Display the shape of loandata.xlsx"file. 2. Find and drop the missing values from loandata.xlsx file. Find out and display information of who has (ApplicantIncome>8000 or CoapplicantIncome>3000) from "loandata.xlsx"file. Concat the two files "loandata.csv" & "loandata.xlsx". Save the newfile as "Newloandata.csv". loandata.csv - Excel Product Activation Failed FLE HOME INSERT PAGE LAYOUT FORMULAS DATA REVIEW VIEW Xcut Calibri General Paste Copy Format Painter BIU AA - Wrap Text A. + Merge & Center - Alignment $.% 24 Insert Delete Format Conditional Formatas Cell Formatting Table Styles Clipboard Font Number Cells 115 1 } K L M N o P NO 6000 Yes D F G H 1 Loan_ID Gender Married Self_Empl Applicant Coapplica LoanAmoi Loan Status 2LPO01002 Male No No 5849 0 Y 3LPOO1003 Male Yes No 4583 1508 128 N 4 LPO01005 Male Yes Yes 3000 0 66 Y 5 LP001006 Male Yes No 2583 2358 120 Y 6 LPO01008 Male No 0 141 Y 7 LP001011 Male Yes 5417 4196 267 Y 8 LPOO1013 Male Yes No 2333 1516 95 Y 9 LP001014 Male Yes No 3036 2504 158 N 10 LPO01018 Male Yes No 4006 1526 168 Y 11 LPO01020 Male Yes No 12841 10968 349 N 12 LP001024 Male Yes No 3200 700 70 Y 13 LP001027 Male Yes 1840 109 Y 14 LPO01028 Male Yes No 3073 8106 200 Y 15 LP001029 Male No No 1853 2840 114 N 16 17 18 19 20 21 22 23 2500 - loandata READY Type here to search o i P 1 G O G loandata.xlsx - Ercel (Product Activation Failed FLE HOME INSERT PAGE LAYOUT FORMULAS DATA REVIEW VIEW Xcut Calibri General Paste Copy Format Paint BTV - A A 2- - Wrap Text A. + Merge & Center - Alignment $% Insert Delete Format Conditional Formatas Cell Formatting Table Styles Clipboard Font Number Cens 116 1 } K L M N o P NO 6000 Yes D F G H 1 Loan_ID Gender Married Self Empl Applicant Coapplica LoanAmoi Loan_Status 2LPO01002 Male No No 5849 0 Y 3LPOO1003 Male Yes No 4583 1508 128 N 4 LPO01005 Male Yes Yes 3000 0 66 Y 5 LP001006 Male Yes No 2583 2358 120 Y 6 LPO01008 Male No 0 141 Y 7 LP001011 Male Yes 5417 4196 267 Y 8 LPOO1013 Male Yes No 2333 1516 95 Y 9 LP001014 Male Yes No 3036 2504 158 N 10 LPO01018 Male Yes No 4006 1526 168 Y 11 LPO01020 Male Yes No 12841 10968 349 N 12 LPO01024 Male Yes No 3200 700 70 Y 13 LP001027 Male Yes 1840 109 Y 14 LPO01028 Male Yes No 3073 8106 200 Y 15 LPO01029 Male No No 1853 2840 114 N 16 17 18 19 20 21 22 23 2500 - loandata READY Type here to search o i P O 1 G O G