QUESTION:I have a fully functional written code that is error free but there's an issue that I have in regards of adding my ".css" file to my ".html" file. The purpose of my assignment is to change the background color of the page when asked to ""Please enter a hexadecimal color code", which I can, but in my CSS file, I must write a code to set the background color of my page to #FFB3B3. The whole code is written and below I posted the Instructions for the assignment to better assist you in recognizing in what I'm looking for.Specific Instructions for Assignment 7:Perform all of the following steps to complete this assignment:1) Begin by creating a new file in your text editor and include all of the basic HTML code like you did in your previous assignments. Or you can simply make a copy of your HTML file from last week and name the new copy LastFirstAssignment7.html (where "Last" is your last name and "First" is your first name), but be careful not to overwrite your file from last week because you will need it again when you do your Final Project during Week 8. 2) Make sure you change the contents of the <title> tag to "Assignment 7" (just the words – not the quotation marks) and make sure your full name is inside of the <h1> heading, just like in your previous assignments. Also, delete the contents of the <script> tag -- everything between the <!-- and //--> tags, if you created your new file by making a copy of your previous file, because you will be creating a brand new page with different JavaScript code for this assignment. Save your file.3) Upload this file to the HTML validator to check for compliance with the HTML5 standards. Your file should pass validation. If you receive any errors or warnings, then go back through the previous steps of the assignment again until you have corrected all errors and your file passes validation.4) Create another new file in your text editor and save it as Assignment7.css or make a copy of last week's CSS file, being careful not to overwrite last week's file.5) In your CSS file, write code to set the background color of your page to #FFB3B3 and write code to center the h1 element. Save your CSS file.6) Access your webpage again in your browser and confirm that your page has a pale red background and that the heading is centered. Upload your CSS file to the CSS validator to check for compliance with the CSS standards. Your file should pass validation. If you receive any errors or warnings, debug your CSS code until you have corrected all errors and your file passes validation.7) Open your Assignment 7 HTML file for editing. Next, you will reuse and slightly modify code from Lab 11-4. Make sure you change the value of "expires" to a future date. Similar to Lab 11-4, prompt the user to enter a hexidecimal color code. However, instead of prompting them for their name, prompt them to enter their age. Your code should set a cookie with the information the user enters and then retrieve that information from the cookie and set the page background to the color entered by the user.Note: It is recommended that you test this assignment in Internet Explorer and/or Firefox. This code may not work correctly in Chrome.

First, we would like you to get us some general statistics from the data. I suggest you create a dictionary of lists with the keys being the heads of the CSV file (or columns of clean DataFrame) and the list attached to it being all of the values for that heading. Duplicates should be included here. This is only a suggestion. If you want to just keep using the DataFrame you are welcome to.Produce the following and write it to a text file called Marvel_Mart_Rankings.txt. Be sure to use append so that you can append data rather than writing over top of the previous data. Be sure to include a newline between each append to the file. When writing to the file, please output in a text form such as: (note you are getting a count of the number of sale transactions here not the sum of the total sales! To be clear: you want a count of the number of sale transactions. Do not sum up the Units Sold. Do not use sum at all. You are getting the count of the number of transactions done per country)Countries Most Sale Transactions:Country 1: (number of sales transactions)Country 2: (number of sales transactions)...(Answer question) "The country we should build our shipping center is ______ because ____..."(A) We want to know which countries we sell the most to so we can pick a new location to build a shipping center. Rank the Top 10 countries we sell to the most to least along with the number of sales we've had with that country. We have shipping centers in Trinidad and Tobago, Guinea, and Maldives right now. Which country should we build a shipping center in based on most sales and lack of shipping center? Please justify your reasoning.(B) Rank the top 3 years we did the most sales (brought in most profit) in to the least sales. (Just the years, not the whole dates). Use the Order Date, not the Ship Date. Please list the years and the amount sold. Answer the question "Which year did we sell the most in?"(doing large number sums with floats in Python usually produces scientific notation but we don't want that. You can turn that off by putting the following line under the import statements at the start of the script:pd.set_option('display.float_format', lambda x: '%.3f' % x)For some reason, it wouldn't upload the csv file so I'll just share it using google spreadsheets:https://docs.google.com/spreadsheets/d/1-xH-bodk3t..._______________________________________________________Here is how I started off:Here is my dictionary but I don't know if this is right:df1 = pd.read_csv('Marvel_Mart_Sales_clean.csv', delimiter=',')mydic = {'Region':[df1['Region']], 'Country': [df1['Country']], 'Item Type': [df1['Item Type']],'Order Date': [df1['Order Date']], 'Order ID': [df1['Order ID']], 'Order Priority': [df1['Order Priority']],'Sales Channel': [df1['Sales Channel']], 'Ship Date': [df1['Ship Date']], 'Total Cost': [df1['Total Cost']],'Total Profit': [df1 ['Total Profit']], 'Total Revenue': [df1['Total Revenue']],'Unit Cost': [df1['Unit Cost']], 'Unit Price': [df1['Unit Price']], 'Units Sold': [df1['Units Sold']]}