Part I: Python Develop a web links scraper program in Python that extracts all of the unique web links that point out to other web pages from the HTML code of the Current Estimates web link and that populates them in a comma-separated values (CSV) file as absolute uniform resource indicators (URIs). Explain how the Python program extracts the web links from the HTML code of the Current Estimates web link. Explain the criteria you used to determine if a link is a locator to another HTML page. Specify the code segment that executes this action as part of your explanation. Explain how the program ensures that relative links are saved as absolute URIs in the output file. Specify the code segment that executes this action as part of your explanation. Explain how the program ensures that there are no duplicated links in the output file. Specify the code that executes this action as part of your explanation. Provide the Python code you wrote to extract all the unique web links from the HTML code of the Current Estimates web link that point out to other HTML pages. Provide the HTML code of the Current Estimates web page. Provide the CSV file that your script created. Test your script and provide a screenshot of the successfully executed results. Part II: SQL Calculate the mathematical difference in the population size estimates for each U.S. state the Census Bureau provided in two consecutive years using the most current data and the latest historical datasets for the national total population. Provide the SQL code and resulting table in your submission. Write a code to join the two tables on the year and state fields into one SQL table that identifies the absolute differences (in whole rounded hundreds) in the estimates of 10,000 individuals or more between the two datasets. If the earlier estimates are larger than 10,000, the cells should indicate a negative value. Provide a screenshot of your tested code showing successful execution. Explain how you prepared the data and how the datasets were imported into two SQL tables. Provide a screenshot of the successfully executed SQL code. Export the data from the SQL table into a CSV file, with rows representing the states and columns representing the years that both datasets estimate, that only shows the differences between the datasets (in whole rounded tens of thousands) that exceed 10,000 individuals. Part III: R Create a linear regression analysis with R to predict the size of the population for the state you live in for 2020 based on the Current Estimates Data dataset. Explain how you prepared the data and how the dataset was imported into R, including a screenshot of your results. Using the estimates for the most recent year in the dataset, create an R script to display a histogram (using one million as the interval size) of the current estimated population size of your state. Provide a screenshot of your results. Create an R script that will tabulate a statistical description of the estimated 2020 data. Provide a screenshot of your results. Predict the population size of your state using a linear regression. Provide a screenshot of your results. Acknowledge sources, using in-text citations and references, for content that is quoted, paraphrased, or summarized.