Resource InformationIn this assignment, you should work with book

Resource InformationIn this assignment, you should work with books.csv file. This file contains the detailed information about books scraped via the Goodreads . The dataset is downloaded from Kaggle website: https://www.kaggle.com/jealousleopard/goodreadsbooks/downloads/goodreadsbooks.zip/6Each row in the file includes ten columns. Detailed description for each column is provided in the following: bookID: A unique Identification number for each book. title: The name under which the book was published. authors: Names of the authors of the book. Multiple authors are delimited with -. average_rating: The average rating of the book received in total. isbn: Another unique number to identify the book, the International Standard Book Number. isbn13: A 13-digit ISBN to identify the book, instead of the standard 11-digit ISBN. language_code: Helps understand what is the primary language of the book.  num_pages: Number of pages the book contains. ratings_count: Total number of ratings the book received. text_reviews_count: Total number of written text reviews the book received.Task Write the following codes: Use pandas to read the file as a dataframe (named as books). bookIDcolumn should be the index of the dataframe. Use books.head() to see the first 5 rows of the dataframe. Use book.shape to find the number of rows and columns in the dataframe. Use books.describe() to summarize the data. Use books[‘authors’].describe() to find about number of unique authors in the dataset and also most frequent author. Use OLS regression to test if average rating of a book is dependent to number of pages, number of ratings, and total number of written text reviews the book received. Summarize your findings in a Word file.Instructions Please follow these directions carefully. Please type your codes in a Jupyter Network file and your summary in a word document named as follows:HW6YourFirstNameYourLastName.