Loading...

Messages

Proposals

Stuck in your homework and missing deadline? Get urgent help in $10/Page with 24 hours deadline

Get Urgent Writing Help In Your Essays, Assignments, Homeworks, Dissertation, Thesis Or Coursework & Achieve A+ Grades.

Privacy Guaranteed - 100% Plagiarism Free Writing - Free Turnitin Report - Professional And Experienced Writers - 24/7 Online Support

Boy's life by howard korder script

28/10/2021 Client: muhammad11 Deadline: 2 Day

Write A Python Code On The Anaconda Navigator

Resource Information
In 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/6

Each 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.

{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Python Basics (Instructor: Dr. Milad Baghersad)\n", "## Module 6: Data Analysis with Python Part 1\n", "\n", "- Reference: McKinney, Wes (2018) Python for data analysis: Data wrangling with Pandas, NumPy, and IPython, Second Edition, O'Reilly Media, Inc. ISBN-13: 978-1491957660 ISBN-10: 1491957662\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "___\n", "___\n", "___\n", "___\n", "### review: Numpy (https://www.numpy.org/)\n", "NumPy, short for Numerical Python, is one of the most important foundational packages for numerical computing in Python.\n", "\n", "One of the key features of NumPy is its N-dimensional array object, or ndarray, which is a fast, flexible container for large datasets in Python. Arrays enable you to perform mathematical operations on whole blocks of data using similar syntax to the\n", "equivalent operations between scalar elements." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "b = np.array([[ 0, 1, 2, 3, 4],\n", " [ 5, 6, 7, 8, 9],\n", " [10, 11, 12, 13, 14]])\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(b)\n", "type(b)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(b.sum(axis=0)) # sum of each column" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "np.ones( (5,4) )" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#Create an array of the given shape and populate it with random samples from a uniform distribution over [0, 1)\n", "np.random.rand(4,2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "---\n", "---\n", "# pandas (https://pandas.pydata.org/)\n", "\n", "- Developed by Wes McKinney.\n", "- pandas contains data structures and data manipulation tools designed to make data cleaning and analysis fast and easy in Python.\n", "- While pandas adopts many coding idioms from NumPy, the biggest difference is that pandas is designed for working with tabular or heterogeneous data. \n", "- NumPy, by contrast, is best suited for working with homogeneous numerical array data.\n", "- Can be used to collect data from different sources such as Yahoo Finance!" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "my_data = np.random.rand(4,2)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "my_data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "type(my_data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### change the array to a pandas dataframe:\n", "A DataFrame represents a rectangular table of data and contains an ordered collection of columns, each of which can be a different value type (numeric, string, boolean, etc.)." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "my_data_df = pd.DataFrame(my_data)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "my_data_df" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "type(my_data_df)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "my_data_df.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#assign columns name\n", "my_data_df = pd.DataFrame(my_data,columns=[\"first column\", \"Second column\"])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "my_data_df" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#assign rows name\n", "my_data_df = pd.DataFrame(my_data,columns=[\"first column\", \"Second column\"],index=['a', 'b', 'c', 'd'])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "my_data_df" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#There are many ways to construct a DataFrame, though one of the most common is\n", "# from a dict of equal-length lists or NumPy arrays:\n", "data = {'state': ['Ohio', 'Ohio', 'Ohio', 'Nevada', 'Nevada', 'Nevada'],\n", " 'year': [2000, 2001, 2002, 2001, 2002, 2003],\n", " 'pop': [1.5, 1.7, 3.6, 2.4, 2.9, 3.2]}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "data_t = pd.DataFrame(data)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "data_t" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#For large DataFrames, the head method selects only the first five rows:\n", "data_t.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "data_t.tail()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "data_t.columns" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#If you specify a sequence of columns, the DataFrame’s columns will be arranged in that order:\n", "pd.DataFrame(data, columns=['year', 'state', 'pop'])" ] }, { "cell_type": "code",

Homework is Completed By:

Writer Writer Name Amount Client Comments & Rating
Instant Homework Helper

ONLINE

Instant Homework Helper

$36

She helped me in last minute in a very reasonable price. She is a lifesaver, I got A+ grade in my homework, I will surely hire her again for my next assignments, Thumbs Up!

Order & Get This Solution Within 3 Hours in $25/Page

Custom Original Solution And Get A+ Grades

  • 100% Plagiarism Free
  • Proper APA/MLA/Harvard Referencing
  • Delivery in 3 Hours After Placing Order
  • Free Turnitin Report
  • Unlimited Revisions
  • Privacy Guaranteed

Order & Get This Solution Within 6 Hours in $20/Page

Custom Original Solution And Get A+ Grades

  • 100% Plagiarism Free
  • Proper APA/MLA/Harvard Referencing
  • Delivery in 6 Hours After Placing Order
  • Free Turnitin Report
  • Unlimited Revisions
  • Privacy Guaranteed

Order & Get This Solution Within 12 Hours in $15/Page

Custom Original Solution And Get A+ Grades

  • 100% Plagiarism Free
  • Proper APA/MLA/Harvard Referencing
  • Delivery in 12 Hours After Placing Order
  • Free Turnitin Report
  • Unlimited Revisions
  • Privacy Guaranteed

6 writers have sent their proposals to do this homework:

Accounting & Finance Mentor
Math Guru
Quick N Quality
Best Coursework Help
Innovative Writer
Finance Homework Help
Writer Writer Name Offer Chat
Accounting & Finance Mentor

ONLINE

Accounting & Finance Mentor

I am a PhD writer with 10 years of experience. I will be delivering high-quality, plagiarism-free work to you in the minimum amount of time. Waiting for your message.

$31 Chat With Writer
Math Guru

ONLINE

Math Guru

I am an elite class writer with more than 6 years of experience as an academic writer. I will provide you the 100 percent original and plagiarism-free content.

$16 Chat With Writer
Quick N Quality

ONLINE

Quick N Quality

I have written research reports, assignments, thesis, research proposals, and dissertations for different level students and on different subjects.

$35 Chat With Writer
Best Coursework Help

ONLINE

Best Coursework Help

I will provide you with the well organized and well research papers from different primary and secondary sources will write the content that will support your points.

$33 Chat With Writer
Innovative Writer

ONLINE

Innovative Writer

I have written research reports, assignments, thesis, research proposals, and dissertations for different level students and on different subjects.

$20 Chat With Writer
Finance Homework Help

ONLINE

Finance Homework Help

I will be delighted to work on your project. As an experienced writer, I can provide you top quality, well researched, concise and error-free work within your provided deadline at very reasonable prices.

$30 Chat With Writer

Let our expert academic writers to help you in achieving a+ grades in your homework, assignment, quiz or exam.

Similar Homework Questions

Aircraft electrical bonding test - The marrow thieves frenchie quotes - Google in china case study analysis answers - Darrick wood infant school - The gambler who blew $127 million - Google scholar forward citation search - Interactive cow eye dissection - How to write a good reflective statement ib - Food cost percentage meaning - Dq 1 - Writing a memo - Traditional chinese warrior clothing - Juvenile Delinquency - Human anatomy and physiology laboratory manual 12th edition answer key - Normandy trident group pbc - Goeller scorecard - Duffy's quality caring model - Plus dane management team - The manager of a store that specializes in selling tea - Biorad dc protein assay - History of ethnographic research - Pavel tsatsouline height weight - St george term deposit interest - Merriam and caffarella learning in adulthood - Animal cell song lyrics - William shakespeare webquest answer key - How do i spell repore - Radius server dead criteria - Riyadh cable ampere rating - Legacy of the progressive era - 5016_ASS 2 # DRAFT 1 # Assessment 2 Instructions: Demand Management Plan # MBA-FPX5016 Operations Mgmt For Leaders - Wjec new specification english - Reply 1 and 2 ,150 words each one add references and citations by 08/23/2020 at 6:00 pm08/23 2020 - Article review 2 -734 - Pic microcontroller instruction set with examples - I have three assignment due in the next three days - Luna capri matenga driver - The ones who walk away from omelas discussion questions - Economics - Ucl spanish evening courses - Chronic Disease Management - Cessna caravan ex price - Types of timber joinery - Tenets of psychoanalytic theory - Math in the Bible - ME - Main - Dis 5 - Strengths based nursing care gottlieb - Http www stress org uk individual stress test - Bankstown tafe modern history - Astucia lights road studs australia - Term time loughborough university - Multidimensional scaling in marketing research ppt - Cuando tenía gripe mi madre me tomar la temperatura - Black bear behavioral adaptations - Www breckland gov uk gardenwaste - Analyzing John Yorke’s “What Makes a Great Screenplay?” - The danger of a single story worksheet answers - 972 464 7674 - Cwv topic 5 review - Could not synchronize record to exchange server 19736 - Dozier company produced and sold units - No wonder they call me a bitch - National desexing month 2021 - Semester Goals- "Feeling Paper" - How to open fiori launchpad from gui - Realme is planning to launch realme NEO for the premium segment - priced at INR 35,000 - M&l manufacturing case study solution - Read And Respond-4 - Chemistry prefixes 1 10 - Peaceful mountain stomach rescue recall - Paper writing - A skydiver steps from a high flying helicopter - Write 19 20 as a decimal - What is iptv mean - Barbie doll by marge piercy theme - Dulux durebild ste application - Algebraic notation year 7 - Occupational therapy clinical reasoning examples - Australian catholic university atar - Acara work samples year 3 writing - Rectangular tray using sheet metal - My body Politic - Parts of bunsen burner - Initiating the Project - Problem Set 6 - Information technology in global Economy - 145 laurel ave chelmer - Vcaa cross curriculum priorities - For prof avril - Studies in social power - A gram sample of a hydrate of calcium - Arcon articulator vs non arcon - Gmo persuasive speech outline - Literacy and numeracy assessment sample - 8 2 2 project 3 multimedia presentation submission - Hn 522 Discussion 8 - Knox park primary school - ACC 499 Week 10 Discussion 1 "Taxes" - Conch republic electronics case study - Cardiac and vascular function curves - History