The population of the five most populous Australian cities at the last three census is recorded in the following cell. Plot a side- by-side bar chart to show the change in the populations. The chart should be grouped by each city and show each census in different colours. The legend should explain the colours for the census. Your plot should include an appropriate title. In [ 1: cities = ('Sydney', 'Melbourne', 'Brisbane', 'Perth', Adelaide'] Pop_2016 - (4321535,4196198,2054614,1874578,1165632] Pop_2011 - [3908642,3707530,1874427,1627576,11039791 Pop_2006 - [3641422,3371888,1676389,1256035,1040719] In [ ]:

The population of the five most populous Australian cities at the last three census is recorded in the following cell. Plot a side- by-side bar chart to show the change in the populations. The chart should be grouped by each city and show each census in different colours. The legend should explain the colours for the census. Your plot should include an appropriate title. In [ 1: cities = ('Sydney', 'Melbourne', 'Brisbane', 'Perth', Adelaide'] Pop_2016 - (4321535,4196198,2054614,1874578,1165632] Pop_2011 - [3908642,3707530,1874427,1627576,11039791 Pop_2006 - [3641422,3371888,1676389,1256035,1040719] In [ ]:

Np Ms Office 365/Excel 2016 I Ntermed

1st Edition

ISBN:9781337508841

Author:Carey

Publisher:Carey

Chapter5: Working With Excel Tables, Pivottables, And Pivotcharts

Section: Chapter Questions

Problem 11RA

See similar textbooks

Similar questions

The monthly payment M of a loan amount P for y years and with interest rate r can be calculated by the formula: P(r/12) M = 1-(1+r/12)-12y Calculate the monthly payment and the total payment for a $100,000 loan for 10, 11, 12, ..., 29, 30 years with an interest rate of 4.85%. Display the results in a three-column table where the first column is the number of years, the sec- ond is the monthly payment, and the third is the total payment.
What is the Manhattan distance between different points as shown below? Fill the table with appropriate Manhattan distances. As an example, the distance between points A and C is computed in the appropriate table cell
Using R, create a dataset with 4 column of integers. Use the function boxplot to provide displays of each column of the dataset. Hand in these plots, all in one page. (to do this, use the graphical function par before plotting. The function par(mfrow=c(2,3))
The accompanying Gradebook spreadsheet contains a partially completed spreadsheet model for computing and summarizing the grades for a class. Complete the spreadsheet model by entering and copying the formulas in the appropriate cells. Cell range H4:H17 should contain the course number grades using the grades from exams and homework assignments and the grade allocation in row 22. Cell range I4:I17 should contain the course letter grades based on the grading criteria in cell range K4:L8. Rows 19, 20, and 21 should contain the average, maximum, and minimum exam, homework, and course number grades. You should only enter each formula once and copy the formulas to other cells. Gradebook Student ID Exam 1 Exam 2 Exam 3 Homework 1 Homework 2 Homework 3 Course Number Grade Course Letter Grade Grading Criteria 000-01-5562 60 50 40 79 92.0 76 0 F 000-01-2667 80 71 70 84 81.0 90 60 D 000-01-7376 65 65 65 60 90.0 94 70 C 000-01-1986…
Use Python Code Your task is : Number of reported COVID-19 deaths by country. (Use pandas to read the csv table. Example : df = pd.read_csv('Covid19Deaths.csv') then do the code using the dataframe) COVID-19 Deaths table (csv): Province/State Country/Region Lat Long ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 2/1/2020 2/2/2020 2/3/2020 2/4/2020 2/5/2020 2/6/2020 2/7/2020 2/8/2020 2/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 3/1/2020 3/2/2020 3/3/2020 3/4/2020 3/5/2020 3/6/2020 3/7/2020 3/8/2020 3/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 4/1/2020 4/2/2020 4/3/2020 4/4/2020 4/5/2020 4/6/2020 4/7/2020 Afghanistan 33 65 0 0 0 0 0 0 0 0…
Let the document be “good bad student good bad instructor” and the query be “good student”. Fill out the empty columns in the following table and then compute the cosine similarity between the document vector and the query vector. In the table, df denotes document frequency, idf denotes inverse document frequency (i.e., idft = log10N/dft), tf denotes term frequency, log tf denotes the tf weight based on log-frequency weighting as shown in slides (i.e., 1+log10tft,d for tft,d> 0 and 0 otherwise), d is the document vector, d’ is the length-normalized d, q is the query vector, and q’ is the length-normalized q. Assume N (number of documents in the corpus) = 10,000,000.
dataset in picture Use the given dataset to perform the following using python: Name of dataframe (your reg_no+your_name) Import the given data set Find out its header and information Calculate the mean, median and mode of covid_deaths, covid_recoveries, and covid_cases Find out the total of covid affected cases(all three cases) in all countries Find out the total of covid related deaths in all countries Countries covid_deaths covid_recoveries covid_cases Pakistan 10000 520000 55000 India 12000 120000 130000 Bangladesh 14000 123000 120000 Srilanka 19000 213000 45000 Bhutan 12000 212 44000 Nepal 1000 9000 12300 Australia 80000 560000 32100 Singapore 2000 130000 12345 England 100000 320000 89765 USA 100000 890000 87898
Use Python Code Your task is : Use pandas to read the csv table . Example : df = pd.read_csv('Covid19Recovered.csv') . Then use the dataframe to make a visualization of the number of recovered patients using matplotlib, seaborn , etc . Just ignore lat and long. Covid-19 Recovered table (csv): Province/State Country/Region Lat Long ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 2/1/2020 2/2/2020 2/3/2020 2/4/2020 2/5/2020 2/6/2020 2/7/2020 2/8/2020 2/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 3/1/2020 3/2/2020 3/3/2020 3/4/2020 3/5/2020 3/6/2020 3/7/2020 3/8/2020 3/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 4/1/2020 4/2/2020 4/3/2020…
In cell C19, insert a formula that will calculate the projected advertising spending after the forecasted increase in cell A18 is added to the 2019 total. Ensure that the reference to cell A18 is an absolute cell reference.
V5. min jee wants to combine the sales data from each of the art fairs. switch to the combined sales worksheet and then update the worksheet as follows. in cell A5 enter a formula without using a function that references cell a5 in the Madison worksheet. copy the formula from cell a5 to the range a6:a8 without copying the formatting. in cell b5, enter a formula using the sum function, 3d references, grouped worksheets that totals the values from cell b:5 in the chicago: madison worksheets.
Modify the accompanying credit risk data using IF functions to include new columns, classifying the checking and savings account balances as low if the balance is less than $250, medium if at least $250 but less than $2000, and high otherwise.
The accompanying Homeownership spreadsheet contains a partially completed spreadsheet model for computing the monthly costs of home ownership. Complete the spreadsheet model by inserting the formulas for monthly mortgage payment, monthly property tax, monthly homeowner insurance premium, monthly maintenance costs , and total in the appropriate cells. Variables: House value: $ 450,000.00 Interest rate: 4.25% Down payment (% of house value): 20% Number of years: 30 Property tax rate: 1.25% Annual homeowner insurance premium: $ 1,400.00 Maintenance cost rate (% of house value): 1% Monthly Cost of Home Ownership Monthly mortgage payment: Monthly property tax: Monthly homeower insurance premium: Monthly maintenance costs: Total: 1. Is this a deterministic or stochastic model? 2. Which of the following is NOT an input of the spreadsheet model? A. Interest rate B. Monthly mortgage payment C. Number of years of…