library(fpp3) library(readabs) consumptionData <- read_abs_series ("A2302449w", release_date mutate (Quarter = as_tsibble( index Quarter ) %>% yearquarter (date)) %>% filter (year (Quarter)>=1990) %>% select(value) %>% rename (Consumption = value) incomeData <- read_abs_series ("A2302702R", release_date mutate (Quarter = yearquarter (date)) %>% as_tsibble( index Quarter ) %>% filter (year (Quarter) >=1990) %>% select(value) %>% rename (Income = value) aus change <- left_join(consumptionData, incomeData) %>% relocate (Quarter) = "2023-12-01") %>% = "2023-12-01") %>%

library(fpp3) library(readabs) consumptionData <- read_abs_series ("A2302449w", release_date mutate (Quarter = as_tsibble( index Quarter ) %>% yearquarter (date)) %>% filter (year (Quarter)>=1990) %>% select(value) %>% rename (Consumption = value) incomeData <- read_abs_series ("A2302702R", release_date mutate (Quarter = yearquarter (date)) %>% as_tsibble( index Quarter ) %>% filter (year (Quarter) >=1990) %>% select(value) %>% rename (Income = value) aus change <- left_join(consumptionData, incomeData) %>% relocate (Quarter) = "2023-12-01") %>% = "2023-12-01") %>%

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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RosterGrades=readtable('RosterScores.txt'); RosterGrades.Grades=cell([size(RosterGrades,1),1]); for i=1:size(RosterGrades,1) if RosterGrades.Scores(i)>=90 RosterGrades.Grades{i}='A'; elseif RosterGrades.Scores(i)>=80 RosterGrades.Grades{i}='B'; elseif RosterGrades.Scores(i)>=70 RosterGrades.Grades{i}='C'; elseif RosterGrades.Scores(i)>=60 RosterGrades.Grades{i}='D'; else RosterGrades.Grades{i}='F'; end end RosterGrades writetable(RosterGrades,'RosterScores.txt')
function [ ] = square_spectrum( L,N )%Activity 1 for CEN415 Summer 2022 x=linspace(0,2*L,200);f1=(-1).^floor(x/L);plot(x,f1)f2=0;for n=1:2:N, f2=f2+4*sin(n*pi.*x/L)/n/pi;endhold onplot(x,f2)hold offend Q1= Run the function for L=3 and N=7 and upload the image of the graph plotted USE MATLAP
function [ ] = square_spectrum( L,N )%Activity 1 for CEN415 Summer 2022 x=linspace(0,2*L,200);f1=(-1).^floor(x/L);plot(x,f1)f2=0;for n=1:2:N, f2=f2+4*sin(n*pi.*x/L)/n/pi;endhold onplot(x,f2)hold offend Q1= Which one is true? a. When the N increases, the approximated graph tends to be closer to the original square wave b. When the L increases, the approximated graph tends to be closer to the original square wave c. When the L decreases, the approximated graph tends to be closer to the original square wave d. When the N decreases, the approximated graph tends to be closer to the original square wave e. None
function [ ] = square_spectrum( L,N )%Activity 1 for CEN415 Summer 2022 x=linspace(0,2*L,200);f1=(-1).^floor(x/L);plot(x,f1)f2=0;for n=1:2:N, f2=f2+4*sin(n*pi.*x/L)/n/pi;endhold onplot(x,f2)hold offend Q1= In which case the bandwidth decreases? a. When N decreases b. When L increases c. When L decreases d. When N increases e. None
function [ ] = square_spectrum( L,N )%Activity 1 for CEN415 Summer 2022 x=linspace(0,2*L,200);f1=(-1).^floor(x/L);plot(x,f1)f2=0;for n=1:2:N, f2=f2+4*sin(n*pi.*x/L)/n/pi;endhold onplot(x,f2)hold offend 2-Run the function for L=3 and N=3 and upload the image of the graph plotted use matlap
function [ ] = square_spectrum( L,N )%Activity 1 for CEN415 Summer 2022 x=linspace(0,2*L,200);f1=(-1).^floor(x/L);plot(x,f1)f2=0;for n=1:2:N, f2=f2+4*sin(n*pi.*x/L)/n/pi;endhold onplot(x,f2)hold offend 1-Run the function with L=3 and N=1 and upload the plotted graph use matlap
get_total_cases() takes the a 2D-list (similar to database) and an integer x from this set {0, 1, 2} as input parameters. Here, 0 represents Case_Reported_Date, 1 represents Age_Group and 2 represents Client_Gender (these are the fields on the header row, the integer value represents the index of each of these fields on that row). This function computes the total number of reported cases for each instance of x in the text file, and it stores this information in a dictionary in this form {an_instance_of_x : total_case}. Finally, it returns the dictionary and the total number of all reported cases saved in this dictionary.
# A set of constants, each representing a list index for station information. ID = 0 NAME = 1 LATITUDE %3D LONGITUDE 3 САРАСITY 4 BIKES_AVAILABLE %3D DOCKS_AVAILABLE %3D NO_KIOSK "SMART' # For use in the get_lat_lon_distance helper function EARTH_RADIUS = 6371 # SAMPLE DATA TO USE IN DOCSTRING EXAMPLES SAMPLE_STATIONS [7090, 'Danforth Ave / Lamb Ave', 43.681991, -79.329455, 15, 4, 10], [7486, 'Gerrard St E / Ted Reeve Dr', 43.684261, -79.299332, 24, 5, 19], [7571, 'Highfield Rd / Gerrard St E - SMART', 43.671685, -79.325176, 19, 14, 5]] HANDOUT_STATIONS [7000, 'Ft. York / Capreol Crt.', 43.639832, -79.395954, 31, 20, 11], [7001, 'Lower Jarvis St SMART / The Esplanade', 43.647992, -79.370907, 15, 5, 10]]
Problem set4.
calculate_new_balance Given a starting balance (a number), and a list of transaction tuples, calculate the final balance for an account. Transaction tuples are of the shape ("description", amount, "withdrawal") , or ("description", amount, "deposit"). The last entry in the tuple will be either "withdrawal" or "deposit". Every withdrawal decreases the balance of the account by the specified amount, and every deposit increases the balance. The return value is the new account balance, as a number. (which could be negative) Sample calls should look like: >>> calculate_new_balance(100, [("payday", 20, "deposit"), ("new shoes", 50, "withdrawal"), ("illicit winnings", 200, "deposit")])270>>> calculate_new_balance(100, [])100
def buy_sell_stock_prices(stock_prices): current_buy = stock_prices[0] global_sell = stock_prices[1] global_profit = global_sell - current_buy for i in range(1, len(stock_prices)): current_profit = stock_prices[i] - current_buy if current_profit > global_profit: global_profit = current_profit global_sell = stock_prices[i] if current_buy > stock_prices[i]: current_buy = stock_prices[i] return global_sell - global_profit, global_sell stock_prices_1 = [10,9,16,17,19,23]buy_sell_stock_prices(stock_prices_1)# (9, 23) stock_prices_2 = [8, 6, 5, 4, 3, 2, 1]buy_sell_stock_prices(stock_prices_2)# (6, 5).
In java create an application to manage your data base information the database is already created in mysql tables, the tables are fill, So the user can use your database application user friendly Retrieve all data: Given a table name, retrieve all data from the table and present it to the user. Average: Given a table name and a column name, return the average of the column. Here the assumption is that the column type will be numeric (e.g., cost column). Insert: Given a table name, your program should show the column names of that table and ask the users to input new data to the table. In case of errors, your program should directly show the MySQL errors to the users. Assumption 1: Users will enter data according to the database constraints. Assumption 2: Users will input one record at a time. Delete: Given a table name, your program should show the column names of that table and ask the users to input data that they want to delete. Assumption 1: Users will enter data according to the…