# Engineering Programming Task on EIT moodle

int first, last;
first=1;
last=10;
for (i=first; i&lt;last; i++)
{

# R Programming Task using the Data Analytics Approach

str(creditDF)

# Q1)
# Exploratory Data Analysis Continue reading

# Database Task on Baby Names

— Query 1 —

SELECT
SUM(number) AS record_count
FROM

—————CREATE CUSTOMER
CREATE TABLE CUSTOMER(CUSTOMERID INT NOT NULL PRIMARY KEY,
CUSTOMERFIRST VARCHAR(50) NOT NULL,
CUSTOMERLAST VARCHAR(50) NOT NULL ,
CUSTOMERSTREET VARCHAR(50) NOT NULL , Continue reading

# Programming Task on Memoization in Scheme

#lang racket

#| Problem 1 |#
; Define the Fibonacci function fib as usual
(define (fib n)
(if (<= n 2) 1
(+ (fib (- n 1)) (fib (- n 2))))) Continue reading

# Programming – Jupyter Notebook Task

{
“cells”: [
{
“cell_type”: “code”,
“execution_count”: 1,
“outputs”: [],
“source”: [

#!/usr/bin/env python
# coding: utf-8

# Essential Problem 1:
# a). Here at least one point is required in each grid, thus the least number of data points are 100
# b). Here the dimension has changed to 3. Thus the least number of data points are 10^3 = 1000.
# c). Here the dimension has changed to 3. Thus the least number of data points are 10^(10)

— version 4.9.2

# SQL – Design and Analysis of Data Systems

— version 4.9.2

— Host: 127.0.0.1
— Generation Time: Apr 06, 2020 at 01:56 PM
— PHP Version: 7.2.26

SET SQL_MODE = “NO_AUTO_VALUE_ON_ZERO”;
SET AUTOCOMMIT = 0;
START TRANSACTION;
SET time_zone = “+00:00”;
/*!40101 SET @OLD_CHARACTER_SET_CLIENT=@@CHARACTER_SET_CLIENT */;
/*!40101 SET @OLD_CHARACTER_SET_RESULTS=@@CHARACTER_SET_RESULTS */;
/*!40101 SET @OLD_COLLATION_CONNECTION=@@COLLATION_CONNECTION */;
/*!40101 SET NAMES utf8mb4 */;

— Database: `oltp`

— ——————————————————–

— Table structure for table `adventureworks`

`ID` int(10) NOT NULL,
`Name` varchar(35) NOT NULL,
`Bike` varchar(35) NOT NULL,
`Model` varchar(35) NOT NULL,
`Color` varchar(35) NOT NULL,
`Year` year(4) NOT NULL,
`Sold` varchar(35) NOT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

— Dumping data for table `adventureworks`

INSERT INTO `adventureworks` (`ID`, `Name`, `Bike`, `Model`, `Color`, `Year`, `Sold`) VALUES
(10, ‘Brown’, ‘Honda’, ‘H789’, ‘Red’, 2002, ‘Yes’),
(11, ‘Lucy’, ‘Adventure’, ‘A345’, ‘Blue’, 2003, ‘Yes’),
(12, ‘Alfreds’, ‘Flyer’, ‘F567’, ‘Black’, 2004, ‘Yes’),
(13, ‘Kaze’, ‘Activa’, ‘A345’, ‘Red’, 2003, ‘No’),
(14, ‘Lucy’, ‘Adventure’, ‘A345’, ‘Blue’, 2003, ‘No’),
(15, ‘Alfreds’, ‘Flyer’, ‘F567’, ‘Black’, 2004, ‘No’),
(16, ‘Kaze’, ‘Activa’, ‘A345’, ‘Red’, 2003, ‘Yes’),
(17, ‘Brown’, ‘Honda’, ‘H789’, ‘Red’, 2002, ‘No’),
(18, ‘Lucy’, ‘Adventure’, ‘A345’, ‘Blue’, 2003, ‘Yes’),
(19, ‘Alfreds’, ‘Flyer’, ‘F567’, ‘Black’, 2004, ‘No’),
(20, ‘Kaze’, ‘Activa’, ‘A345’, ‘Red’, 2003, ‘Yes’);

— ——————————————————–

— Table structure for table `customer`

CREATE TABLE `customer` (
`customerID` varchar(35) NOT NULL,
`ID` int(10) NOT NULL,
`Name` varchar(35) NOT NULL,
`State/province` varchar(35) NOT NULL,
`Email` varchar(35) NOT NULL,
`SalesVolume` varchar(35) NOT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

— Dumping data for table `customer`

INSERT INTO `customer` (`customerID`, `ID`, `Name`, `Address`, `State/province`, `Email`, `SalesVolume`) VALUES
(‘C12’, 10, ‘Brown’, ‘Near Park 6’, ‘Newyork’, ‘brown@gmail.com’, ‘789’),
(‘C13’, 14, ‘Lucy’, ‘London near street 6’, ‘London’, ‘lucy@gmail.com’, ‘890’),
(‘C14’, 15, ‘Alfreds’, ‘South Carolina’, ‘South Est’, ‘a1@gmail.com’, ‘440’),
(‘C15’, 16, ‘Kaze’, ‘Near water park’, ‘London’, ‘ka@gmail.com’, ‘900’),
(‘C16’, 10, ‘Brown’, ‘Near Park 6’, ‘Newyork’, ‘brown@gmail.com’, ‘200’),
(‘C17’, 14, ‘Lucy’, ‘London near street 6’, ‘London’, ‘lucy@gmail.com’, ‘345’),
(‘C18’, 15, ‘Alfreds’, ‘South Carolina’, ‘South Est’, ‘a1@gmail.com’, ‘500’),
(‘C19’, 16, ‘Kaze’, ‘Near water park’, ‘London’, ‘ka@gmail.com’, ‘345’);

— ——————————————————–

— Table structure for table `dimemployee`

CREATE TABLE `dimemployee` (
`EmpID` varchar(35) NOT NULL,
`Name` varchar(35) NOT NULL,
`BikeID` varchar(35) NOT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

— Dumping data for table `dimemployee`

(‘E123’, ‘Tom Cru’, ‘Near Kk park’, ‘tw@gmail.com’, ‘123’, ’10’),
(‘E124’, ‘Maze’, ‘Water parrk’, ‘m@gmail.com’, ‘567’, ’11’),
(‘E125’, ‘Maze’, ‘Water parrk’, ‘m@gmail.com’, ‘567’, ’11’),
(‘E126’, ‘Tomy Cru’, ‘Near Kk park’, ‘tw@gmail.com’, ‘123’, ’12’),
(‘E127’, ‘Malle’, ‘Water parrk’, ‘m@gmail.com’, ‘567’, ’14’),
(‘E128’, ‘Toy Cru’, ‘Near Kk park’, ‘tw@gmail.com’, ‘123’, ’10’),
(‘E129’, ‘Maze’, ‘Water parrk’, ‘m@gmail.com’, ‘567’, ’15’),
(‘E130’, ‘Tom Cru’, ‘Near Kk park’, ‘tw@gmail.com’, ‘123’, ’19’),
(‘E131’, ‘Maze’, ‘Water parrk’, ‘m@gmail.com’, ‘567’, ’16’),
(‘E132’, ‘Tom Cru’, ‘Near Kk park’, ‘tw@gmail.com’, ‘123’, ’10’);

— Indexes for dumped tables

— Indexes for table `customer`

ALTER TABLE `customer`

— Indexes for table `dimemployee`

ALTER TABLE `dimemployee`