In this tutorial, we learn to create univariate bar plots using the Graphics package in R. We also learn to modify graphical parameters associated with the bar plot.
Data Visualization With R: Learn To Combine Multiple GraphsRsquared Academy
In this tutorial, we learn to combine multiple graphs into a single frame using the par() and layout() functions. We also compare the differences between the two functions.
Data Visualization With R: Learn To Modify Title, Axis Labels & RangeRsquared Academy
This document contains slides from a data visualization course in R. It discusses how to modify the title, axis labels, and range of plots created in R. Specifically, it shows how to add these elements either by including arguments in the plot() function or by using the title() function. The title(), xlab, ylab, xlim, and ylim arguments can be used in plot() to customize the title, axis labels, and ranges. Alternatively, the title() function can be used after plotting but may overwrite default axis labels, so the ann argument should be set to FALSE in plot().
Learn the basics of data visualization in R. In this module, we explore the Graphics package and learn to build basic plots in R. In addition, learn to add title, axis labels and range. Modify the color, font and font size. Add text annotations and combine multiple plots. Finally, learn how to save the plots in different formats.
R is a free software environment for statistical computing and graphics that provides a wide variety of statistical techniques and graphical methods. It includes base functions and packages, and is used through interfaces like RStudio. R represents data using objects like vectors, matrices, and data frames. Common operations include calculations, generating random variables, and visualizing data. R can be used to analyze a glass fragment dataset to visualize compositions and potentially classify an unknown fragment.
Access intermediate 2010 final project newclscott1
The document provides instructions for a final Access Intermediate project to modify an existing Vacation database for Griffin and Emma MacElroy's travel agency, GEM Ultimate Vacations. Students are asked to download the database, save it under a new name, and perform tasks like modifying data, creating queries to find specific property records and allow country parameter selection, designing a form to display guest and reservation records, creating a report to group properties by country and count reservations, and generating mailing labels for guests. The modified Access database file is to be submitted for grading.
Learn to manipulate numbers in R using the built in numeric functions. This tutorial is part of the Working With Data module of the R Programming course offered by r-squared.
This document provides an introduction to MATLAB by covering key topics like the command window, inputs and outputs, M files, and basic programming structures in MATLAB such as conditionals and loops. Some key points covered include how to enter and manipulate matrices in the command window, perform basic math operations, load and save data, plot graphs, write M files to organize commands and create functions, and use conditional statements and loops in M files.
The document discusses two-dimensional arrays in C++. It explains that a two-dimensional array is an array of arrays, with elements arranged in rows and columns. It provides examples of declaring, initializing, accessing, inputting, and passing two-dimensional arrays as parameters to functions. It also gives examples of functions that perform operations on two-dimensional arrays, such as addition, multiplication, finding row/column sums, diagonal sums, and transposing the array.
This document provides an overview and introduction to using the statistical software R. It outlines R's interface, workspace, help system, packages, input/output functions, and how to reuse results. It also discusses downloading and installing R, basic functions and syntax, data manipulation techniques like sorting and merging, creating graphs, and performing statistical analyses such as t-tests, regression, ANOVA, and multiple comparisons. The document recommends several tutorials that provide more in-depth information on using R for statistical modeling, data analysis, and graphics.
This document provides an example of running an R script from Excel to create plots. It describes setting up an Excel file with buttons to run an R script and open the resulting PDF. The R script generates random data, plots it, and saves the plots to a PDF. Clicking the first button runs the R script, passing cell values as arguments. Clicking the second button opens the PDF if it was created.
statistical computation using R- an intro..Kamarudheen KV
This presentation deals with some basics of R language. It is very useful for benners in R. It describes the basics in a very easy manner, so those who are not familiar with R it would be very helpful.
The document discusses arrays in C programming. It defines arrays as groups of same data types that can store integer, float, character, or other data. Arrays allow storing multiple values in a single variable and accessing elements using indexes. The document provides examples of one-dimensional and two-dimensional arrays, and using for loops to initialize, input, and output array elements. Nested for loops are described for traversing two-dimensional or multi-dimensional arrays like matrices.
The document discusses arrays in C programming. It defines arrays as groups of same data types that can store integer, float, character, or other data. Arrays allow storing multiple values in a single variable and accessing elements using indexes. The document provides examples of one-dimensional and two-dimensional arrays, and explains how to initialize, declare, and access array elements. It also discusses using for loops and nested loops to iterate through arrays.
This document provides an example of integrating R and Excel using the XLConnect package. It summarizes data in R, generates a graph, and writes the results to an Excel template, applying formatting. Key steps include: loading an Excel template, writing an R data frame and summary results to sheets, adding a pre-generated graph image, and saving the updated workbook.
This document provides an introduction and overview of the MATLAB programming environment and its core functionality. It describes how to perform basic operations and calculations, write scripts and functions, work with vectors and matrices, and use common plotting and programming commands. Key features covered include MATLAB's command-line interface, help system, variables, operators, functions, file types (m-files and function files), flow control, and short summaries of many common commands.
This document contains the questions from an examination on algorithms and data structures. Question 1 asks about asymptotic analysis and simplifying Big-O expressions. Question 2 involves analyzing and implementing an insertion sort algorithm. Question 3 covers queue implementation using a circular array. Question 4 is about linear search. Question 5 deals with binary search trees, including drawing a tree from insertions, traversing methods, defining a node structure, and finding the minimum value.
This document describes Assignment 3 for the CS193P class, which involves enhancing an MVC application that displays polygons. Students will create a custom view to draw the polygon shape based on a model class. They will also add functionality to save and restore the number of polygon sides using user defaults. The assignment tests that the application draws polygons correctly, updates dynamically, and preserves state as expected. Hints provide code to calculate polygon points given parameters.
The document provides 6 programming assignments involving functions, recursion, pointers, structures, and unions in C language. Assignment 1 asks to write a program to display a word descending in length using a function. Assignment 2 asks to solve an equation using recursion. Assignment 3 asks to solve an equation using pointers. Assignment 4 asks to get and display system details using a structure. Assignment 5 asks to call and display output from a function without arguments. Assignment 6 asks to get and display book details using a union containing structures.
Conversion from infix to prefix using stackHaqnawaz Ch
This document is a data structures assignment that contains two tasks:
1) Converting an infix expression to postfix notation using a stack. The example infix expression is converted to postfix as -+-AB*C+DE+FG.
2) Evaluating the postfix expression from the first task by assigning values to variables and using a stack to calculate the result, which is 33.
The slides I was using when delivering a meetup about the matplotlib library. More info about that meetup can be found at https://www.meetup.com/life-michael/events/271738271/
The document discusses various types of plots that can be created in MATLAB, including:
1. Standard two-dimensional plots created using the plot command, which connects data points with lines. Additional lines and graphs can be added to the same plot using hold on/off or the line command.
2. Plots with logarithmic axes created using semilogy, semilogx, and loglog for situations where data spans a wide range of values.
3. Formatted plots where elements like titles, labels, legends, grids can be added using various commands.
4. Specialized plots like bar plots, stem plots, and pie charts for different data visualization needs.
5. The ability to place
This document discusses Sterling Integrator, including what it is, its key features and benefits, and how it addresses common enterprise integration problems. It also describes the main user interfaces in Sterling Integrator: the administration interface, map editor, and graphical process modeler. Finally, it provides information on creating and running maps in Sterling Integrator, including the different types of maps, components used, data formats supported, and how to compile and run a map.
2GKS, Open GL and IGES_Video Lect Given by Renjin.pptxRamanathanSabesan
The document discusses various CAD standards including:
- Graphic Kernel System (GKS) which provides 2D and interactive graphic capabilities across devices. It defines graphic primitives like polylines, fill areas, and text.
- Open Graphics Library (OpenGL) which is a graphics standard for image exchange and defines geometric objects and how they are rendered.
- Data exchange standards like IGES, STEP, and DXF that allow transfer of CAD models between different systems in a neutral format, with IGES having drawbacks like not supporting solid geometry models.
Background This course is all about data visualization. However, we.docxrosemaryralphs52525
This document provides instructions for a two-part data visualization assignment using RStudio. For part 1, students will analyze a unique dataset by exploring its structure, calculating summary statistics, and visualizing correlations. Screenshots of the analysis must be provided. For part 2, students will create various visualizations of the data, including pie charts, bar plots, histograms, box plots, and scatter plots. Screenshots of the visualizations must be submitted along with an APA style cover page in one Word document.
Access intermediate 2010 final project newclscott1
The document provides instructions for a final Access Intermediate project to modify an existing Vacation database for Griffin and Emma MacElroy's travel agency, GEM Ultimate Vacations. Students are asked to download the database, save it under a new name, and perform tasks like modifying data, creating queries to find specific property records and allow country parameter selection, designing a form to display guest and reservation records, creating a report to group properties by country and count reservations, and generating mailing labels for guests. The modified Access database file is to be submitted for grading.
Learn to manipulate numbers in R using the built in numeric functions. This tutorial is part of the Working With Data module of the R Programming course offered by r-squared.
This document provides an introduction to MATLAB by covering key topics like the command window, inputs and outputs, M files, and basic programming structures in MATLAB such as conditionals and loops. Some key points covered include how to enter and manipulate matrices in the command window, perform basic math operations, load and save data, plot graphs, write M files to organize commands and create functions, and use conditional statements and loops in M files.
The document discusses two-dimensional arrays in C++. It explains that a two-dimensional array is an array of arrays, with elements arranged in rows and columns. It provides examples of declaring, initializing, accessing, inputting, and passing two-dimensional arrays as parameters to functions. It also gives examples of functions that perform operations on two-dimensional arrays, such as addition, multiplication, finding row/column sums, diagonal sums, and transposing the array.
This document provides an overview and introduction to using the statistical software R. It outlines R's interface, workspace, help system, packages, input/output functions, and how to reuse results. It also discusses downloading and installing R, basic functions and syntax, data manipulation techniques like sorting and merging, creating graphs, and performing statistical analyses such as t-tests, regression, ANOVA, and multiple comparisons. The document recommends several tutorials that provide more in-depth information on using R for statistical modeling, data analysis, and graphics.
This document provides an example of running an R script from Excel to create plots. It describes setting up an Excel file with buttons to run an R script and open the resulting PDF. The R script generates random data, plots it, and saves the plots to a PDF. Clicking the first button runs the R script, passing cell values as arguments. Clicking the second button opens the PDF if it was created.
statistical computation using R- an intro..Kamarudheen KV
This presentation deals with some basics of R language. It is very useful for benners in R. It describes the basics in a very easy manner, so those who are not familiar with R it would be very helpful.
The document discusses arrays in C programming. It defines arrays as groups of same data types that can store integer, float, character, or other data. Arrays allow storing multiple values in a single variable and accessing elements using indexes. The document provides examples of one-dimensional and two-dimensional arrays, and using for loops to initialize, input, and output array elements. Nested for loops are described for traversing two-dimensional or multi-dimensional arrays like matrices.
The document discusses arrays in C programming. It defines arrays as groups of same data types that can store integer, float, character, or other data. Arrays allow storing multiple values in a single variable and accessing elements using indexes. The document provides examples of one-dimensional and two-dimensional arrays, and explains how to initialize, declare, and access array elements. It also discusses using for loops and nested loops to iterate through arrays.
This document provides an example of integrating R and Excel using the XLConnect package. It summarizes data in R, generates a graph, and writes the results to an Excel template, applying formatting. Key steps include: loading an Excel template, writing an R data frame and summary results to sheets, adding a pre-generated graph image, and saving the updated workbook.
This document provides an introduction and overview of the MATLAB programming environment and its core functionality. It describes how to perform basic operations and calculations, write scripts and functions, work with vectors and matrices, and use common plotting and programming commands. Key features covered include MATLAB's command-line interface, help system, variables, operators, functions, file types (m-files and function files), flow control, and short summaries of many common commands.
This document contains the questions from an examination on algorithms and data structures. Question 1 asks about asymptotic analysis and simplifying Big-O expressions. Question 2 involves analyzing and implementing an insertion sort algorithm. Question 3 covers queue implementation using a circular array. Question 4 is about linear search. Question 5 deals with binary search trees, including drawing a tree from insertions, traversing methods, defining a node structure, and finding the minimum value.
This document describes Assignment 3 for the CS193P class, which involves enhancing an MVC application that displays polygons. Students will create a custom view to draw the polygon shape based on a model class. They will also add functionality to save and restore the number of polygon sides using user defaults. The assignment tests that the application draws polygons correctly, updates dynamically, and preserves state as expected. Hints provide code to calculate polygon points given parameters.
The document provides 6 programming assignments involving functions, recursion, pointers, structures, and unions in C language. Assignment 1 asks to write a program to display a word descending in length using a function. Assignment 2 asks to solve an equation using recursion. Assignment 3 asks to solve an equation using pointers. Assignment 4 asks to get and display system details using a structure. Assignment 5 asks to call and display output from a function without arguments. Assignment 6 asks to get and display book details using a union containing structures.
Conversion from infix to prefix using stackHaqnawaz Ch
This document is a data structures assignment that contains two tasks:
1) Converting an infix expression to postfix notation using a stack. The example infix expression is converted to postfix as -+-AB*C+DE+FG.
2) Evaluating the postfix expression from the first task by assigning values to variables and using a stack to calculate the result, which is 33.
The slides I was using when delivering a meetup about the matplotlib library. More info about that meetup can be found at https://www.meetup.com/life-michael/events/271738271/
The document discusses various types of plots that can be created in MATLAB, including:
1. Standard two-dimensional plots created using the plot command, which connects data points with lines. Additional lines and graphs can be added to the same plot using hold on/off or the line command.
2. Plots with logarithmic axes created using semilogy, semilogx, and loglog for situations where data spans a wide range of values.
3. Formatted plots where elements like titles, labels, legends, grids can be added using various commands.
4. Specialized plots like bar plots, stem plots, and pie charts for different data visualization needs.
5. The ability to place
This document discusses Sterling Integrator, including what it is, its key features and benefits, and how it addresses common enterprise integration problems. It also describes the main user interfaces in Sterling Integrator: the administration interface, map editor, and graphical process modeler. Finally, it provides information on creating and running maps in Sterling Integrator, including the different types of maps, components used, data formats supported, and how to compile and run a map.
2GKS, Open GL and IGES_Video Lect Given by Renjin.pptxRamanathanSabesan
The document discusses various CAD standards including:
- Graphic Kernel System (GKS) which provides 2D and interactive graphic capabilities across devices. It defines graphic primitives like polylines, fill areas, and text.
- Open Graphics Library (OpenGL) which is a graphics standard for image exchange and defines geometric objects and how they are rendered.
- Data exchange standards like IGES, STEP, and DXF that allow transfer of CAD models between different systems in a neutral format, with IGES having drawbacks like not supporting solid geometry models.
Background This course is all about data visualization. However, we.docxrosemaryralphs52525
This document provides instructions for a two-part data visualization assignment using RStudio. For part 1, students will analyze a unique dataset by exploring its structure, calculating summary statistics, and visualizing correlations. Screenshots of the analysis must be provided. For part 2, students will create various visualizations of the data, including pie charts, bar plots, histograms, box plots, and scatter plots. Screenshots of the visualizations must be submitted along with an APA style cover page in one Word document.
This document provides an overview of ABAP programming and covers several key concepts:
- It outlines the chapters of an ABAP course, including list processing, Open SQL, event-driven programming, and modularization.
- It introduces ABAP, describing it as an advanced business application programming language that is operating system independent.
- It explains some fundamental ABAP concepts like data objects, variables, data types, structures, constants, and system fields. It also demonstrates how to define and assign values to variables and structures.
This document provides an introduction to using R and RStudio. It discusses installing R and RStudio, the four windows in RStudio (source editor, console, environment/history, and plots/files), and basic commands and functions for running code, saving scripts, clearing the screen, commenting lines, and getting help. It also covers creating and manipulating variables and vectors, importing and exporting data, generating basic plots like bar plots, pie charts and histograms, and importing/exporting data.
The document outlines new features and updates in version 3.1.0 of amCharts including:
1) Fixes for Firefox error messages about style declarations and an issue with the maxWidth property of AmBalloon.
2) Charts now support patterns to fill bars, lines, and slices with images and can simulate hand drawn charts.
3) Minor bugs were fixed.
I am Boris M. I am a Computer Science Assignment Help Expert at programminghomeworkhelp.com. I hold MSc. in Programming, McGill University, Canada. I have been helping students with their homework for the past 7 years. I solve assignments related to Computer Science.
Visit programminghomeworkhelp.com or email [email protected] can also call on +1 678 648 4277 for any assistance with Computer Science assignments.
This document provides an overview of strings and decimal data types in Microsoft Visual Basic 2005. It discusses declaring string variables, assigning text to strings, and concatenating strings. It also covers the single, double, and decimal numeric data types. Additionally, it explains how to use the Format function to format numeric values and the Enabled property to enable or disable controls. The SelectionStart and SelectionLength properties are described for selecting text in text boxes.
This document provides an introduction and overview of key functions and capabilities in MATLAB. It describes how to perform basic operations and calculations, use plotting and programming features, work with vectors and matrices, and utilize common MATLAB functions. Key points covered include how to get help, change directories, clear variables, perform calculations, create scripts and functions, use flow control, plot data, index vectors and matrices, and more.
This document contains questions for an examination on Object Oriented Modeling and Design. It has two parts - Part A and Part B. Part A focuses on concepts related to UML, class modeling, associations, events, sequence diagrams and software development process. Part B focuses on use case modeling, class design, design patterns, and advanced OO concepts like templates and styles. The document provides guidelines for answering questions and allocates marks for each question.
This document contains questions for an examination on Object Oriented Modeling and Design. It has two parts - Part A and Part B. Part A focuses on concepts related to UML, class modeling, associations, events, sequence diagrams and software development process. Part B focuses on use case modeling, class design, design patterns, and advanced OO concepts like templates and styles. The document provides guidelines for answering questions and allocates marks for each question.
This document contains questions for an examination on Object Oriented Modeling and Design. It has two parts - Part A and Part B. Part A focuses on concepts related to UML, class diagrams, associations, metamodels, events, sequence diagrams, activity diagrams etc. It also covers software development process. Part B focuses on use case diagrams, class models, advanced use case relationships, class design, patterns etc. Students are required to answer 5 out of the 8 questions, selecting at least 2 from each part.
Here is The code in C language:
/*------------------------------------------------------------------
File: plotFunctions.c
Author: Gilbert Arbez, Fall 2016
Description: Allows the user to plot a number of functions for
different ranges.
---------------------------------------------------------------------*/
#include <stdio.h>
#include <gng1106plplot.h> // provides definitions for using PLplot library
#include <math.h>
#include <float.h>
// Some definitions
#define NUM_POINTS 500 // Number of points used for plotting
#define X_IX 0 // Row index for storing x values
#define FX_IX 1 // Row index for storing f(x) values
#define TRUE 1
#define FALSE 0
// Structure for user input
typedef struct
{
int fNumber; // function number
double x0; // first value of x to plot
double xf; // final value of x to plot
} F_SELECT;
// function prototypes
void selectFunction(F_SELECT *);
void computeDataPoints(F_SELECT *fsPtr, int n, double [][n]);
double calcFx(double, int);
void plot(int n, double [][n]);
double getMinDouble(double [], int);
double getMaxDouble(double [], int);
/*---------------------------------------------------------------------
Function: main
Description: This function computes a set of points for plotting. The
function calcFx is called to computes the value of f(x) .
Modify calcFx to compute the values of f(x) desired.
In this template, the sin function is used.
------------------------------------------------------------------------*/
void main(void)
{
// Variable declarations
F_SELECT fselect;
double points[2][NUM_POINTS]; // row 0 contains values of x
// Get user input
selectFunction(&fselect);
// Compute the data points and save in array
computeDataPoints(&fselect, NUM_POINTS, points);
// Call plot function to plot
plot(NUM_POINTS, points);
}
/*-----------------------------------------------------------------------
Function: selectFunction
Parameters:
sfPtr - Pointer to F_SELECT structure variable to store input data.
Description: Prompts the user to get x0 and xf (range of x for plotting)
and to select a function to plot.
------------------------------------------------------------------------*/
void selectFunction(F_SELECT *sfPtr)
{
// Variable Declarations
int flag;
// Display function menu
printf("1) f(x) = sqrt(|x-1|) + 1n");
printf("2) f(x) = exp(-x)n");
printf("3) f(x) = sqrt(x^2+1) - xn");
printf("4) f(x) = [exp(-x) - 1)]/xn");
printf("5) f(x) = sin(x)+0.1*cos(10.0*x)n");
// Select a function
// Select a range of x for plotting
}
/*-----------------------------------------------------------------------
Function: computeDataPoints
Parameters:
fsPtr - Pointer to F_SELECT structure variable with input data.
n - number of points in the 2D array (i.e. number of columns)
points - 2D array that contains the data points - row X_IX with x values
and row FX_IX with the f(x) values.
Description: Calculates NUM_POINTS points of the function f(x) (selected by the
the user and computed with calcFx), and stored in the
2D array points. points[X_.
The document provides an overview of ABAP (Advanced Business Application Programming) programming. It outlines the structure of an ABAP course including chapters on list processing, open SQL, event-driven programming, modularization, and debugging. It also describes the basic features and structure of the ABAP language, including data objects, control statements, and event handling.
The document provides an overview of ABAP (Advanced Business Application Programming) programming. It discusses the structure of ABAP programs, data objects, basic statements and features. The key topics covered are:
1. The structure of ABAP programs including reports, dialog programs, and transactions.
2. Data objects in ABAP such as variables, structures, internal tables, and field symbols.
3. Basic statements for data manipulation like MOVE, WRITE, and IF.
4. Features of ABAP such as its independence from operating systems and integrated SQL functionality.
The document provides an overview of ABAP (Advanced Business Application Programming) programming. It outlines the structure of an ABAP course including chapters on list processing, open SQL, event-driven programming, modularization, and debugging. It also describes the basic concepts of ABAP including data types, variables, structures, constants, and system fields.
The document provides an overview of ABAP (Advanced Business Application Programming) programming. It outlines the structure of an ABAP course including chapters on list processing, open SQL, event-driven programming, modularization, and debugging. It also describes the basic concepts of ABAP including data types, variables, structures, constants, system fields and statements like MOVE, CLEAR and FIELD-SYMBOLS.
The document provides an overview of ABAP (Advanced Business Application Programming) programming. It discusses the structure of ABAP programs, data objects, predefined data types, and other key concepts like structures, constants, system fields, MOVE statement, and CLEAR statement. The outline includes 6 chapters that cover topics like introduction to ABAP, list processing, open SQL, event-driven programming, modularization, and debugging techniques.
A comprehensive introduction to handling date and time data in R. Get an introduction to date and time manipulation in R. Learn to create, transform, extract and operate on date/time objects.
This document provides information about association rule mining on market basket analysis data. It discusses connecting with the company on various platforms, accessing resources like slides and code, and the key concepts of association rule mining including what it is, why it is used, how it works, and example use cases. It then demonstrates the process of generating, inspecting, and filtering rules from transaction data to understand common purchases and influence of products. Top rules are examined by support, confidence, and lift. Association rule mining can uncover frequently bought item sets and has applications in retail and other industries.
This document summarizes information about the governors of the Reserve Bank of India (RBI) by extracting a table from the Wikipedia page on the topic. It lists the 15 governors of the RBI in order from longest to shortest terms in office. It also analyzes the backgrounds of the governors, finding that most were economists (7) or bureaucrats from the IAS or ICS (7), with some also having a banking background (2) or being a career RBI officer (1).
Learn the grammar of data manipulation using dplyr. You will work through a case study to explore the dplyr verbs such as filter, select, mutate, arrange, summarize, group_by etc.
Learn to write readable code with pipes using the magrittr package. You will learn about the forward operator (%>%), exposition operator (%$%) and the assignment operator (%<>%).
tibbles are an alternative for dataframes. You will learn how tibbles are different from dataframes, why you should use them, how to create and modify them.
Read/Import data from flat/delimited files into RRsquared Academy
This document provides examples of using the readr package in R to read data from CSV files. It demonstrates how to handle column names, skip text lines, specify column types as numeric, integer or factor, and read specific columns. Functions used include read_csv(), read_delim(), spec_csv(), and arguments like col_names, skip, col_types, and cols_only to control reading of columns.
Learn how to install & update R packages from CRAN, GitHub, Bioconductor etc. You wlll also learn to install specific versions of a package from CRAN or GitHub.
A brief introduction to the R ecosystem for absolute beginners. You will learn about the history and capabilities of R as a modern language for data science.
In this tutorial, we learn to access MySQL database from R using the RMySQL package. The tutorial covers everything from creating tables, appending data to removing tables from the database.
This document provides an introduction to R Markdown. It explains that R Markdown combines Markdown syntax and R code chunks to create dynamic reports and documents. The document outlines the key topics that will be covered, including what Markdown and R Markdown are, Markdown syntax like headers, emphasis, lists, links and images, R code chunks and options, and RStudio settings. Resources for learning more about Markdown, R Markdown, and related tools are provided.
In this tutorial, we explore the most basic data structure in R, the vector. We cover everything from creating vectors to subsetting them in different ways.
In this tutorial, we learn to create variables in R. Followed by that, we explore the different data types including numeric, integer, character, logical and date/time.
Learn the built-in mathematical functions in R. This tutorial is part of the Working With Data module of the R Programming course offered by r-squared.
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Just-in-time: Repetitive production system in which processing and movement of materials and goods occur just as they are needed, usually in small batches
JIT is characteristic of lean production systems
JIT operates with very little “fat”
Dimension Data has over 30,000 employees in nine operating regions spread over all continents. They provide services from infrastructure sales to IT outsourcing for multinationals. As the Global Process Owner at Dimension Data, Jan Vermeulen is responsible for the standardization of the global IT services processes.
Jan shares his journey of establishing process mining as a methodology to improve process performance and compliance, to grow their business, and to increase the value in their operations. These three pillars form the foundation of Dimension Data's business case for process mining.
Jan shows examples from each of the three pillars and shares what he learned on the way. The growth pillar is particularly new and interesting, because Dimension Data was able to compete in a RfP process for a new customer by providing a customized offer after analyzing the customer's data with process mining.
Mieke Jans is a Manager at Deloitte Analytics Belgium. She learned about process mining from her PhD supervisor while she was collaborating with a large SAP-using company for her dissertation.
Mieke extended her research topic to investigate the data availability of process mining data in SAP and the new analysis possibilities that emerge from it. It took her 8-9 months to find the right data and prepare it for her process mining analysis. She needed insights from both process owners and IT experts. For example, one person knew exactly how the procurement process took place at the front end of SAP, and another person helped her with the structure of the SAP-tables. She then combined the knowledge of these different persons.
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Bram Vanschoenwinkel is a Business Architect at AE. Bram first heard about process mining in 2008 or 2009, when he was searching for new techniques with a quantitative approach to process analysis. By now he has completed several projects in payroll accounting, public administration, and postal services.
The discovered AS IS process models are based on facts rather than opinions and, therefore, serve as the ideal starting point for change. Bram uses process mining not as a standalone technique but complementary and in combination with other techniques to focus on what is really important: Actually improving the process.
3. dataCrunchFont
Slide 3
The font argument can be used along with main, sub, axis and lab arguments to specify the font of
the title, subtitle, axes and the labels.
Feature Argument
Title font.main
Subtitle font.sub
Axis font.axis
Labels font.lab
The font argument takes values from 1 - 5. The font type represented by each value is shown in the
above table.
Value Font Type
1 Plain
2 Bold
3 Italic
4 Bold Italic
5 Symbol
4. dataCrunchFont: Title
Slide 4
# modify the font of the title
plot(mtcars$disp, mtcars$mpg,
main = "Displacement vs Miles Per Gallon",
font.main = 1)
Description
The font of the title can be modified using the font.
main argument in the plot() function.
Code
6. dataCrunchFont: Subtitle
Slide 6
# modify the font of the subtitle
plot(mtcars$disp, mtcars$mpg,
sub= "Displacement vs Miles Per Gallon",
font.sub = 3)
Description
The font of the subtitle can be modified using the
font.sub argument in the plot() function.
Code
8. dataCrunchFont: Axis
Slide 8
# modify the font of the axis
plot(mtcars$disp, mtcars$mpg,
font.axis = 3)
Description
The font of the axis can be modified using the
font.axis argument in the plot() function.
Code
10. dataCrunchFont: Labels
Slide 10
# modify the font of the labels
plot(mtcars$disp, mtcars$mpg,
xlab = "Displacement",
ylab = "Miles Per Gallon",
font.lab = 3)
Description
The font of the labels can be modified using the
font.lab argument in the plot() function.
Code
13. dataCrunchFont Size
Slide 13
The cex argument can be used along with main, sub, axis and lab arguments to specify the font size
of the title, subtitle, axes and the labels.
Feature Argument
Title cex.main
Subtitle cex.sub
Axis cex.axis
Labels cex.lab
The values taken by the cex argument are relative to 1 i.e the default size is represented by 1 and if
the supplied value is less than 1, the size of the font will be relatively smaller, and if the supplied value
is greater than 1, the size of the font will be relatively bigger.
14. dataCrunchFont Size: Title
Slide 14
# modify the font size of the title
plot(mtcars$disp, mtcars$mpg,
main = "Scatter Plot",
cex.main = 1.5)
Description
The font size of the title can be modified using the
cex.main argument in the plot() function.
Code
15. dataCrunchFont Size: Title
Slide 15
The below plot depicts the appearance of the title when different options for font size are applied:
16. dataCrunchFont Size: Subtitle
Slide 16
# modify the font size of the subtitle
plot(mtcars$disp, mtcars$mpg,
sub= "Scatter Plot",
cex.sub = 1.5)
Description
The font size of the subtitle can be modified using
the cex.sub argument in the plot() function.
Code
18. dataCrunchFont Size: Axis
Slide 18
# modify the font size of the axis
plot(mtcars$disp, mtcars$mpg,
cex.axis = 1.5)
Description
The font size of the axis can be modified using the
cex.axis argument in the plot() function.
Code
19. dataCrunchFont Size: Axis
Slide 19
The below plot depicts the appearance of the axis when different options for font size are applied:
20. dataCrunchFont Size: Labels
Slide 20
# modify the font size of the labels
plot(mtcars$disp, mtcars$mpg,
xlab = "Displacement",
ylab = "Miles Per Gallon",
cex.lab = 1.5)
Description
The font size of the labels can be modified using the
cex.lab argument in the plot() function.
Code
21. dataCrunchFont Size: Labels
Slide 21
The below plot depicts the appearance of the subtitle when different options for font size are applied:
22. dataCrunch
Slide 22
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