I am currently a graduate student at Northeastern University, Boston pursuing Master’s degree in Computer Science with a current GPA of 3.5. I am passionate about technology, owing to my undergraduate degree in Information Science from Bangalore Institute of Technology, India and my work experience as a Systems Engineer of over 2.5 years at a leading global consulting company, TATA Consultancy Services (TCS).
I am actively seeking co-op opportunities which will enable me to obtain real life experience of the theoretical concepts learnt during my Graduate education and to contribute the best of my technical and inter-personal skills towards the growth of the organisation during the co-op period.
Northeastern University, Boston, MA (Sep 2015 - Present)
College of Computer and Information Science (Expected Graduation: Aug 2017)
GPA 3.5/4
Related Coursework: Programming Design Paradigm, Artificial Intelligence, Web Development, Algorithms, Computer Systems, Fundamentals of Computer Network.
Bangalore Institute of Technology, Bangalore, India (Sept 2008 - Apr 2013)
Visvesvaraya Technological University
GPA 7.2/10
Related Coursework: C/C++, C#, .NET, Web Designing, DBMS, Algorithms, Computer Graphics, Java,
Unix Programming, Object Oriented Programming, Operating Systems, Networks.
Northeastern Univeristy, Boston, MA
Cogitas Consulting LLC, Boston, MA
Northeastern Univeristy, Boston, MA
TATA Consultancy Services, Bangalore, India
TCS BaNCS Anti Money Laundering (AML) Product:
TCS BaNCS FATCA Compliance Product:
The Form Maker web application consists of a Website that allow users to create forms and share them on the Web as single pages or embedded in their own Web pages.
The Web application is built on the MEAN stack using the four underpinning technologies MongoDB, Express, AngularJS, and Node.js.
Prismatic Music is a web application that allow users to search music based on track, artist or album name.
The Web application is built on the MEAN stack using the four underpinning technologies MongoDB, Express, AngularJS, and Node.js.
Experiment to test the Last.fm API.
Experiment to test the YouTube API.
Email:
<EMAIL_ADDRESS>Address:
116 Hemenway Street,
Apt #2E,
Boston, MA 02115, USA
Phone:
+1-(617)-785-6379
Connect with me on:


Toggle navigation
My Company
Data
Welcome to My Company!
Here, you will find some statistics about My Company's data.
Charge points: Providers
Charge points: Location


C:/Users/Simmy56/Documents/GitHub/DanSimonet.github.io
You will need the following for this workshop
tidyverse
, psych
, afex
tidyverse
), Cars93 (in MASS
), ChickWeight (base R), and NAPS.xls.If you’re like most people, you think of R as a statistics program. However, while R is definitely the coolest way to conduct statistics – it’s not really a program. Rather, it’s a programming language written by and for statisticians. In this first section, we will navigate the RStudio interface while discussing some basics of the R language. We will also assemble R code which simulates rolling a pair of dice to get familiar with running R commands, creating objects, and using packages.
Beyond its wide use and popularity, here are numerous reasons to adopt R.
R is 100% free and as a result, has a huge support community. Unlike SPSS, Matlab, Excel and JMP, R is, and always will be completely free. This doesn’t just help your wallet - it means that a huge community of R programmers will constantly develop an distribute new R functionality and packages at a speed that leaves all those other packages in the dust! The size of the R programming community is staggering. If you ever have a question about how to implement something in R, a quick Google search will lead you to your answer virtually every single time.
R is the present, and future of statistical programming. Next to Python, it is ranked as the most in demand languages for data scientists and academics. This virtually guarantees its continued usage for the forseeable future.
R is incredibly versatile. You can use R to do everything from calculating simple summary statistics, to performing complex simulations to creating gorgeous plots. If you can imagine an analytical task, you can almost certainly implement it in R. Below are links to pages or packages illustrating application of R to dyadic data analyses, SEM, networks, polynomial regression, genetic sequencing, and creation of a variety of figures.
Using RStudio, a program to help you write R code, allows you to seamlessly combine R code, analyses, plots, and written text into elegant documents all in one place using Sweave (R and Latex) or RMarkdown. In fact, I translated this entire seminar (the text, formatting, plots, code…yes, everything) in RStudio using Markdown. With RStudio and RMarkdown, instead of trying to manage two or three programs, say Excel, Word and (sigh) SPSS, where you find yourself spending half your time copying, pasting and formatting data, images and test, you can do everything in one place so nothing gets misread, mistyped, or forgotten. I can even make this cool figure right next to my text.
circlize::chordDiagram(matrix(sample(10),
nrow = 2, ncol = 5))
R is very much like a relationship. Like relationships, there are two major truths to R programming
1. There is nothing more frustrating than when your code does not work
Anything worth doing, from losing weight to publishing a paper, takes time. Learning R is no different. Especially if this is your first experience programming, you are going to experience a lot of headaches when you get started. You will run into error after error and pound your fists against the table screaming: “WHY ISN’T MY CODE WORKING?!?!?  You will spend hours trying to find a bug in your code, only to find that - frustratingly enough, you had had an extra space or missed a comma somewhere. You’ll then wonder why you ever decided to learn R when (sigh) SPSS was so “nice and easy.”
Programming is learning a language, one of speaking to a computer. You get better by doing, speaking, and thinking about how the computer is understanding your code. Code itself has verbs, nouns, and syntax which must be mastered bit by bit. It’s really easy in SPSS and other progrms to learn things by clicking a button (e.g., the ANOVA button). This is like learning survival phrases as opposed to actually speaking a language. It will get you to a certain point but you will eventually hit a wall.
Writing implies you just put it down and its done. You should not think of writing code as a task be finished and forgotten. Rather, it is a developmental process in the same way a project or research paper is developmental. You don’t just write one draft and say I’m done. You go back, review words and paragraphs, and modify things so they sound better. That same basic process occurs in programming on a much finer level. You instead write one or two lines of code at a time, run them, make sure they do what you think, and keep moving. Then you build iteratively one step at a time.
A big part of this is experimentation. Probably the best way to intuitively grasp R is to take others’ code and modify it for your data. Alter arguments or variables and see the result. Even better, alter the code until it breaks. Then, understand why it broke and fix it.
Because a lot of R work with functions, you will often want to run each function by itself on some data to see what happens. To do so, always build test code with made-up data. Once you get a feel for one function, then you can nest it inside other functions to build increasingly complex lines of code. Conversely, when you find nested functions in the wild, it is often helpful to unpack each function and run each by itself to see what it does. In the following image, we might run the mean first to see the result, then run round to see the result.
As you get more fluent in R, you should transition to the idea you can do everything in R from data cleaning, to table creation, to writing your actual manuscript. Eventually, you will want to have one R script which can take your 100% raw data - directly downloaded from excel, Qualtrics, archival data set, or other format - and transorm it into final tables, figures, and text embedded in a document. It should also be portable, meaning you could add a different data-set, repeat the code, and end up with new tables and text.
R is a statistical programming language. Rstudio is an integrated development environment or IDE for R. It is important to note the difference. R is the base language or “engine” running code while Rstudio is a front-end or “hood” to make R easier to use. In R, you can run many statistical techniques, manipulations, and visualizations. Rstudio, on the other hand, provides a kind of graphical user interface for R by adding interactivity, organization, and greater functionality, such as syntax-hilghlighting editor, plot area for showing graphs, and a work space for viewing loaded data.
If you open R directly, you will see a plain old console.
You can run all statistical and graphical functionality within base R. For instance, I can create and plot two numerical vectors, x and y.
x <- 1:5
y <- 6:10
plot(x,y)
Running the above creates a plot within the R console. If wanting to retrieve x
and y
from R’s working memory you need to run the ls()
command. This will display the contents of the current R environment. Finally, you can see base R has menu options but they are fairly limited.
Now let’s compare with R studio. When opened, you see four panels with the R console located in the bottom left. The console is the same R engine we ran before – you can do all the same stuff here.
Let’s enter and plot the same two vectors in the R console. Notice a few changes. First, we can directly see what’s in R’s working memory in the upper right. Second, all plots are self-contained in the bottom right window, with R studio tracking all images created in a single session.
If you want to save a plot, you can click on the export tab, save as an image, and make modifications to the format and dimensions prior to saving.
Importing data also becomes easier. While you can still import data using commands like read.table
, you can also import data using the import dataset tab in the uppper right. We can select from a local file — meaning it’s saved on your computer — and then use the options available to modify how the data is imported. Below we are selecting the NAPS excel dataset. Rstudio also provides a preview of how the data will be formatted once loaded into R.
Once we import the NAPS dataset, you’ll see it pop up in a tab within the script editor in the upper left. This shows the data in a spreadhseet format similiar to SPSS or excel. You can also sort the data by any variable from highest to lowest or vice versa.
We can also easily create and manage scripts, which are just plain text files with R code. File > New File > R Script in the menu will create an untitled script. Let’s do this. In the script, create a new variable, z
, and assign the values 11 to 15. Then add up x, y, and z using the sum
command. The output appears in the console. You can save this script as a .R file under File > Save As which allows you to reproduce your analyses at a later date.
RStudio also directly interfaces with RMarkdown which allows you to turn your code and analyses directly into reports, presentations, and dashboards. Similarly, you can use Rprojects to organize your work by placing all related files and output for a single paper in one spot.
The point of the above is to show RStudio makes the user experience of working within the R programming language much much nicer! It’s a no-brainer: if you’re going to work with the R programming language work within the RStudio environment. You’ll be happy that you did.
R is a programming language rather than a collection of discrete commands. Because of this, you can combine several commands, each using the output of the previous one (Linux users will recognize the similarity to chaining shell commands using pipes). The ability to combine R functions gives tremendous flexibility and, if used properly, is quite powerful. As a simple example, consider this nested command:
nrow(subset(mtcars, cyl == 6))
## [1] 7
First, the subset
functions takes the built-in R dataframe mtcars
and extracts all vehicles for which the variable cylinder has the value of 6. This results in a new, smaller data frame, which is then fed to the nrow
function. This function counts the number of rows in a frame. The net effect is to report a count of cyl = 7 in the original frame.
At a very broad level, commands in R are generally made of two parts: objects and functions. These are separated by the assignment operator ‘<-’ (pronounced get) symbol, which you can think of as meaning ‘is created from.’ As such, the general form of a command is:
Object <- Function
This means an ‘object is created from function’. An object is anything created in R. It could be a variable, collection of variables, statistical model, graph, different operations, etc. Objects can be single values (such as the mean of a set of scores) or collections of information; for example, when you run an analysis, you create an object containing the output of that analysis, which means the object contains many different values and variables. Functions are procedures that typically take one or more objects as arguments (i.e., inputs), does something to these objects, and then returns a new object. Calculating the mean, running an ANOVA, generating a histogram, or importing data are functions which return new objects or output.
In the following code chunk, I’ll define a simple object heights
made up of 6 height measures using a function ‘c()’ and then calculate the mean
of this object. The concatenate
or c()
function is first used to group all these numbers together into a single entity or vector which is then assigned the label heights
. The mean()
function, in turn, takes a vector object of numeric data, like heights
, as its argument, calculates the arithmetic mean of those data, then returns a single number (a scalar) as a result.
#1: Create a vector object called heights
heights <- c(5.8, 6.7, 5.2, 5.6, 4.6, 5.9)
#2: Apply the mean() function to the heights object
mean(heights)
## [1] 5.633333
If we type the commands above into the console and hit return, then object heights
is created. This object is stored in memory so we can print it to the console or refer to it in future commands.
R also works well with text data, which can similarly be bound together in an object. Below we create an object called Presidents made up of the names of four notable US Presidents. We again use c()
to group the four names into a single object, surround each name by quotes to indicate each value is a character or string, and then assigned the label ‘Presidents’.
Presidents <- c("George Washington", "Thomas Jefferson",
"Theodore Roosevelt", "Franklin D. Roosevelt")
Again, we can view all four names by entering President
into the console. Or, perhaps we wish to use the str_subset
function from the stringr
package to pull out any President with a name containing the letter R.
stringr::str_subset(Presidents, "R")
## [1] "Theodore Roosevelt" "Franklin D. Roosevelt"
As can be seen, R is an object-oriented language. This means variables, datasets, graphs, and programs are represented as in R’s memory and directly manipulated. Hence, we might represent the number 7 as x
, 8 as y
, and then add x + y
to produce 15.
The advantage of object orientation can be explained by an example. Consider statistical regression. When you perform a regression analysis with other statistical packages, such as SAS or SPSS, you get a mountain of output on the screen. By contrast, if you call the lm
regression function in R, the function returns an object containing all the results – the estimate coefficients, their standard errors, residuals, and so on. You then pick and choose, programmatically, which parts of that object to extract.
For instance, we may desire to regress miles per gallon upon vehicle weight using R’s built-in mtcars
dataset. We will store the results of this analysis in the object cargas
cargas <- lm(mpg ~ wt, mtcars)
We can view all the information stored within this object using the attributes
function. R recognizes this as a class from lm
and provides everything stored in this object under the names attribute.
attributes(cargas)
## $names
## [1] "coefficients" "residuals" "effects" "rank"
## [5] "fitted.values" "assign" "qr" "df.residual"
## [9] "xlevels" "call" "terms" "model"
##
## $class
## [1] "lm"
We can access this output directly using the $
sign, request a summary
of the model, or feed the object into the plot
function. For instance, we might just want the model coefficients and predicted mpg for the first four vehicles.
cargas$coefficients; cargas$fitted.values[1:4]
## (Intercept) wt
## 37.285126 -5.344472
## Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
## 23.28261 21.91977 24.88595 20.10265
You will see that R’s approach makes programming much easier, partly because it offers a certain uniformity of access to data. This uniformity stems from the fact that R is polymorphic, which means that a single function can be applied to different types of inputs, which the function processes in the appropriate way. Such a function is called a generic function (If you are a C++ programmer, you have seen a similar concept in virtual functions).
For instance, consider the plot
function. If you apply it to a list of numbers, you get a simple plot. But if you apply it to the output of a regression analysis, you get a set of plots representing various aspects of the analysis. Indeed, you can use the plot
function on just about any object produced by R. This is nice, since it means that you, as a user, have fewer commands to remember!
Insert Content
This section adapts the structure and examples from Garret Grolemund’s excellent Hands on Programming with R to provide a broad overview of the R language. We will build a pair of virtual dice you can roll to generate random numbers.
In general, a die has six possible values: 1, 2, 3, 4, 5, and 6. Each time it is rolled it will return one of these numbers. You could capture the essence of a dice by saving the numbers 1 to 6 as a group of values, or a single object, into R’s memory. Let’s first work on saving these numbers and then consider a function which allows us to “roll” the dice. We will introduce each pane of R studio along the way.
Before you can ask your computer to save some numbers, you’ll need to know how to talk to it. That’s where R and RStudio come in. RStudio gives you a way to talk to your computer. R gives you a language to speak in. To get started, open RStudio just as you would open any other application on your computer. You should see three or four panes (the script file or source pane may be minimized) like those displayed below. If you’d like, you can change the order under Tools > Global Options > Pane Layout. You can also change their shape by either clicking the minimize or maximize buttons on the top right of each panel, or by clicking and dragging the middle of the borders of the windows.
You can quickly switch between the source and consoles using Ctrl (or Command on a Mac) and a number corresponding to the desired pane. The two you will be jumping between most frequently are Source Editor (1; labeled Script Files above) and Console (2). Other preset windows are Help (3), History (4), Plots (5), and Environment (8). By adding Shift to any of these combinations you can also toggle maximize pane for the one you are switching to at the same time, very handy if you need a broader perspective. You can hit Ctrl+Shift+Alt+0 to revert back to displaying all four panes.
RStudio offers many handy keyboard shortcuts which can greatly accelerate your workflow. Alt+Shift+K brings up a keyboard shortcut reference card. Here is a list of my favorite which I frequently use and will reference later:
| Function | Key |
|---|---|
| Run lines of code | Ctrl + Enter |
| Highlight multiple lines of code | Shift + Up/Down |
| Delete current line/selection | Ctrl + D |
| Move lines of code up and down (rather than cut/paste) | Alt + Up/Down |
| Insert an R Section | Ctrl + Shift + R |
| Collapse/Open R sections (also other types of sections) | Alt + L/Alt + Shift + L |
| Run current R section | Ctrl + Alt + T |
| Run whole script | Ctrl + Alt + R |
| Comment out code by inserting a hashtag (#) | Ctrl + Shift + C |
| Re-run previously run code region with any changes | Ctrl + Shift + P |
| Automatic indentation of code | Ctrl + I |
| Insert assignment operator (<-) | Alt + (-) |
| Switch back and forth between tabs | Ctrl + Tab/Ctrl + Shift + Tab |
| Search through open tabs | Ctrl + Shift + . |
| In console, visually search previously executed commands | Ctrl + Up |
| Clear console | Ctrl + L |
The bottom left pane is the R Console, or the heart of R. This is where code is evaluated and results returned. At the beginning of the console you’ll see the > character, a prompt indicating R is ready for new code. Simply type code into the console and hit Enter to run it. The code you type is called a command, because it will command your computer to do something.
When you run a command, the computer executes it and shows the results. Then RStudio displays a fresh prompt for your next command. For example, if you type 1 + 1
and hit Enter, RStudio will display:
> 1 + 1
[1] 2
You’ll notice a [1]
appears next to your result. This means the line begins with the first value in your result. Some commands return more than one value, and their results may fill up multiple lines. For example, the command 10:30
returns 20 values; it creates a sequence of integers from 10 to 30. Notice new bracketed values appear at the start of new lines. These numbers indicate the position or index of the value within the object. Consider the following example:
# > 10:30
# [1] 10 11 12 13 14 15 16 17 18
# [10] 19 20 21 22 23 24 25 26 27
# [19] 28 29 30
Here R counts 19 as the 10th value in the vector and 28 as the 19th. At the beginning of every line, R tells you the index of the first value in that line. We will return to indexing later.
If you type an incomplete command and press Enter, R will display a +
prompt, which means R is waiting for you to type the rest of your command. Either finish the command or hit Escape to start over:
# > 5 -
# +
# + 1
# [1] 4
If you type a command R doesn’t recognize, R will return an error message. If you ever see an error message, don’t panic. R is just telling you it couldn’t understand or do what you asked. Errors are often a good time to pause, diagnose, and think about why problems are arising in your code.
5 * abc
Once you get the hang of the command line, you can easily do anything in R that you would do with a calculator. For example, you could do some basic arithmetic.
3 * 10
## [1] 30
6 / (4 - 1)
## [1] 2
sqrt(20)^2
## [1] 20
Further mathematical operations include:
+
-
*
/
^
%%
The ^
operator raises the number to its left to the power of the number to its right: for example 3^2
is 9
. The modulo returns the remainder of the division of the number to the left by the number on its right, for example 5 modulo 3 or 5 %% 3
is 2.
 If so, try carrying out the following calculations. If you do it correctly, you should end up with the same number you started with.
You could start with the number 99, and then do the following steps:
99 + 2
## [1] 101
101 * 3
## [1] 303
303 - 6
## [1] 297
297/3
## [1] 99
Or, you could run as follows
(((99+2)*3) - 6)/3
## [1] 99
The upper right pane is R’s working memory. It displays objects (data, values, functions) in the environment pane while the history window shows all executed commands during the current session. We will first discuss objects and then commands for working with your R environment.
Now that we know how to use R, let’s use it to make a virtual die. The :
operator from above gives a nice way to a create a group of numbers in a sequence. The :
operator returns its results as a vector, a one-dimensional set of numbers.
1:6
## [1] 1 2 3 4 5 6
This is what a virtual dice looks like! But, where does this information go? Running 1:6
generated the numbers, but it did not store the vector anywhere in your computer’s memory. If you want to re-use those (or other) numbers again, you’ll have to ask your computer to save them somewhere. You can do that by creating an R object.
 What is an object? Just a name that you can use to call up stored data. For example, you can save data into an object like a
or b
using the assignment operator <-
. Whenever you apply the object, R will replace it with the data saved inside. For example
a <- 1
a + 2
## [1] 3
Note you can also change a variable’s value by assining it a new one
a <- 11
a + 2
## [1] 13
This means assigning a value to one variable does not change values of other variables. For example, let’s store the result of a
plus 100 in another variable
b <- a + 100
and then change a
to 0.
a <- 0
What do you think the current content of objec b
is, 100 or 111? Try it out and see.
Without using R, what are the values of the following? After solved, check your answer in R.
mass <- 50 # mass?
age <- 30 # age?
mass <- mass * 2 # mass?
age <- age - 10 # age?
mass_index <- mass/age # massIndex?
You will makes lots of assignments and the <-
operator can be a pain to type. Instead, use RStudio’s keyboard shortcut: Alt+- (the minus sign). Object names cannot start with a digit or contain certain other characters such as a comma or a space. So, for another example, the following code would create an object named die
that contains the numbers one through six. To see what is stored in an object, just type the object’s name by itself:
die <- 1:6
die
## [1] 1 2 3 4 5 6
When creating objects, it is wise to provide informative names and adopt a convention for demcarcating words in names. Let’s make another assignment.
this_is_a_really_long_name <- 2.5
To inspect this, try out RStudio’s completion facility: type the first few characters, press Tab, add characters until you disambiguate, then press Return. This auto-completion comes in handy when there are many objects and datasets you need to reference. This feature also provides brief inline help for functions. For example, type mean()
and press the Tab key to acess the arguments.
Make another assignment.
katherine_rocks <- 2 ^ 3
Note R is very precise in labels. Let’s inspect the object
katherinerocks
Katherine_rocks
The implicit deal you make with a computer: it will do tedious computations for you but, in return, you must be exact in your instructions. Typos matter. Case matters. Missing commas matter. Get better at typing.
Often you may want to re-excute commands previously entered. Rather then type it out, the console can recall previous commands using the arrow keys:
You can view an entire list of your recent commands by pressing Ctrl+Up on Windows (or Command+Up on Mac).
It is important to remember everything in R — including datasets, output, and functions — are stored as objects. For example, we can store R’s built-in dataset about cars as a new object.
car_data <- mtcars
head(car_data)
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
The Environment pane shows the names of all data objects (like vectors, dataframes, matrices) that you’ve defined in your current R session. My current environment includes all the objects created above.
You can also see object information, like the number of observations and rows in datasets. I have expanded the car_data
object by clicking on the blue arrow. This shows the dataset’s variables. The pane has additional tabs for data importation, connecting to external servers or databases, and working with version control.
You can get a listing of all current objects with commands objects()
or ls()
. If you want to remove the object named a
, you can do this:
rm(a)
To remove everything:
rm(list = ls())
or click the broom in RStudio’s Environment pane.
As a final note, R will overwrite an previous information stored in an object without asking you for permission. So, it is a good idea to not use names that are already taken.
x <- c(1, 2, 3)
x
## [1] 1 2 3
x <- c(4, 5, 6)
x
## [1] 4 5 6
You now have a virtual die
that is stored in your computer’s memory. You can access it whenever you like by typing the word die
. So what can you do with this die? Quite a lot. R will replace an object with its contents whenever the object’s name appears in a command. So, for example, you can do all sorts of math with the die.  R uses element-wise execution. When you manipulate a set of numbers, R applies the same operation to each element in the set.
When you use two or more vectors in an operation, R lines up the vectors and performs a sequence of individual operations.  R then multiplies the second element of vector 1 by the second element of vector 2, and so forth, until every element has been multiplied. The result is a vector of the same length as the first two, as visualized below.
Element-wise operations are a very useful feature because they manipulate groups of values in an orderly way. When you start working with data sets, element-wise operations will ensure that values from one observation or case are only paired with values from the same observation or case. Element-wise operations also make it easier to write your own programs and save the output of your results as new objects. Take the following examples.
# creating new objects using other objects
die_minus_one <- die - 1
#create probability table
die_prob <- rep(1/length(die), length(die)) # number desired outcomes / number possible outcomes
cum_prob <- die / 6 # cumulative prob: rolling anything <= to chosen number
die_table <- data.frame(die, die_prob, cum_prob) # Combine different objects into a table
die_table # Display newly created die_prob and cum_prob vectors alongside die values
## die die_prob cum_prob
## 1 1 0.1666667 0.1666667
## 2 2 0.1666667 0.3333333
## 3 3 0.1666667 0.5000000
## 4 4 0.1666667 0.6666667
## 5 5 0.1666667 0.8333333
## 6 6 0.1666667 1.0000000
The first example stores the object die_minus_one
in your environment. Whenever altering datasets or variables, it is recommended you store results as a new object rather than overwriting old ones. This keeps a record of your decision making. The second example shows how we run various calculations on die
, save these as their own objects, and then combine these objects into a data set (more on this later in the R objects section). Each appears as a new object in the Environment pane.
Note how cum_prob
calculates values across die
to produce a vector showing the increasing likliehood of rolling a number equal to or less than a chosen value. For example, you are 100% guaranteed to get at least a 6 or less on any given role. This shows the power of R’s element-wise operations to produce new information from within our data. Statistical tests, transformations, and scoring items are examples where we run a function on a vector to produce new insights we store and use later.
Now that we can do math with your die
object, let’s look at how you could “roll” it. Rolling your die will require something more sophisticated than arithmetic; you’ll need to randomly select one of the die’s values. For that you will need a function.
As we begin assembling…
The Source pane in the upper left is where you create and edit R Scripts – your collections of code. This is basically a notepad of all your notes and actions. RStudio’s source editor supports nifty features, like syntax higlighting, code completion, and find/replace to make it easier to manage. R scripts exist as text files with the “.R” extension. When you open R Studio, it will automtaically start a new Untitled script.
While you can run code either from the source or by typing in the Console, 99% of the time you should use the source. The reason is straightforward: if you type code in the console, it won’t be saved (although you can review in history). If you make a mistake in the console, you’d have to re-type everything all over again. If you ….
The last pane in the bottom right has a number of different tabs.
The Files tab allows you to navigate your file system without leaving RStudio. By default it will display your working directory. The meaning of the icons are as follows:
In order to delete, rename, copy, or move a file, you must select the file(s) that you want to operate on by clicking the white box next to it, so that a check appears. Warning: deleting a file from within RStudio also deletes it from your local file system.
Moving forward, the Plots tab is where graphics you create will appear. The meaning of its icons are as follows:
Let’s see how plots are displayed in the Plots panel. Run the code below to display a histogram of the weights of chickens stored in the ChickWeight
dataset. When you do, you should see a plot similar to the one below show up in the Plots panel.
hist(x = ChickWeight$weight,
main = "Chicken Weights",
xlab = "Weight",
col = "skyblue",
border = "white")
One of the great features of RStudio’s Plot tab is its ability to keep a history of all the plots you have created, and to jump back and forth between them by using the Previous and Next button. Run the following code to create a scatterplot between a chicken’s weight and number of days since birth. Once it appears, you can click on the Previous and Next buttons to switch between both figures.
plot(ChickWeight$weight, ChickWeight$Time,
xlab = "Time", ylab = "Weight",
col = "skyblue")
The third tab, Packages, shows a list of all R packages installed on your hard drive and indicates if they are currently loaded. Loaded packages are checked while those which are installed but not loaded are unchecked. Finally, the Help menu provides all help documents for R functions. You can type the name of a function in the search window, or use the code to search for a function with the name. We will discuss more on packages and help functions in a few sections.
?hist # How does the histogram function work?
?t.test # What about a t-test?
…
R exists as a base package with a reasonable amount of functionality. Once you’ve downloaded and installed R, you can start analyzing and visualizing data. However, the beauty of R is that it can be expanded by downloading packages that add specific functionality to the program. Anyone with a big enough brain and a bit of time and dedication can write a package for other people to use. These packages, as well as the software itself, are stored in a central location known as the CRAN (Comprehensive R Archive Network). Once a package is stored in the CRAN, anyone with an Internet connection can download it from the CRAN and install it to use within their own copy of R.
The CRAN is central to using R: it is the place from where you download the software and any packages that you want to install. It would be a shame, therefore, if the CRAN were one day to explode. The statistical world might collapse. Even assuming the internet does not metldown, it is still a busy place. Therefore, rather than have a single CRAN location that everyone accesses, the CRAN is ‘mirrored’ at different places across the globe. ‘Mirrored’ simply means that there are identical versions of the CRAN scattered across the world. If I resided in Ireland, I might access a CRAN location in Ireland, whereas if you are in a different country you would likely access the copy of the CRAN in your own country (or one nearby). Bigger countries, such as the US, have multiple CRANs to serve them: the basic philosophy is to choose a CRAN that is geographically close to you.
There are two primary ways to install packages. First, we can use the install.packages
command and input the name of the desired packaged as a string. We will be using the afex
package later, which can be installed by running install.packages("afex")
.
A second option is the packages tab in the display pane (lower right) within Rstudio. The tab displays all downloaded packages in the user library. Click on the Install button and type the name of the desired package in the prompt. Rstudio provides an auto-complete drop down list of packages matching entered characters which you can use to identify a desired package.
Once you’ve installed a package, it’s there for life unless you uninstall it. However, you must load the library before the package’s functionality is available. This is done with the library
command.
library(afex)
Once loaded you can now use all the afex
commands. However, any loaded package disappears when ending an R session. So you must load all desired packages each time you start R.
I suggest including a vector of package names at the top of your script and then running the following code to load everything in one go. The code below includes 5 different packages I often use, each with specialized capabilities.
x <- c("tidyverse", "MplusAutomation", "texreg", "tidyr", "lubridate")
lapply(x, require, character.only = TRUE)
## Loading required package: MplusAutomation
## Version: 0.7-3
## We work hard to write this free software. Please help us get credit by citing:
##
## Hallquist, M. N. & Wiley, J. F. (2018). MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus. Structural Equation Modeling, 25, 621-638. doi: 10.1080/10705511.2017.1402334.
##
## -- see citation("MplusAutomation").
## [[1]]
## [1] TRUE
##
## [[2]]
## [1] TRUE
##
## [[3]]
## [1] TRUE
##
## [[4]]
## [1] TRUE
##
## [[5]]
## [1] TRUE
There are a number of different ways to get help in R, most of which broadly come from either internal help systems or online. We will look at internal systems first followed by online resources.
The broadest options are available in the Help menu, including shortcuts, cheat sheets, and documentation provided both from R and R Studio staff. More general manuals and guides can be found under R help or, equivalently, by executing help.start()
.
To get help on a specific function, dataset, or object that you know the name of, use ?
or, equivalently, help
. This provides access to the documentation pages. The following command provides information on the use, arguments, and returned value for the mean
function.
?mean
help(mean) #same
You may also use the help
function to access information about a package in your library — for example, help(package="dplyr")
— which displays an index of help pages for the package along with other information.
If you don’t know the name of the command you are looking for, then you can use ??
or, equivalently, help.search
. These scan the documentation for packages installed in your library, including help pages, vigenttes, and demos. For instance, running help.search("effect size")
on my machine returns functions related to computing Cohen’s D, partial eta squared, and numerous others.
Perhaps the most useful sort of help are vignettes. These are how-to guides for topics, and usually offer gentle introductions and examples. To get a list of all available vignettes type vignette()
followed by the return key. browseVignettes
provides the same list but opened in your webbrowser with links to pdfs and online documentation. Once you see one you are interested in use the openVignette()
command to open it.
Rstudio provides some of the best resources on the web for broadening your skills in R. Perhaps their best resource is a set of cheatsheets providing quick visual references for how popular packages and functions operate. Below is an example of the tidyr
cheatsheet showing how to reshape datasets.
R Bloggers aggregates blogs written in English from across the globe. This is the first place you want to visit if you want tutorial help with R, data analysis, visualization and machine learning. There are blogs on a wide range of topics, including running latent class analysis, logistic regression, and tips for importing data. You can subscribe for regular updates and, if you are a blogger yourself, share it with the R community by adding your blog to R Bloggers.
reprex
package to create reproducible examples. errorist
provides added support for R newcomers by automatically searching the web for solutions whenever R throws and error or warning. This will often redirect to a relevant stack overflow solution. If looking for a specific type of function, the site search.r-project.org is similiar to help.search
but uses the internet to search for information in function help pages and vignettes for all CRAN packages. For instance, if we search for “heart rate variability” we find several functions from the RHRV package which perform spectral analyses on heart rate data. A simply Google query will likely lead you to the same results. If it is a common problem in your field, chances are someone has tried to solve it and uploaded their package to CRAN.
There are additional options within R. available.packages
tells you all the packages that are available in the repositories that you set via setRepositories
. installed.packages
tells you all the packages that you have installed in all the libraries specified in .libPaths
. library
(without any arguments) is similar, returning the names and tag-line of installed packages.
View(available.packages())
View(installed.packages())
library()
.libPaths()
Similarly, data
with no arguments tells you which datasets are available on your machine. search
tells you which packages have been loaded while packageDescription
shows you the contents of a package’s DESCRIPTION
file.
data()
search()
## [1] ".GlobalEnv" "package:MplusAutomation"
## [3] "package:kableExtra" "package:knitr"
## [5] "package:lubridate" "package:texreg"
## [7] "package:car" "package:carData"
## [9] "package:multcomp" "package:TH.data"
## [11] "package:MASS" "package:survival"
## [13] "package:mvtnorm" "package:emmeans"
## [15] "package:afex" "package:lme4"
## [17] "package:Matrix" "package:corrr"
## [19] "package:forcats" "package:stringr"
## [21] "package:dplyr" "package:purrr"
## [23] "package:readr" "package:tidyr"
## [25] "package:tibble" "package:ggplot2"
## [27] "package:tidyverse" "package:psych"
## [29] "package:stats" "package:graphics"
## [31] "package:grDevices" "package:utils"
## [33] "package:datasets" "package:methods"
## [35] "Autoloads" "package:base"
packageDescription("dplyr")
## Type: Package
## Package: dplyr
## Title: A Grammar of Data Manipulation
## Version: <IP_ADDRESS>
## Authors@R: c( person("Hadley", "Wickham"<EMAIL_ADDRESS>## c("aut", "cre"), comment = c(ORCID =
## "0000-0003-4757-117X")), person("Romain", "Fran\u00e7ois",
## role = "aut", comment = c(ORCID = "0000-0002-2444-4226")),
## person("Lionel", "Henry", role = "aut"), person("Kirill",
## "M\u00fcller", role = "aut", comment = c(ORCID =
## "0000-0002-1416-3412")), person("RStudio", role = c("cph",
## "fnd")) )
## Description: A fast, consistent tool for working with data frame
## like objects, both in memory and out of memory.
 Several can be fairly specific. For instance, the abc
package provides tools for approximate Bayesian Computation while the acc
packages is for accelerometer data. While many helpful packages exist, navigating them can be a challenge. Below is a guide to some frequently used R packages by data scientists as indexed by citations and CRAN downloads.
DBI - The standard for for communication between R and relational database management systems. Packages that connect R to databases depend on the DBI package.
odbc - Use any ODBC driver with the odbc package to connect R to your database. Note: RStudio professional products come with professional drivers for some of the most popular databases.
RMySQL, RPostgresSQL, RSQLite - If you’d like to read in data from a database, these packages are a good place to start. Choose the package that fits your type of database.
XLConnect, xlsx - These packages help you read and write Microsoft Excel files from R. You can also just export your spreadsheets from Excel as .csv’s.
foreign - Want to read a SAS data set into R? Or an SPSS data set? Foreign provides functions that help you load data files from other programs into R.
haven - Enables R to read and write data from SAS, SPSS, and Stata.
R can handle plain text files – no package required. Just use the functions read.csv, read.table, and read.fwf. If you have even more exotic data, consult the CRAN guide to data import and export.
dplyr - Essential shortcuts for subsetting, summarizing, rearranging, and joining together data sets. dplyr is our go to package for fast data manipulation.
tidyr - Tools for changing the layout of your data sets. Use the gather and spread functions to convert your data into the tidy format, the layout R likes best.
stringr - Easy to learn tools for regular expressions and character strings.
lubridate - Tools that make working with dates and times easier.
ggplot2 - R’s famous package for making beautiful graphics. ggplot2 lets you use the grammar of graphics to build layered, customizable plots.
ggvis - Interactive, web based graphics built with the grammar of graphics.
rgl - Interactive 3D visualizations with R
htmlwidgets - A fast way to build interactive (javascript based) visualizations with R. Packages that implement htmlwidgets include:
googleVis - Let’s you use Google Chart tools to visualize data in R. Google Chart tools used to be called Gapminder, the graphing software Hans Rosling made famous in hie TED talk.
car - car’s Anova function is popular for making type II and type III Anova tables. Includes many additional functions applied to fitted regression models.
mgcv - Generalized Additive Models
lme4/nlme - Linear and Non-linear mixed effects models
randomForest - Random forest methods from machine learning
multcomp - Tools for multiple comparison testing
vcd - Visualization tools and tests for categorical data
glmnet - Lasso and elastic-net regression methods with cross validation
survival - Tools for survival analysis
caret - Machine learning tools for training regression and classification models
shiny - Easily make interactive, web apps with R. A perfect way to explore data and share findings with non-programmers.
R Markdown - The perfect workflow for reproducible reporting. Write R code in your markdown reports. When you run render, R Markdown will replace the code with its results and then export your report as an HTML, pdf, or MS Word document, or a HTML or pdf slideshow. The result? Automated reporting. R Markdown is integrated straight into RStudio.
xtable - The xtable function takes an R object (like a data frame) and returns the latex or HTML code you need to paste a pretty version of the object into your documents. Copy and paste, or pair up with R Markdown.


Collection of math utility methods.
- Source:
Methods
(static) clamp(value, min, max) → {number}
Clamps a value to a min and max value, inclusive.
Parameters:
| Name | Type | Description |
|---|---|---|
value |
number | Value to be clamped. |
min |
number | Minimum value of the clamp boundary. |
max |
number | Maximum value of the clamp boundary. |
- Source:
Returns:
The resulting value.
- Type
- number
(static) isClamped(value, min, max, exclusiveopt) → {boolean}
Determines if value is bounded by the specified min and max values, defaults
include edge values.
Parameters:
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
value |
number | Value to test against. | ||
min |
number | Minimum value to test against. | ||
max |
number | Maximum value to test against. | ||
exclusive |
boolean |
<optional> |
false | Specifies whether the edge values are omitted. |
- Source:
Returns:
True if bounded, false otherwise.
- Type
- boolean
(static) isEven(value, excludeZeroopt) → {boolean}
Determines if a number is an even number. Zero is considered even by default.
Parameters:
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
value |
number | Value of interest. | ||
excludeZero |
boolean |
<optional> |
false | Speicifies whether zero should be excluded from the test. |
- Source:
Returns:
True if number is even, false otherwise.
- Type
- boolean
(static) isOdd(value) → {boolean}
Determines if a number is an odd number.
Parameters:
| Name | Type | Description |
|---|---|---|
value |
number | Value of interest. |
- Source:
Returns:
True if number is odd, false otherwise.
- Type
- boolean
(static) random(min, max) → {number}
Generates a random real number within the given range, starting from the
minimum (inclusive) to the maximum (exclusive).
Parameters:
| Name | Type | Description |
|---|---|---|
min |
number | Min value (inclusive). |
max |
number | Max value (exclusive). |
- Source:
Returns:
Random number within the given range.
- Type
- number


Born Cape Town, South Africa 1994.
Education:
MA Public Humanities from Brown University, 2017-2019
With a fully-supported two-year fellowship for a student pursuing a master's degree in Public Humanities who is dedicated to working in museums and other cultural institutions on issues related to the history and legacy of slavery.
BA in History and minor in French from University of Alabama, 2012-2016
National Achievement Scholar
Completed coursework abroad in Paris, France at Cours de Civilisation Française de la Sorbonne, 2015
Museum Education and Programming:
Yale University Art Gallery, Cullman-Payson Fellow in Academic Affairs and Outreach, 2019-2021
The Center for the Study of Slavery and Justice, Graduate Fellow for the Study of the Public History of Slavery, 2017-2019
The Studio Museum in Harlem, Public Programs Graduate, Summer 2018
The Metropolitan Museum of Art, Twelve-Month Intern, Teen Programs Education, 2016-2017
The Smithsonian National Museum of Natural History, Research Intern NHRE REU, 2015
Curation and Exhibitions:
Memory Dishes: Women and African Diasporic Cooking, 2019
Lead Curator, Center for the Study of Slavery and Justice
-
Curator of community exhibit exploring the cooking practices of members of the African Diaspora in the Providence area. Memory Dishes provides a platform for underrepresented voices by highlighting six local families, their histories, and the foods they make
A Seat @ The Table, 2018
Curator, Gallery Lab
-
Curated an installation-based exhibit and program series surrounding the kitchen table and the ways the space is used by womxn of color outside of eating and cooking, providing a safe space to host conversations around race, culture, and identity
Rosa Parks House, 2018
Lead Archivist, Center for the Study of Slavery and Justice
-
Project manager of the archival image research for the spring 2018 exhibit on Rosa Parks’ house and the untold story of the Civil Rights Movement. Responsibilities included image archival research, rights acquisitions, and maintaining stakeholder relations
Multimedia Work:
Working Out Loud, 2019
- Developed a month-long podcasting workshop to address equity and social justice issues in podcasting. Provided undergraduate students tools and resources for producing short audio stories that connected their individual communities to overarching social issues.
“Untitled (Cracked Watermelon)”, 2017
- Produced audio story on Charles Ethan Porter, the first African American still-life artist, and his painting Untitled (Cracked Watermelon) which hangs at the Metropolitan Museum of Art
In Fact
- Serialized podcast centering on the lives of Cuban detainees in an American federal detention center in Talladega, Alabama, In Production 2016-
Black Noise
- Co-directed Black Noise, a short documentary on the intersection between race and disability in the Alabama black deaf community, 2014
- Screened at Sidewalk Film Festival and New Orleans Film Festival, 2014
Southern Exposure Film Fellow
- Directed In Our Nature, a short documentary on environmental education for urban Alabama youth, commissioned by The Southern Environmental Law Center, 2014
University Research:
Atlantic Slave Trade Research Group, 2017 - present
Researcher, Firelight Films and The Center for The Study of Slavery and Justice
- Researcher for a PBS produced multi-part documentary on the slave trade. Helped coordinate and manage five intensive research workshops in North America, Europe, and Africa with top scholars and film producers
Memory Dishes: An Exploration of African Diasporic Cooking Practices in Rhode Island
- Researched African diasporic cooking in the United States by taking a hyper-local analysis of culinary practices in Providence, Rhode Island through a series of oral histories
Runaway Advertisements, Hair, and Colonial Racial Identity in Eighteenth Century America
- Researched the connection between descriptions of hair in runaway slave advertisements and 18th century colonial American identity
Freedom on the Move
- Worked as a research assistant for the project “Freedom on the Move” collecting runaway slave advertisements for the purpose of adding them to a digital database.
Presentations and Awards:
- Awarded fully funded two-year fellowship through the Center for the Study of Slavery and Justice in partnership with the John Nicholas Brown Center for Public Humanities
- American Association of Physical Anthropologist, 2016
- National Undergraduate Research Conference 2014
- University of Alabama Undergraduate Research Conference 2013
- Harold Bishop Award
- National Achievement Scholar


Nashville, TN
Hello! I'm currently a senior at Vanderbilt University and will be working as a software engineer at IMC Trading after graduation.
I enjoy problem-solving, especially when it involves code. Looking to expand my skills in just about any direction.
Beyond programming, I enjoy anything outdoors. I'll play just about any sport, but I'm partial to basketball, spikeball, and ultimate frisbee.


__HEADER_SIDE__
The page you've requested cannot be found. If you think this is an error, please contact the webmaster:
__WEBMASTER__
.
__FOOTER__


subject
BOOKS ARCHIVE TJQ5VP5JSRE7TY
doc-i-want-a-pet-mini-edition.pdf
October 25, 2016
Filetype: PDF
|
1725 views
system_update_alt
Download
subject
Read
doc-my-life-hardback.pdf
August 19, 2016
Filetype: PDF
|
1251 views
system_update_alt
Download
subject
Read
doc-dirty-larry.pdf
August 20, 2016
Filetype: PDF
|
1150 views
system_update_alt
Download
subject
Read
doc-chemistry-of-the-non-metals-paperback.pdf
November 02, 2016
Filetype: PDF
|
2428 views
system_update_alt
Download
subject
Read
doc-water-ethics-governance-and-sustainability.pdf
November 09, 2016
Filetype: PDF
|
2897 views
system_update_alt
Download
subject
Read
doc-reference-book-to-the-incorporated-railway-compa.pdf
December 03, 2016
Filetype: PDF
|
1047 views
system_update_alt
Download
subject
Read
doc-a-chance-worth-taking.pdf
January 16, 2017
Filetype: PDF
|
2654 views
system_update_alt
Download
subject
Read
doc-unequal-by-design-high-stakes-testing-and-the-st.pdf
January 30, 2017
Filetype: PDF
|
1965 views
system_update_alt
Download
subject
Read
doc-the-pets-at-home-guide-to-rabbits.pdf
January 08, 2017
Filetype: PDF
|
451 views
system_update_alt
Download
subject
Read
doc-an-equine-anthology-paperback.pdf
August 09, 2016
Filetype: PDF
|
2965 views
system_update_alt
Download
subject
Read
doc-consolidated-screening-checklist-for-automotive-.pdf
December 19, 2016
Filetype: PDF
|
2524 views
system_update_alt
Download
subject
Read
doc-oxford-reading-tree-level-3-more-stories-a-straw.pdf
August 25, 2016
Filetype: PDF
|
1341 views
system_update_alt
Download
subject
Read
doc-the-bible-and-the-new-york-times-paperback.pdf
November 05, 2016
Filetype: PDF
|
2750 views
system_update_alt
Download
subject
Read
doc-20-rebus-mini-books-for-emergent-readers-adorabl-1.pdf
November 11, 2016
Filetype: PDF
|
1921 views
system_update_alt
Download
subject
Read
doc-staar-success-strategies-grade-3-reading-study-g.pdf
August 12, 2016
Filetype: PDF
|
3200 views
system_update_alt
Download
subject
Read
doc-psychiatric-mental-health-nursing-concepts-of-ca.pdf
October 30, 2016
Filetype: PDF
|
2252 views
system_update_alt
Download
subject
Read
doc-windows-glass-houses-volume-2.pdf
November 29, 2016
Filetype: PDF
|
1281 views
system_update_alt
Download
subject
Read
doc-portland-ore-the-delaplaine-2016-long-weekend-gu.pdf
September 27, 2016
Filetype: PDF
|
3122 views
system_update_alt
Download
subject
Read
doc-2015-chinese-map-guangdong-province-township-civ.pdf
January 12, 2017
Filetype: PDF
|
3270 views
system_update_alt
Download
subject
Read
doc-secret-admirer-fear-street.pdf
January 08, 2017
Filetype: PDF
|
2156 views
system_update_alt
Download
subject
Read
doc-four-on-the-shore-paperback.pdf
December 02, 2016
Filetype: PDF
|
2667 views
system_update_alt
Download
subject
Read
doc-the-widower-x27-s-two-step-tres-navarre-mystery.pdf
January 28, 2017
Filetype: PDF
|
3229 views
system_update_alt
Download
subject
Read
doc-acid-alkaline-balance-the-missing-link-to-health.pdf
September 23, 2016
Filetype: PDF
|
1040 views
system_update_alt
Download
subject
Read
doc-screening-for-hiv-in-pregnant-women-systematic-r.pdf
November 10, 2016
Filetype: PDF
|
2736 views
system_update_alt
Download
subject
Read
doc-the-science-of-the-lambs-paperback.pdf
August 16, 2016
Filetype: PDF
|
2203 views
system_update_alt
Download
subject
Read
doc-b-is-for-bedpost-paperback.pdf
October 18, 2016
Filetype: PDF
|
2374 views
system_update_alt
Download
subject
Read
doc-dios-llama-edici-oacute-n-ampliada-spanish-editi.pdf
October 05, 2016
Filetype: PDF
|
2671 views
system_update_alt
Download
subject
Read
doc-my-life-those-wonderful-years.pdf
December 07, 2016
Filetype: PDF
|
2224 views
system_update_alt
Download
subject
Read
doc-woman-an-intimate-geography-revised-and-updated.pdf
November 05, 2016
Filetype: PDF
|
1816 views
system_update_alt
Download
subject
Read
doc-the-homeseller-x27-s-kit-4th-edition.pdf
December 15, 2016
Filetype: PDF
|
3267 views
system_update_alt
Download
subject
Read
doc-markings-absolutely-invincible-high-school-mathe.pdf
December 03, 2016
Filetype: PDF
|
2673 views
system_update_alt
Download
subject
Read
doc-memoria.pdf
September 08, 2016
Filetype: PDF
|
2518 views
system_update_alt
Download
subject
Read
doc-engaging-unbelief-a-captivating-strategy-from-au.pdf
October 07, 2016
Filetype: PDF
|
1002 views
system_update_alt
Download
subject
Read
doc-life-without-principle-paperback.pdf
January 29, 2017
Filetype: PDF
|
2316 views
system_update_alt
Download
subject
Read
doc-kentucky-5th-grade-math-test-prep-common-core-le.pdf
January 09, 2017
Filetype: PDF
|
1590 views
system_update_alt
Download
subject
Read
doc-the-night-thoreau-spent-in-jail-a-play.pdf
October 26, 2016
Filetype: PDF
|
383 views
system_update_alt
Download
subject
Read
doc-statistisches-jahrbuch-15.pdf
October 10, 2016
Filetype: PDF
|
2988 views
system_update_alt
Download
subject
Read
doc-the-true-site-of-calvary-and-suggestions-relatin-3.pdf
December 30, 2016
Filetype: PDF
|
1829 views
system_update_alt
Download
subject
Read
doc-tea-cup-reading-fortune-telling-by-tea-leaves-pa.pdf
November 28, 2016
Filetype: PDF
|
785 views
system_update_alt
Download
subject
Read
doc-willy-and-the-couple.pdf
January 01, 2017
Filetype: PDF
|
2760 views
system_update_alt
Download
subject
Read
doc-u-is-for-underwear.pdf
October 22, 2016
Filetype: PDF
|
2027 views
system_update_alt
Download
subject
Read
doc-jute-cultivation-in-india-and-bangladesh-a-compa.pdf
January 06, 2017
Filetype: PDF
|
1091 views
system_update_alt
Download
subject
Read
doc-pinch-point.pdf
November 02, 2016
Filetype: PDF
|
435 views
system_update_alt
Download
subject
Read
doc-puffin-modern-classics-goodnight-mister-tom.pdf
November 03, 2016
Filetype: PDF
|
694 views
system_update_alt
Download
subject
Read
doc-it-x27-s-your-business-the-smart-guide-to-custom.pdf
December 29, 2016
Filetype: PDF
|
1388 views
system_update_alt
Download
subject
Read
doc-a-collection-of-views-of-land-in-the-indian-navi.pdf
October 27, 2016
Filetype: PDF
|
2983 views
system_update_alt
Download
subject
Read
doc-investing-in-reits-real-estate-investment-trusts.pdf
August 14, 2016
Filetype: PDF
|
660 views
system_update_alt
Download
subject
Read
doc-poems-of-john-donne-volume-2-paperback.pdf
August 06, 2016
Filetype: PDF
|
1969 views
system_update_alt
Download
subject
Read
doc-advent-reflections-come-lord-jesus-paperback.pdf
January 05, 2017
Filetype: PDF
|
1169 views
system_update_alt
Download
subject
Read
doc-command-influence-a-story-of-korea-and-the-polit.pdf
August 24, 2016
Filetype: PDF
|
1480 views
system_update_alt
Download
subject
Read
doc-how-to-subpoena-god-paperback.pdf
January 30, 2017
Filetype: PDF
|
1817 views
system_update_alt
Download
subject
Read
doc-gooney-the-fabulous-paperback.pdf
August 17, 2016
Filetype: PDF
|
641 views
system_update_alt
Download
subject
Read
doc-what-women-fear-walking-in-faith-that-transforms.pdf
January 25, 2017
Filetype: PDF
|
2019 views
system_update_alt
Download
subject
Read
doc-piano-lessons-book-4-book-x2f-enhanced-cd-pack-h.pdf
November 04, 2016
Filetype: PDF
|
1629 views
system_update_alt
Download
subject
Read
doc-glitter-face-painting.pdf
November 13, 2016
Filetype: PDF
|
1601 views
system_update_alt
Download
subject
Read
doc-the-world-s-work-a-history-of-our-time-volume-30.pdf
November 21, 2016
Filetype: PDF
|
1941 views
system_update_alt
Download
subject
Read
doc-this-train-hardback.pdf
November 18, 2016
Filetype: PDF
|
1215 views
system_update_alt
Download
subject
Read
doc-mary-a-daughter-of-the-english-peasantry-by-the-.pdf
November 17, 2016
Filetype: PDF
|
1580 views
system_update_alt
Download
subject
Read
doc-ase-test-preparation-a8-engine-performance-delma.pdf
October 24, 2016
Filetype: PDF
|
1754 views
system_update_alt
Download
subject
Read
doc-single-variable-calculus-early-transcendentals-v-1.pdf
October 22, 2016
Filetype: PDF
|
2100 views
system_update_alt
Download
subject
Read
doc-fighter-operations-in-europe-and-north-africa-19.pdf
January 04, 2017
Filetype: PDF
|
2234 views
system_update_alt
Download
subject
Read
doc-be-a-direct-selling-superstar-achieve-financial-.pdf
December 01, 2016
Filetype: PDF
|
2645 views
system_update_alt
Download
subject
Read
doc-evolution-to-complexity-from-unanimated-matter-t.pdf
January 17, 2017
Filetype: PDF
|
1736 views
system_update_alt
Download
subject
Read
doc-gist-the-essence-of-raising-life-ready-kids.pdf
January 19, 2017
Filetype: PDF
|
1760 views
system_update_alt
Download
subject
Read
doc-the-muslim-prayer-book-how-to-pray-step-by-step-.pdf
December 18, 2016
Filetype: PDF
|
2294 views
system_update_alt
Download
subject
Read
doc-the-birds-of-cedar-point-and-vicinity-paperback.pdf
January 01, 2017
Filetype: PDF
|
2476 views
system_update_alt
Download
subject
Read
doc-the-last-day-i-saw-her-paperback.pdf
October 26, 2016
Filetype: PDF
|
629 views
system_update_alt
Download
subject
Read
doc-nice-girls-don-t-bite-their-neighbors.pdf
November 01, 2016
Filetype: PDF
|
2286 views
system_update_alt
Download
subject
Read
doc-prestigious-teacher-class-job-high-school-chemis-1.pdf
September 09, 2016
Filetype: PDF
|
730 views
system_update_alt
Download
subject
Read
doc-mr-wicker-paperback.pdf
November 13, 2016
Filetype: PDF
|
1863 views
system_update_alt
Download
subject
Read
doc-risk-uncertainty-and-profit-paperback.pdf
August 11, 2016
Filetype: PDF
|
405 views
system_update_alt
Download
subject
Read
doc-achieving-your-potential-as-a-photographer-a-cre.pdf
December 15, 2016
Filetype: PDF
|
1823 views
system_update_alt
Download
subject
Read
doc-minecraft-book-bundles-minecraft-10-books-in-1-m.pdf
September 09, 2016
Filetype: PDF
|
3225 views
system_update_alt
Download
subject
Read
doc-garment-japanese-21-century-fine-art-and-design-.pdf
September 24, 2016
Filetype: PDF
|
1096 views
system_update_alt
Download
subject
Read
doc-the-michigan-technic-volume-5-7.pdf
December 26, 2016
Filetype: PDF
|
2448 views
system_update_alt
Download
subject
Read
doc-decisions-seeking-gods-guidance-9-studies-for-in.pdf
October 09, 2016
Filetype: PDF
|
1614 views
system_update_alt
Download
subject
Read
doc-elvis-takes-a-back-seat.pdf
August 25, 2016
Filetype: PDF
|
1275 views
system_update_alt
Download
subject
Read
doc-old-macdonald-had-a-farm-paperback.pdf
August 05, 2016
Filetype: PDF
|
3179 views
system_update_alt
Download
subject
Read
doc-absence-of-mind.pdf
October 22, 2016
Filetype: PDF
|
2781 views
system_update_alt
Download
subject
Read
doc-milling-machine.pdf
September 12, 2016
Filetype: PDF
|
2077 views
system_update_alt
Download
subject
Read
doc-the-downfall-of-man-paperback.pdf
September 19, 2016
Filetype: PDF
|
1705 views
system_update_alt
Download
subject
Read
doc-und-gib-uns-frieden-ein-buch-weltlicher-andacht-.pdf
September 30, 2016
Filetype: PDF
|
2981 views
system_update_alt
Download
subject
Read
doc-erythrocyte-sedimentation-rate-is-it-an-importan.pdf
January 14, 2017
Filetype: PDF
|
2497 views
system_update_alt
Download
subject
Read
doc-el-plan-de-comunicaci-oacute-n-hospitalario-herr.pdf
January 11, 2017
Filetype: PDF
|
3289 views
system_update_alt
Download
subject
Read
doc-masters-of-time-a-science-fiction-and-fantasy-ti.pdf
October 17, 2016
Filetype: PDF
|
2055 views
system_update_alt
Download
subject
Read
doc-50-things-you-should-know-about-u-s-government-t.pdf
December 31, 2016
Filetype: PDF
|
2521 views
system_update_alt
Download
subject
Read
doc-a-new-construction-of-homogeneous-quaternionic-m.pdf
August 17, 2016
Filetype: PDF
|
2452 views
system_update_alt
Download
subject
Read
doc-the-delineator-volume-101-paperback.pdf
August 09, 2016
Filetype: PDF
|
2461 views
system_update_alt
Download
subject
Read
doc-essential-maths-skills-for-as-x2f-a-level-psycho.pdf
December 04, 2016
Filetype: PDF
|
344 views
system_update_alt
Download
subject
Read
doc-scientific-healing-affirmations-paperback.pdf
January 20, 2017
Filetype: PDF
|
774 views
system_update_alt
Download
subject
Read
Other Files
description
doc-l-orlando-furioso-4-paperback.pdf
[37.86 KB]
description
doc-the-terrible-old-man-and-the-secret-cave-paperba.pdf
[37.86 KB]
description
doc-politicians-at-war.pdf
[37.86 KB]
description
doc-dedication-of-the-state-library-building-at-conc.pdf
[37.86 KB]
description
doc-the-confidence-man-his-masquerade-paperback.pdf
[37.86 KB]
description
doc-edge-of-darkness-the-men-of-t-flac-the-edge-brot.pdf
[37.86 KB]
description
doc-national-defense-weaknesses-in-the-resident-lang.pdf
[37.86 KB]
description
doc-creature-feature-hardback.pdf
[37.86 KB]
description
doc-economic-and-social-survey-of-asia-and-the-pacif-2.pdf
[37.86 KB]
description
doc-electron-paramagnetic-resonance-epr-investigatio.pdf
[37.86 KB]
description
doc-como-sacar-los-idiotas-del-gobierno-how-to-get-s.pdf
[37.86 KB]
description
doc-studyguide-for-traditions-and-encounters-volume--5.pdf
[37.86 KB]
description
doc-insight-travel-map-ireland-insight-travel-maps.pdf
[37.86 KB]
description
doc-the-black-fens.pdf
[37.86 KB]
description
doc-thelonious-monk-quartet-with-john-coltrane-at-ca-1.pdf
[37.86 KB]
description
doc-milk-and-honey.pdf
[37.86 KB]
description
doc-f-s-p-an-n-c-o-s-description-of-his-and-others-f.pdf
[37.86 KB]
description
doc-meditation-for-beginners.pdf
[37.86 KB]
description
doc-bible-proofs-of-universal-salvation-containing-t-9.pdf
[37.86 KB]
description
doc-the-mystery-of-the-roman-gladiator-paperback.pdf
[37.86 KB]
description
doc-sister-x2f-brother-gertrude-leo-s-pb-gertrude-an.pdf
[37.86 KB]
description
doc-my-name-is-rachel-corrie-2nd-revised-edition.pdf
[37.86 KB]
description
doc-ocr-21st-century-gcse-chemistry-a-exam-practice-.pdf
[37.86 KB]
description
doc-white-wolf-a-novel-of-druss-the-legend.pdf
[37.86 KB]
description
doc-the-end-of-molasses-classes-getting-our-kids-uns.pdf
[37.86 KB]
description
doc-anti-inflammation-diet-critical-tips-and-hints-o.pdf
[37.86 KB]
description
doc-principles-of-human-anatomy.pdf
[37.86 KB]
description
doc-the-noble-rebellion-paperback.pdf
[37.86 KB]
description
doc-macmillan-language-tree-primary-language-arts-fo-4.pdf
[37.86 KB]
description
doc-eager-paperback.pdf
[37.86 KB]
description
doc-too-bad-to-forgive-1-the-potpourri-novella-serie.pdf
[37.86 KB]
description
doc-lightning-rod-faces-the-cyclops-queen.pdf
[37.86 KB]
description
doc-big-kids-coloring-book-tropical-undersea-wonders.pdf
[37.86 KB]
description
doc-sundays-with-jesus-reflections-for-the-year-of-m-1.pdf
[37.86 KB]
description
doc-the-kingfisher-treasury-of-funny-stories.pdf
[37.86 KB]
description
doc-probability-and-mathematical-statistics-study-gu.pdf
[37.86 KB]
description
doc-wonder-woman-the-greatest-stories-ever-told-pape.pdf
[37.86 KB]
description
doc-valour-and-vanity.pdf
[37.86 KB]
description
doc-the-conservative-holiness-movement-a-historical-.pdf
[37.86 KB]
description
doc-metropolitan-system-of-bookkeeping-volume-1-2-em.pdf
[37.86 KB]
description
doc-image-of-the-city.pdf
[37.86 KB]
description
doc-le-meurtre-de-la-falaise.pdf
[37.86 KB]
description
doc-london-calling-paperback.pdf
[37.86 KB]
description
doc-made-with-love-for-dad.pdf
[37.86 KB]
description
doc-cherokee-legends-and-the-trail-of-tears-by-thoma.pdf
[37.86 KB]
description
doc-limits-space-as-resource-paperback.pdf
[37.86 KB]
description
doc-goodnight-mr-darcy.pdf
[37.86 KB]
description
doc-ed466-061-teaming-with-technology-research-proje.pdf
[37.86 KB]
description
doc-how-to-do-relationships-a-step-by-step-guide-to-.pdf
[37.86 KB]
description
doc-level-up-hardback.pdf
[37.86 KB]
description
doc-social-security-and-medicare-answer-book-2012.pdf
[37.86 KB]
description
doc-violin-playtime-bk-2-violin-and-piano-paperback.pdf
[37.86 KB]
description
doc-iowa-gems-and-minerals-in-your-pocket-mixed-medi.pdf
[37.86 KB]
description
doc-cold-day-warm-day-furs-mountain-genuine-mall-chi.pdf
[37.86 KB]
description
doc-training.pdf
[37.86 KB]
description
doc-blessings-through-the-years-paperback.pdf
[37.86 KB]
description
doc-world-energy-projection-system-plus-model-docume-1.pdf
[37.86 KB]
description
doc-biscuits-breads-amp-cookies.pdf
[37.86 KB]
description
doc-ayudenme-siento-desanimo-paperback.pdf
[37.86 KB]
description
doc-books-printed-and-sold-by-t-sowle-in-white-hart-.pdf
[37.86 KB]
description
doc-usurper-of-the-sun.pdf
[37.86 KB]
description
doc-tomorrow-classic-novels-paperback.pdf
[37.86 KB]
description
doc-the-pied-piper-of-hamelin-russell-brand-x27-s-tr.pdf
[37.86 KB]
description
doc-the-prodigal-god-curriculum-kit-finding-your-pla.pdf
[37.86 KB]
description
doc-diary-illustrative-of-the-times-of-george-the-fo-1.pdf
[37.86 KB]
description
doc-book2-english-arabic-for-beginners-a-book-in-2-l.pdf
[37.86 KB]
description
doc-bridge-and-tunnel-centres.pdf
[37.86 KB]
description
doc-mr-greedy-mr-men-classic-library.pdf
[37.86 KB]
description
doc-advanced-high-temperature-seal-development-at-na.pdf
[37.86 KB]
description
doc-fairy-circle.pdf
[37.86 KB]
description
doc-the-sea-glass-hunter-x27-s-handbook.pdf
[37.86 KB]
description
doc-die-grenzboten-47-pt-2.pdf
[37.86 KB]
description
doc-holt-mcdougal-literature-alabama-target-standard-4.pdf
[37.86 KB]
description
doc-the-coming-spiritual-earthquake-another-perspect.pdf
[37.86 KB]
description
doc-american-jewish-fiction-a-century-of-stories.pdf
[37.86 KB]
description
doc-mediterranean-meals-25-delicious-recipes-and-the.pdf
[37.86 KB]
description
doc-text-me-paperback.pdf
[37.86 KB]
description
doc-measurement-of-electrical-resistance-and-mechani.pdf
[37.86 KB]
description
doc-beyond-impunity-an-ecumenical-approach-to-truth-.pdf
[37.86 KB]
description
doc-obamas-challenge-americas-economic-crisis-and-th.pdf
[37.86 KB]
description
doc-lean-manufacturing-implementation-a-complete-exe.pdf
[37.86 KB]
description
doc-roman-law-essentials.pdf
[37.86 KB]
description
doc-tracks-scats-and-signs-of-rocky-mountain-mammals.pdf
[37.86 KB]
description
doc-all-of-me.pdf
[37.86 KB]
description
doc-predators-and-child-molesters-what-every-parent--1.pdf
[37.86 KB]
description
doc-studyguide-for-physical-education-for-elementary.pdf
[37.86 KB]
description
doc-rw-primary-tcm-clinical-department-of-must-read-.pdf
[37.86 KB]
description
doc-the-best-book-to-read.pdf
[37.86 KB]
description
doc-dove-egrave-sempre-notte.pdf
[37.86 KB]
description
doc-urchin-of-the-riding-stars-new-edition.pdf
[37.86 KB]
description
doc-dutch-courage-and-other-stories-paperback.pdf
[37.86 KB]
description
doc-one-master-one-disciple-a-thrilling-spiritual-ad.pdf
[37.86 KB]
description
doc-allergy-friendly-food-for-families-120-gluten-fr.pdf
[37.86 KB]
description
doc-advanced-topics-in-end-user-computing-series-vol.pdf
[37.86 KB]
description
doc-i-x27-m-going-to-read-reg-level-2-harry-x27-s-ba.pdf
[37.86 KB]
description
doc-aztec-fire-paperback.pdf
[37.86 KB]
description
doc-what-you-don-t-see-a-collection-of-short-stories.pdf
[37.86 KB]
description
doc-electronic-principles-devices-and-circuits.pdf
[37.86 KB]
description
doc-propaganda-paperback.pdf
[37.86 KB]
description
doc-wrestling-with-the-angel.pdf
[37.86 KB]
description
doc-best-practices-for-graphic-designers-color-works.pdf
[37.86 KB]
description
doc-the-haunted-dolls-house-paperback.pdf
[37.86 KB]
description
doc-how-to-hear-god-paperback.pdf
[37.86 KB]
description
doc-everything-is-illuminated.pdf
[37.86 KB]
description
doc-current-economic-conditions-march-5-2014-paperba.pdf
[37.86 KB]
description
doc-limited-time-love-3-bwwm-romance-best-sellers-in.pdf
[37.86 KB]
description
doc-one-pot-the-stand-alone-flip-it-book-for-fuss-fr.pdf
[37.86 KB]
description
doc-studyguide-for-introductory-statistics-by-weiss-.pdf
[37.86 KB]
description
doc-suicidal-kings-the-road-to-redemption.pdf
[37.86 KB]
description
doc-blue-exorcist-6.pdf
[37.86 KB]
description
doc-the-deadliest-weapon.pdf
[37.86 KB]
description
doc-the-worlds-coolest-hotel-rooms-the-cool-hunter.pdf
[37.86 KB]
description
doc-a-manager-s-guide-to-service-science-a-comprehen.pdf
[37.86 KB]
description
doc-the-bushcraft-handbooks-trapping-tracks-paperbac.pdf
[37.86 KB]
description
doc-the-mascot-comic-opera-in-three-acts-classic-rep.pdf
[37.86 KB]
description
doc-project-x-alien-adventures-dark-blue-book-band-o-6.pdf
[37.86 KB]
description
doc-longing-for-a-kiss-love-poems-from-many-lands.pdf
[37.86 KB]
description
doc-dances-with-my-father-paperback.pdf
[37.86 KB]
description
doc-methods-in-teaching-being-the-stockton-methods-i.pdf
[37.86 KB]
description
doc-sea-glass-island.pdf
[37.86 KB]
description
doc-reading-2002-practice-book-grade-1-6.pdf
[37.86 KB]
description
doc-cost-accounting-in-the-21st-century-applied-unde.pdf
[37.86 KB]
description
doc-deliberative-mini-publics-involving-citizens-in-.pdf
[37.86 KB]
description
doc-draft-programmatic-environmental-assessment-gran.pdf
[37.86 KB]
description
doc-ninth-grade-cloze-intensive-training-the-red-dev.pdf
[37.86 KB]
description
doc-step-forward-sexual-harassment-in-the-workplace-.pdf
[37.86 KB]
description
doc-topics-in-geophysical-fluid-dynamics-atmospheric.pdf
[37.86 KB]
description
doc-9787546388175-wuhai-night-flying-red-classic-mov.pdf
[37.86 KB]
description
doc-the-math-of-soccer-paperback.pdf
[37.86 KB]
description
doc-bournemouth-x27-s-founders-and-famous-visitors.pdf
[37.86 KB]
description
doc-dealings-with-the-firm-of-dombey-and-son-wholesa-1.pdf
[37.86 KB]
description
doc-alzheimers-hard-questions.pdf
[37.86 KB]
description
doc-the-new-covenant-paperback.pdf
[37.86 KB]
description
doc-brother-of-sleep.pdf
[37.86 KB]
description
doc-must-the-chinese-go-an-examination-of-the-chines-1.pdf
[37.86 KB]
description
doc-leonard-dobbs-peak-oil-entrepreneur-paperback.pdf
[37.86 KB]
description
doc-vanilla-gorilla.pdf
[37.86 KB]
description
doc-prevention-x27-s-food-and-nutrition-the-most-com.pdf
[37.86 KB]
description
doc-teach-them-spanish-grade-4.pdf
[37.86 KB]
description
doc-a-handshake-with-change.pdf
[37.86 KB]
description
doc-the-kama-sutra-illustrated.pdf
[37.86 KB]
description
doc-highway-construction-manual-bridges-and-culverts.pdf
[37.86 KB]
description
doc-i-met-god-in-bermuda-faith-in-the-21st-century.pdf
[37.86 KB]
description
doc-genuine-national-secondary-vocational-and-techni.pdf
[37.86 KB]
description
doc-candle-prayers-for-toddlers.pdf
[37.86 KB]
description
doc-poznaj-sowa-blisko-i-daleko-fk-op.pdf
[37.86 KB]
description
doc-cosmos-and-consciousness-quantum-computers-super.pdf
[37.86 KB]
description
doc-click-start-6-computer-science-for-schools.pdf
[37.86 KB]
description
doc-jason-edwards-an-average-man-paperback-1.pdf
[37.86 KB]
description
doc-tangle-magic-a-spellbinding-colouring-book-with-.pdf
[37.86 KB]
description
doc-algebra-ii-workbook-for-dummies.pdf
[37.86 KB]
description
doc-organize-yourself-3rd-revised-edition.pdf
[37.86 KB]
description
doc-the-lost-language-of-plants-the-ecological-impor.pdf
[37.86 KB]
description
doc-my-first-trucks-my-1st-board-books.pdf
[37.86 KB]
description
doc-holt-algebra-1-new-york-homework-and-practice-wo.pdf
[37.86 KB]
description
doc-a-collection-of-performance-tasks-amp-rubrics-hi.pdf
[37.86 KB]
description
doc-igniting-the-soul-at-work-a-mandate-for-mystics.pdf
[37.86 KB]
description
doc-symmetry-elements-and-group-theory.pdf
[37.86 KB]
description
doc-wickingham-way-a-harbour-falls-mystery-3.pdf
[37.86 KB]
description
doc-reporting-status-of-aerospace-expeditionary-forc.pdf
[37.86 KB]
description
doc-handbook-of-linear-algebra.pdf
[37.86 KB]
description
doc-college-textbooks-embedded-software-foundation-c.pdf
[37.86 KB]
description
doc-coping-with-stress-vs-beating-stress.pdf
[37.86 KB]
description
doc-place-for-talk-a-role-of-talk-in-the-education-o.pdf
[37.86 KB]
description
doc-103-crafts-activities-for-preschoolers-toddlers-.pdf
[37.86 KB]
description
doc-mission-how-the-best-in-business-break-through.pdf
[37.86 KB]
description
doc-christianizing-the-social-order.pdf
[37.86 KB]
description
doc-no-sweat-science-reg-optical-illusion-experiment.pdf
[37.86 KB]
description
doc-tulsian-s-accountancy-for-ca-ipcc-group-i-with-q.pdf
[37.86 KB]
description
doc-the-cheery-book-paperback.pdf
[37.86 KB]
description
doc-using-information-technology-nvq-level-2-simulat.pdf
[37.86 KB]
description
doc-cross-cultural-psychology-2nd-edition.pdf
[37.86 KB]
description
doc-an-historical-view-of-the-philippine-islands-vol.pdf
[37.86 KB]
description
doc-containment-relevant-or-relic-paperback.pdf
[37.86 KB]
description
doc-101-ways-to-flirt-how-to-get-more-dates-and-meet.pdf
[37.86 KB]
description
doc-religious-reality-paperback.pdf
[37.86 KB]
description
doc-genuine-brand-new-guarantee-customize-new-the-cl.pdf
[37.86 KB]
description
doc-building-construction-and-the-knowledge-map-high.pdf
[37.86 KB]
description
doc-the-man-who-inherited-a-golf-course.pdf
[37.86 KB]
description
doc-a-legal-guide-to-united-states-business-organiza.pdf
[37.86 KB]
description
doc-an-article-on-the-propagation-by-offshoots-of-th.pdf
[37.86 KB]
description
doc-pupils-daily-20-minutes-mathematical-olympiad-3-.pdf
[37.86 KB]
description
doc-nber-international-seminar-on-macroeconomics-200-1.pdf
[37.86 KB]
description
doc-stories-from-ireland.pdf
[37.86 KB]
description
doc-mcdougal-littell-language-of-literature-resource-2.pdf
[37.86 KB]
description
doc-a-sincere-and-pure-devotion-to-christ-volume-2-1.pdf
[37.86 KB]
description
doc-real-emotional-logic-film-and-television-docudra.pdf
[37.86 KB]
description
doc-wicked-business-wicked-series-book-2.pdf
[37.86 KB]
description
doc-the-man-who-would-be-king.pdf
[37.86 KB]
description
doc-foundations-of-galois-theory-international-serie.pdf
[37.86 KB]
description
doc-billy-sure-kid-entrepreneur-and-the-no-trouble-b.pdf
[37.86 KB]
description
doc-homes-and-home-life-in-bible-lands.pdf
[37.86 KB]
description
doc-pot-pourri-parisien-classic-reprint-paperback.pdf
[37.86 KB]
description
doc-shift-using-business-simulations-and-serious-gam.pdf
[37.86 KB]
description
doc-the-duchess-of-malfi-and-other-plays.pdf
[37.86 KB]
description
doc-the-impact-of-two-professional-development-inter.pdf
[37.86 KB]
description
doc-in-the-public-version-of-the-2013-tianjin-instit.pdf
[37.86 KB]
description
doc-insight-guides-explore-sydney-paperback.pdf
[37.86 KB]
description
doc-ant-and-honey-bee-a-pair-of-friends-in-winter-ca.pdf
[37.86 KB]
description
doc-arthur-schopenhauer-x27-s-s-auml-mmtliche-werke--2.pdf
[37.86 KB]
description
doc-365-way-to-motivate-and-reward-your-employees-ev.pdf
[37.86 KB]
description
doc-beyond-the-barn-door-earth-has-run-out-of-time-b.pdf
[37.86 KB]
description
doc-christmas-hits.pdf
[37.86 KB]
description
doc-supernaturally.pdf
[37.86 KB]
description
doc-ivan-the-terrible-paperback.pdf
[37.86 KB]
description
doc-islam-and-the-problem-of-black-suffering.pdf
[37.86 KB]
description
doc-golf-crazy-hardback-1.pdf
[37.86 KB]
description
doc-chemistry-1212-general-chemistry-lab-manual-9th-.pdf
[37.86 KB]
description
doc-2014-6-latest-reform-of-college-english-six-ques.pdf
[37.86 KB]
description
doc-globalization-is-a-form-of-colonialism.pdf
[37.86 KB]
description
doc-mantra-healing-mantras-for-long-life-health-weal.pdf
[37.86 KB]
description
doc-online-crowdfunding-in-turkey.pdf
[37.86 KB]
description
doc-policing-major-events-perspectives-from-around-t.pdf
[37.86 KB]
description
doc-phr-exam-secrets-study-guide-phr-test-review-for-1.pdf
[37.86 KB]
description
doc-in-the-shadow-of-the-buddha-secret-journeys-sacr.pdf
[37.86 KB]
description
doc-causeries-du-lundi-11.pdf
[37.86 KB]
description
doc-dark-journey-castles-amp-crusades-modules-amp-ad.pdf
[37.86 KB]
description
doc-the-international-teacher-paperback.pdf
[37.86 KB]
description
doc-all-these-things-added.pdf
[37.86 KB]
description
doc-combo-loose-leaf-version-of-human-physiology-wit.pdf
[37.86 KB]
description
doc-hard-times-quot.pdf
[37.86 KB]
description
doc-math-all-around-you-grade-5-unit-5-leveled-reade.pdf
[37.86 KB]
description
doc-a-tame-surrender-a-story-of-the-chicago-strike-p.pdf
[37.86 KB]
description
doc-highlights-from-timss-2011.pdf
[37.86 KB]
description
doc-revised-ordinances-of-1906-standing-regulations-.pdf
[37.86 KB]
description
doc-prayers-for-the-dying-paperback.pdf
[37.86 KB]
description
doc-summerkin-paperback.pdf
[37.86 KB]
description
doc-200-words-pupils-easy-fun-n-word-essay-limit-chi.pdf
[37.86 KB]
description
doc-primary-english-south-supplementary-step-through.pdf
[37.86 KB]
description
doc-american-odyssey-the-united-states-in-the-20th-c-9.pdf
[37.86 KB]
description
doc-the-reliquary-volume-6-paperback.pdf
[37.86 KB]
description
doc-the-memorist.pdf
[37.86 KB]
description
doc-glory-and-praise.pdf
[37.86 KB]
description
doc-the-dukan-diet-lose-weight-quickly-and-safely-fo.pdf
[37.86 KB]
description
doc-concord-lectures-on-philosophy-comprising-outlin.pdf
[37.86 KB]
description
doc-practices-for-engaging-the-21st-century-workforc.pdf
[37.86 KB]
description
doc-change-your-life-7-key-tips-to-have-more-willpow.pdf
[37.86 KB]
description
doc-forced-justice-school-desegregation-and-the-law.pdf
[37.86 KB]
description
doc-coal-industry-enterprises-occupational-health-an.pdf
[37.86 KB]
description
doc-h1-genuine-integrity-panic-chinese-edition.pdf
[37.86 KB]
description
doc-plane-and-solid-analytic-geometry-an-elementary-.pdf
[37.86 KB]
description
doc-the-right-way-to-teach-chess-to-kids.pdf
[37.86 KB]
description
doc-applied-physics-for-engineers-pb-2014.pdf
[37.86 KB]
description
doc-the-power-of-soft-how-to-get-what-you-want-and-n.pdf
[37.86 KB]
description
doc-the-story-of-captain-the-horse-with-the-human-br.pdf
[37.86 KB]
description
doc-the-psychedelic-sacrament-manna-meditation-and-m.pdf
[37.86 KB]
description
doc-troublers-paperback.pdf
[37.86 KB]
description
doc-the-return-of-the-great-depression.pdf
[37.86 KB]
description
doc-the-cello-collection-easy-x2f-intermediate-mixed.pdf
[37.86 KB]
description
doc-samuel-de-champlain.pdf
[37.86 KB]
description
doc-kenyattas-escape-paperback.pdf
[37.86 KB]
description
doc-moleskine-messages-postal-notebook-large-plain-f.pdf
[37.86 KB]
description
doc-chart-of-medical-microbiology-9787117131742-chin.pdf
[37.86 KB]
description
doc-introducing-the-oscillations-based-paradigm.pdf
[37.86 KB]
description
doc-managerial-economics-the-concise-chinese-edition.pdf
[37.86 KB]
description
doc-kachina-tales-from-the-indian-pueblos-paperback.pdf
[37.86 KB]
description
doc-genuine-plant-chemical-protection-experiments-gu.pdf
[37.86 KB]
description
doc-the-girl-with-a-clock-for-a-heart-paperback.pdf
[37.86 KB]
description
doc-the-accused.pdf
[37.86 KB]
description
doc-taxation-of-corporations-volume-6-paperback.pdf
[37.86 KB]
description
doc-hummingbird-falls-an-ellie-hastings-mystery.pdf
[37.86 KB]
description
doc-excel-x-for-mac-os-x-visual-quickstart-guide.pdf
[37.86 KB]
description
doc-child-s-geography-and-history-of-st-louis-city-c.pdf
[37.86 KB]
description
doc-g3-genuine-the-1994-2004-western-medicine-integr.pdf
[37.86 KB]


the and was were from The Company poultry for IBV using viral {background population with between companies Italian could analysis been different farms margin other that this {border-style (Fig. are strains px;} sequences spreading two #ffffff;} dispersal factors infectious obtained virus which considered when (i.e. environmental has over deme its most only bronchitis have high migration not Avian However, area control influenza integrated one rate same size transmission Northern [HPD: also among ghost infection reported risk role than vaccination avian based collected each farm field genotype including introduction phylogenetic posterior presence present relevant trees Italy after all coalescent effect effective estimated evaluated model px; samples some spatial structured time {font-family All approach branch can circulation companies, continuous demonstrated distribution font-size included increase information more results selected strain these third used velocity .*− Although Biol. Therefore, biosecurity cannot densely density double; epidemiology evolution further likelihood likely mainly major management measures model, new observed phylogeographic populated recombination sampled study their time. BEAST Bayesian Figure Influenza Italy. Moreover, Results Supplementary Vet. affecting belonging border-color border-width cells companies. company density, during epidemiological even fact, factor final generated greater higher history located molecular parameters partially performed period production reconstructed red region several single solid; spread studies thus tree under understanding variables where {font-style {font-weight "ghost�? (). Additionally, B). Commons Creative Even GI- Infectious Italy) More Pathol../ [], adequate al. analysis. animal associated available being bold but calculated certain clinical clock clustering courier; dataset demes described determinants em; epidemiology. events factors, featured first formed genetic implemented increased investigated least like lineage live location models movement movements number outbreaks p-value pattern patterns provide pt;} raster rather reconstruct region. relatively remarkable representative represented rural sampling scale. seems sharing significant study, therefore those use vaccine values wave while


Martin Bashir saved on X Factor Celebrity - despite forgetting lyrics
Bashir stumbled while performing the Commodores song Easy during the live show and said: "I've forgotten my words, I do apologise."
by James Rodger, https://www.facebook.com/jamesrodgerjournalistMartin Bashir has survived the axe from X Factor: Celebrity, despite forgetting the words to his song.
Instead soap stars Victoria Ekanoye and Jonny Labey got the boot after losing out in the public vote.
Bashir stumbled while performing the Commodores song Easy during the live show and said: "I've forgotten my words, I do apologise."
Afterwards, he said: "I'm not trying to make excuses but my song had to be changed very late so I learned this song this morning.
"I had been working on something else and rights issues meant we couldn't do that."
Simon Cowell told him: "I knew the story so I knew things were likely to go wrong.
"I hope the audience gives you a second chance."
After learning he had survived to sing another week, Bashir said: "There is some kind of psychotic breakdown happening in this country."
While Ekanoye said she expected to be given the chop, Labey said he felt he had much more to give as he was dumped from the show.
Earlier in the episode, Try Star paid tribute to the England rugby team after their defeat in the World Cup final at the hands of South Africa, with a performance of Swing Low, Sweet Chariot.
The performance prompted Nicole Scherzinger to give the group, mentored by Cowell, her safe seat.
Meanwhile Cowell gave his safe seat to Love Island group No Love Lost.
The X Factor: Celebrity continues next Saturday on ITV at 8.10pm.


--- layout: post date: 2006-04-17 time: "09:00:00" authors: ["Greg Wilson"] title: "Zipf's Law of Feedback" tags: ["Opinion"] ---
Zipf's Law says that frequency is inversely proportional to rank, i.e., the second most common word in a large body of text will occur half as many times as the most common. I have observed an even steeper curve for Software Carpentry feedback: of the 336 corrections I've received, 212 are from one person (Adam Goucher), 21 from Matthew Moelter, 12 from the next two people, and then we're down into the curve's long tail. Has anyone ever done similar stats on the volume or frequency of contributions to software projects?


del shape[_]
new_shape = shape[nones:]
new_shape = tuple([C.InferredDimension if _ == C.FreeDimension else _ for _ in new_shape])
return C.reshape(x, new_shape)
def tile(x, n):
new_shape = shape[nones:]
new_shape_temp = []
for _ in new_shape:
if _ == C.FreeDimension:
new_shape_temp.append(C.InferredDimension)
else:
new_shape_temp.append(_)
new_shape = tuple(new_shape_temp)
return C.reshape(x, new_shape)


Gradient Table
Select Dimensions (2-100):
Note:
Please select any value
n
from 2 to 100 to get
n
x
n
table.
{{c}}
{{r}}
{{r + c}}


Description
scrollNav is a light jQuery plugin that grabs your page's existing content, divides it up into logical sections and builds a customizable scrolling sidebar navigation. Scroll this page and watch the nav follow along with you.
Features
-
Simple to setup
A single file import and function in your footer and you're on your way.
-
Fully Customizable
All the styling is up to you and the few bits controled by the plugin are editable
-
Tiny Size
Damn right it's fast! At 1.5kb min'd and GZip'd, scrollNav is pretty unintrusive.
Usage
Import
Start by importing the script to your page, the best location is in the footer, but no matter what, make sure it follows your jQuery file.

Build your page
Include a class or id hook on the element you want to apply the plugin to and include an

for section headings you want to inlcude in the navigation.

This is the main heading for the article

This is a sub-heading for the article

Yada yada yada...

This is a section heading

More yada yada...

Another section heading

More more yada...

Initialize
Now initialize the plugin with your hook for the article
$('.post__article').scrollNav();
The plugin scans the article, grabs all the

s, adds them to the navigation list and inserts the list before the article. It’s that easy…well almost.
Styling

An active
class is attached to the nav item matching the section that is the highest within the view bounds. An in-view
class is attached to all nav items whose section is within the view bounds. If you have short sections at the end of your page and dislike that the last nav itmes are never activated, you can use the in-view
hook to style all sections with in the view.
There are loading hooks added to the body element (similar to how Typekit handles font loading) to allow for css transitions or any other changes in css you'd need. When the plug-in starts sn-loading
is added to the body class and is replaced by sn-active
when the plugin is successful or sn-failed
if it fails.
Options
There are a few customizable options in scrollNav using key : value pairs. Here are the defaults.
$('.post-article').scrollNav({ sections: 'h2', subSections: false, sectionElem: 'section', showHeadline: true, headlineText: 'Scroll To', showTopLink: true, topLinkText: 'Top', fixedMargin: 40, scrollOffset: 40, animated: true, speed: 500, insertTarget: this.selector, insertLocation: 'insertBefore', arrowKeys: false, onInit: null, onRender: null, onDestroy: null });
Sections
As mentioned, the script automatically searches for

s within the target article. If your page structure differs, feel free to target another element, like an

or

or even a class, like .scroll-headline
.
Sub-sections
Set to false
by default, the plugin supports nesting sub-sections within each section in the final nav. Available selectors are the same as Sections.
Section Wrapper Element
If your article already contains section
tags, you'll want to change this to 'div'
. Sub-sections aren't affected by this option.
Show Headline
Set this to false
to remove the Headline Text entirely.
Headline Text
scrollNav’s default headline text is ‘Scroll To’, but feel free to change it to whatever works for you, like ‘Article Sections’ or ‘Page Navigation’
Show Top Link
Set this to false
to remove the Top
nav item entirely.
Top Link Text
scrollNav’s default return to the top link text is ‘Top’, but feel free to change it to whatever works for you.
Fixed Margin
This is the top
dimension you set for the .scroll-nav.fixed
class, which is applied as the user scrolls down the page and is removed as they scroll above the article. You definitely want to set this if you don’t use the default 40px, otherwise the nav will jump around as the user scrolls past the top of the article.
Scroll Offset
This option affects two things. First is the "active state" boundries within the viewport. The bounderies are within the area from the top and bottom of the viewport offset by this amount. Second is the destination when scrolling the page. This will place the heading of the section right at the top edge of the "active state" boundry.
Animated Scrolling
The plugin animates the page scroll when clicking on a nav link by default. Set this to false
if you do not wish to animate the scroll.
Scrolling Speed
Change this to either increase or decrease the animated page scroll speed.
Insertion Target
If you need to insert the nav relative to an element other than the one scrollNav is initialized on, you can change it here.
Insertion Location
You can pass any of the following jQuery insertion methods to change where scrollNav is inserted in relation to the targeted container. insertBefore
, prependTo
, appendTo
, or insertAfter
Arrow Key Navigation
Set to false
by default, change this to `true` to allow up/down arrow keys to jump through each section.
Callback functions
There are three new callback functions that you can utilize to accomodate anything you need to run after specific scrollNav events. They are onInit, onRender, and onDestroy. Add them to your options just like any other and they should look like this:
$('.post__article').scrollNav({ onInit: function() { callback actions in here } });
Errors
The plugin will refuse to build and log an error message if it doesn’t find your desired container or any sections within the container. If the nav doesn’t show up on load, check your browser’s console.
Issues
There are a few known issues, including poor location updating when scrolling on touch devices. If you find any others please submit them to the.
License
scrollNav is Copyright © 2012-2013 James Wilson, released under the This means you can re-create, edit or share the plugin as long as you maintain the same open licensing.