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Connections: Interfaces to the Outside World

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R-Programmierung

Johns Hopkins University

4.6 (14,524 ratings) | 410K Students Enrolled

Kurs 1 von 10 in Datenverarbeitung Spezialisierung

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

Lehrplan anzeigen

Skills You'll Learn

Data Analysis, Debugging, R Programming, Rstudio

Bewertungen

4.6 (14,524 ratings)

5 stars
10,057 ratings
4 stars
3,242 ratings
3 stars
785 ratings
2 stars
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1 star
194 ratings

AK

May 27, 2017

This was very engaging, however, the level of expectation and effort needed is much greater than course 1 - ToolBox.\n\nThis is perhaps the best course on R Programming designed for a small duration.

GB

Feb 03, 2016

Excelente opportunity to learn a lot. The course is very well prepared introduce you to R programing. Dont feel bad if you dont get it at te first moment. It will be a process of leaning worth trying

Aus der Unterrichtseinheit

Week 1: Background, Getting Started, and Nuts & Bolts

This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story.

Introduction1:20

Overview and History of R16:07

Getting Help13:53

R Console Input and Evaluation4:46

Data Types - R Objects and Attributes4:43

Data Types - Vectors and Lists6:27

Data Types - Matrices3:24

Data Types - Factors4:31

Data Types - Missing Values2:10

Data Types - Data Frames2:44

Data Types - Names Attribute1:49

Data Types - Summary0:43

Reading Tabular Data5:51

Reading Large Tables7:08

Textual Data Formats4:58

Connections: Interfaces to the Outside World4:35

Subsetting - Basics4:13

Subsetting - Lists4:45

Subsetting - Matrices2:50

Subsetting - Partial Matching1:42

Subsetting - Removing Missing Values3:59

Vectorized Operations3:46

Unterrichtet von

Roger D. Peng, PhD
Associate Professor, Biostatistics
Jeff Leek, PhD
Associate Professor, Biostatistics
Brian Caffo, PhD
Professor, Biostatistics

Skript

So there are a variety of ways that you can interface between R, R,

wi, with the outside world.

And generally speaking there are functions that, that are used to kind of open up

the what are called connections to the outside world.

Usually you want to, the most common type of connection is to me,

is to a file, so for example if you want to read a file then you can,

you can create a file connection, you might want to for example o,

or read a compressed file, or that's a slight variation on that.

And most functions will do this in the background without you having to

know what's going on.

So for example, when you call read.table with it and

you pass it the name of a file, what it does behind the scenes is it

opens up a file connection to that file, and then reads from that file connection.

The connection can be made to other types of objects too.

For example, you can open a connection to a webpage using the URL function.

And so, when you open a connection to a webpage,

you can read data from that webpage using the URL connection.

And so, the idea behind the connection interface is, is that it kind of,

that it abstracts out.

The mechanism for connecting to different types of objects that are external to R,

whether they be files, or webpages, or whatever.

So the file function is the function that opens a connection to

a standard uncompressed file.

So this, this can be useful for

text files, for, for reading in other types of text files.

Gzfile and bzfile, are used for opening connections to compressed data files.

So gz file i, are, is used for files that are compressed with the gzip algorithm and

bz files used for, is for

opening connections to files compressed with the bzip2 algorithm.

Files that are compressed with gzip usually have a gz extension and

files compressed with bzip2 usually have a bz2 extension.

So the file function here has a few arguments,

the description argument is the name of the file and there's a flag that's called,

that goes to the open argument and you have to know what the codes are, but

basically r is for reading, w is for writing, a is for appending, and then rb,

wb and ab are for reading, writing, and appending on binary files.

The other options for file are not particularly important at this time.

So, connections can be very powerful and they can let you navigate files and

other external objects in a more sophisticated way than just,

like, reading the whole thing, for example.

And generally you don't have to deal with the connect interface in many cases, but

sometimes it's useful.

So for example, so here I've got a simple example or opening a fi, a file

connection to some file called foo.text, I'm going to open it for reading.

I can call read.csv on the connection, and

that by default will just read the entire file then I can close the connection.

So that three line process is the same as just calling read.csv on the file.

So in this case there was no need to use the connection to read the file.

However, sometimes a connection can be useful if you want to read parts of

a file.

So for example,

here I've got the readLines function which just reads lines from a text file.

And I'm going to open up this words.gz file.

So, this is a file that has words in it for it's like a dictionary file.

And it's compressed using the gz, the gzip algorithm.

So I'm going to be using the gz file function to open a connection to that.

And I'm just going to read the first ten lines.

So now I'm going to re,

use this connection, and to read the first ten lines.

And here, the first ten lines are printed out here

as you can see these are the first top ten words in the file.

And similarly, write lines is a,

is a function that can be used to write out lines of text to a file.

And each, and what you do is pass write lines of character vector and

each element of the character vector becomes a line in the text file.

You can also use readLines to read elements from a web page, so for example,

you can use the URL function to create a connection to a website, so

this website here is the Johns Hopkins School of Public Health website.

And I'm going to open the connection there for

reading, and then I'm going to read lines from this connection.

And so and I'm, and then and so the lines of text that come

from the connection are going to be stored in this character vector x.

So when I look at the first couple of lines from x you can

see that it looks like HTML which is kind of what you would expect.

And so the URL function is useful for

creating a connection to a kind of a non file object.

and then using read.lines is useful to read the text from that connection.

So this is another way to read data beyond using functions like

read.table or read.csv

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