# r_users_group_2 / exercises /

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```                                README
======

Author: Tavis Rudd
Date: 2011-05-17 18:21:34 PDT

=================
1 Resources
2 hello world
3 hello.world function
4 create an anonymous version of the same function
5 use Google to figure out what R's rules are for naming variables and functions
6 hello(name) function
7 hello(name) with a default argument
8 create a `vector` of the following strings and assign it to a variable
9 use help.search to find a function that can convert each element in that vector to uppercase
10 find a function that will give you the length of the vector
11 figure out the syntax to get the third element in the vector
12 create a function that applies another function to each element in a vector
13 find a function that will create a sequence of integers
14 use that function and the `matrix` function to create a 4 x 5 matrix of the first 20 natural numbers
15 figure out the syntax to get the matrix element at row 2, col 3
16 multiply every element in the matrix by 3
17 find a function that gives you the dimensions of the matrix
18 convert this matrix to a vector
19 create a Boolean matrix of the same size
20 use the Boolean matrix to take a subset of our first matrix
21 what are the type and dimensions of the subset
22 figure out how to create a random sample of 100 integers
23 take a random sample of five elements from your first matrix
24 find a way to sort the result of that sampling
25 create a `list` that contains the letters of English and
26 find the built-in dataset `swiss` and the help information about it
27 what are the `type`, `dimensions`, `structure`, and `dimension names` of this dataset
28 figure out how to access each column of this dataset individually
29 show the first and last six elements of this dataset
30 what are the types of the columns in `swiss`
31 create a subset of swiss that only includes the columns Catholic and Fertility
32 create a subset only showing the regions that are at least 50% Catholic
33 use the functions that Isabella mentioned to examine the swiss data
34 look at the `airquality` built-in dataset and create a subset without the NA Ozone values removed
35 plot the various dimensions of the airquality dataset
36.1 work in groups to choose some line-based log data (like apache logs, syslog, etc.)
36.2 use `awk`, `perl`, `sed` or similar to select a subset (match a regular expression) and output csv
36.3 save the output into a csv file and then import into R
36.4 use what you've learnt so far to explore, summarize and plot the data

1 Resources
------------

- type ? followed by a function name to see built-in help

- help.search function

2 hello world
--------------
Start the R interpreter and print the string "hello world"

3 hello.world function
-----------------------
Create a function called hello.world that does what you did manually
in the previous exercise.

4 create an anonymous version of the same function
---------------------------------------------------

5 use Google to figure out what R's rules are for naming variables and functions
---------------------------------------------------------------------------------

6 hello(name) function
-----------------------
Create a variant of the previous function that accepts a `name`
parameter and prints "Hello Mary", "Hello Lamb", etc.

Hint: you'll need to figure out how to concatenate/join strings

7 hello(name) with a default argument
--------------------------------------
Give the `name` argument a default value.

8 create a `vector` of the following strings and assign it to a variable
-------------------------------------------------------------------------

9 use help.search to find a function that can convert each element in that vector to uppercase
-----------------------------------------------------------------------------------------------

10 find a function that will give you the length of the vector
---------------------------------------------------------------

11 figure out the syntax to get the third element in the vector
----------------------------------------------------------------

12 create a function that applies another function to each element in a vector
-------------------------------------------------------------------------------

13 find a function that will create a sequence of integers
-----------------------------------------------------------
This is like the `range` function in Python.

14 use that function and the `matrix` function to create a 4 x 5 matrix of the first 20 natural numbers
--------------------------------------------------------------------------------------------------------

15 figure out the syntax to get the matrix element at row 2, col 3
-------------------------------------------------------------------

16 multiply every element in the matrix by 3
---------------------------------------------

17 find a function that gives you the dimensions of the matrix
---------------------------------------------------------------

18 convert this matrix to a vector
-----------------------------------

19 create a Boolean matrix of the same size
--------------------------------------------
... that indicates whether the elements in our first matrix are > 13

20 use the Boolean matrix to take a subset of our first matrix
---------------------------------------------------------------
... where the condition is true
... and where it is false

21 what are the type and dimensions of the subset
--------------------------------------------------

22 figure out how to create a random sample of 100 integers
------------------------------------------------------------

23 take a random sample of five elements from your first matrix
----------------------------------------------------------------

24 find a way to sort the result of that sampling
--------------------------------------------------

25 create a `list` that contains the letters of English and
------------------------------------------------------------
... and their position in the alphabet as separate fields

hint: letters is a constant built-in to R

26 find the built-in dataset `swiss` and the help information about it
-----------------------------------------------------------------------

27 what are the `type`, `dimensions`, `structure`, and `dimension names` of this dataset
-----------------------------------------------------------------------------------------

28 figure out how to access each column of this dataset individually
---------------------------------------------------------------------

29 show the first and last six elements of this dataset
--------------------------------------------------------
hint: there are built in functions that will do this for you

30 what are the types of the columns in `swiss`
------------------------------------------------

31 create a subset of swiss that only includes the columns Catholic and Fertility
----------------------------------------------------------------------------------

32 create a subset only showing the regions that are at least 50% Catholic
---------------------------------------------------------------------------

33 use the functions that Isabella mentioned to examine the swiss data
-----------------------------------------------------------------------

34 look at the `airquality` built-in dataset and create a subset without the NA Ozone values removed
-----------------------------------------------------------------------------------------------------

35 plot the various dimensions of the airquality dataset
---------------------------------------------------------

---------------------

36.1 work in groups to choose some line-based log data (like apache logs, syslog, etc.)
========================================================================================

36.2 use `awk`, `perl`, `sed` or similar to select a subset (match a regular expression) and output csv
========================================================================================================

36.3 save the output into a csv file and then import into R
============================================================

36.4 use what you've learnt so far to explore, summarize and plot the data
===========================================================================
```
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