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_freeze/posts/r_rstudio/new_post_2/post_2/execute-results/html.json

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+    "markdown": "---\ntitle: \"The Basics of R and RStudio\"\nsubtitle: \"Part 1: Simple Arithmetic\"\nauthor: \"William Okech\"\ndate: \"2022-06-15\"\nimage: \"r_and_rstudio.png\"\ncategories: [RStudio, R, Tutorial, Blog]\ntoc: true\ndraft: false\n---\n\n\n## Introduction\n\nThis is the first in a series of blog posts looking at the basics of R and RStudio. These programs allow us to perform various basic and complex calculations.\n\nTo get started, first, we will open R or RStudio. In R, go to the console, and in RStudio, head to the console pane. Next, type in a basic arithmetic calculation such as \"1 + 1\" after the angle bracket (\\>) and hit \"Enter.\"\n\nAn example of a basic calculation:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n1+1\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 2\n```\n:::\n:::\n\n\nThe output will be observed next to the square bracket containing the number 1 (\\[1\\]).\n\n![](r_console_1plus1.png){fig-align=\"center\" width=\"90%\"}\n\nAdditionally, to include comments into the code block we use the hash (#) symbol. Anything written after the code block will be commented out and not run.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# A simple arithmetic calculation (which is not run because of the hash symbol)\n1+1\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 2\n```\n:::\n:::\n\n\n## Arithmetic operators available in R/RStudio\n\nVarious arithmetic operators (listed below) can be used in R/RStudio.\n\n| Arithmetic Operator |            Description             |\n|:-------------------:|:----------------------------------:|\n|         \\+          |              Addition              |\n|         \\-          |            Subtraction             |\n|         \\*          |           Multiplication           |\n|          /          |              Division              |\n|     \\*\\* or \\^      |           Exponentiation           |\n|         %%          | Modulus (remainder after division) |\n|         %/%         |          Integer division          |\n\n## Examples\n\n### Addition\n\n\n::: {.cell}\n\n```{.r .cell-code}\n10+30\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 40\n```\n:::\n:::\n\n\n### Subtraction\n\n\n::: {.cell}\n\n```{.r .cell-code}\n30-24\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 6\n```\n:::\n:::\n\n\n### Multiplication\n\n\n::: {.cell}\n\n```{.r .cell-code}\n20*4\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 80\n```\n:::\n:::\n\n\n### Division\n\n\n::: {.cell}\n\n```{.r .cell-code}\n93/4\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 23.25\n```\n:::\n:::\n\n\n### Exponentiation\n\n\n::: {.cell}\n\n```{.r .cell-code}\n3^6\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 729\n```\n:::\n:::\n\n\n### Modulus (remainder with division)\n\n\n::: {.cell}\n\n```{.r .cell-code}\n94%%5\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 4\n```\n:::\n:::\n\n\n### Integer Division\n\n\n::: {.cell}\n\n```{.r .cell-code}\n54%/%7\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 7\n```\n:::\n:::\n\n\n### Slightly more complex arithmetic operations\n\n\n::: {.cell}\n\n```{.r .cell-code}\n5-1+(4*3)/16*3\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 6.25\n```\n:::\n:::\n",
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_freeze/posts/r_rstudio/new_post_3/post_3/execute-results/html.json

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+    "markdown": "---\ntitle: \"The Basics of R and RStudio\"\nsubtitle: \"Part 2: Variables\"\nauthor: \"William Okech\"\ndate: \"2022-06-22\"\nimage: \"r_and_rstudio.png\"\ncategories: [RStudio, R, Tutorial, Blog]\ntoc: true\ndraft: false\n---\n\n\n## Introduction\n\nVariables are instrumental in programming because they are used as \"containers\" to store data values.\n\nTo assign a value to a variable, we can use `<−` or `=`. However, most R users prefer to use `<−`.\n\n## Variable assignment\n\n### 1. Using `<-`\n\n\n::: {.cell}\n\n```{.r .cell-code}\nvariable_1 <- 5\nvariable_1\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 5\n```\n:::\n:::\n\n\n### 2. Using `=`\n\n\n::: {.cell}\n\n```{.r .cell-code}\nvariable_2 = 10\nvariable_2\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 10\n```\n:::\n:::\n\n\n### 3. Reverse the value and variable with `->`\n\n\n::: {.cell}\n\n```{.r .cell-code}\n15 -> variable_3\nvariable_3\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 15\n```\n:::\n:::\n\n\n### 4. Assign two variables to one value\n\n\n::: {.cell}\n\n```{.r .cell-code}\nvariable_4 <- variable_5 <- 30\nvariable_4\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 30\n```\n:::\n\n```{.r .cell-code}\nvariable_5\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 30\n```\n:::\n:::\n\n\n## Variable output\n\nThe output of the variable can then be obtained by:\n\n1.  Typing the variable name and then pressing \"Enter,\"\n2.  Typing \"print\" with the variable name in brackets, `print(variable)`, and\n3.  Typing \"View\" with the variable name in brackets, `View(variable)`.\n\nBoth `print()` and `View()` are some of the many built-in functions[^1] available in R.\n\n[^1]: Functions are a collection of statements (organized and reusable code) that perform a specific task, and R has many built-in functions.\n\nIn RStudio, the list of variables that have been loaded can be viewed in the environment pane.\n\n![](env_pane_1.png){fig-align=\"center\" width=\"90%\"}\n\nFigure 1: A screenshot of the environment pane with the stored variables.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nprint(variable_1)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 5\n```\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nView(variable_2)\n```\n:::\n\n\nOutput of `View()` will be seen in the script pane\n\n## The `assign()` and `rm()` functions\n\nIn addition to using the assignment operators (`<-` and `=`), we can use the `assign()` function to assign a value to a variable.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nassign(\"variable_6\", 555)\nvariable_6\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 555\n```\n:::\n:::\n\n\nTo remove the assignment of the value to the variable, either delete the variable in the \"environment pane\" or use the `rm()` function.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nvariable_7 <- 159\n```\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\nrm(variable_7)\n```\n:::\n\n\nAfter running `rm()` look at the environment pane to confirm whether `variable_7` has been removed.\n\n## Naming variables\n\nAt this point, you may be wondering what conventions are used for naming variables. First, variables need to have meaningful names such as current_temp, time_24_hr, or weight_lbs. However, we need to be mindful of the [variable](https://web.stanford.edu/class/cs109l/unrestricted/resources/google-style.html) [style guide](http://adv-r.had.co.nz/Style.html) which provides us with the appropriate rules for naming variables.\n\nSome rules to keep in mind are:\n\n1.  R is case-sensitive (`variable` is not the same as `Variable`),\n2.  Names similar to typical outputs or functions (`TRUE`, `FALSE`, `if`, or `else`) cannot be used,\n3.  Appropriate variable names can contain letters, numbers, dots, and underscores. However, you cannot start with an underscore, number, or dot followed by a number.\n\n## Valid and invalid names\n\n### Valid names:\n\n-   time_24_hr\n-   .time24_hr\n\n### Invalid names:\n\n-   \\_24_hr.time\n-   24_hr_time\n-   .24_hr_time\n",
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_freeze/posts/r_rstudio/new_post_4/post_4/execute-results/html.json

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+    "markdown": "---\ntitle: \"The Basics of R and RStudio\"\nsubtitle: \"Part 3: Data Types\"\nauthor: \"William Okech\"\ndate: \"2022-06-23\"\nimage: \"r_and_rstudio.png\"\ncategories: [RStudio, R, Tutorial, Blog]\ntoc: true\ndraft: false\n---\n\n\n## Introduction\n\nR and RStudio utilize multiple data types to store different kinds of data.\n\nThe most common data types in R are listed below.\n\n| **Data Type** | **Description**                                                                                                                                                                           |\n|---------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Numeric       | The most common data type. The values can be numbers or decimals (all real numbers).                                                                                                      |\n| Integer       | Special case of numeric data without decimals.                                                                                                                                            |\n| Logical       | Boolean data type with only 2 values (`TRUE` or `FALSE`).                                                                                                                                 |\n| Complex       | Specifies imaginary values in R.                                                                                                                                                          |\n| Character     | Assigns a character or string to a variable. The character variables are enclosed in single quotes ('character') while the string variables are enclosed in double quotes (\"string\").     |\n| Factor        | Special type of character variable that represents a categorical such as gender.                                                                                                          |\n| Raw           | Specifies values as raw bytes. It uses built-in functions to convert between raw and character (charToRaw() or rawToChar()).                                                              |\n| Dates         | Specifies the date variable. Date stores a date and POSIXct stores a date and time. The output is indicated as the number of days (Date) or number of seconds (POSIXct) since 01/01/1970. |\n\n## Data types\n\n### 1. Numeric\n\n\n::: {.cell}\n\n```{.r .cell-code}\n89.98\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 89.98\n```\n:::\n\n```{.r .cell-code}\n55\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 55\n```\n:::\n:::\n\n\n### 2. Integer\n\n\n::: {.cell}\n\n```{.r .cell-code}\n5L\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 5\n```\n:::\n\n```{.r .cell-code}\n5768L\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 5768\n```\n:::\n:::\n\n\n### 3. Logical\n\n\n::: {.cell}\n\n```{.r .cell-code}\nTRUE\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] TRUE\n```\n:::\n\n```{.r .cell-code}\nFALSE\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] FALSE\n```\n:::\n:::\n\n\n### 4. Complex\n\n\n::: {.cell}\n\n```{.r .cell-code}\n10 + 30i\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 10+30i\n```\n:::\n\n```{.r .cell-code}\n287 + 34i\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 287+34i\n```\n:::\n:::\n\n\n### 5. Character or String\n\n\n::: {.cell}\n\n```{.r .cell-code}\n'abc'\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"abc\"\n```\n:::\n\n```{.r .cell-code}\n\"def\"\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"def\"\n```\n:::\n\n```{.r .cell-code}\n\"I like learning R\"\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"I like learning R\"\n```\n:::\n:::\n\n\n### 6. Dates\n\n\n::: {.cell}\n\n```{.r .cell-code}\n\"2022-06-23 14:39:21 EAT\"\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"2022-06-23 14:39:21 EAT\"\n```\n:::\n\n```{.r .cell-code}\n\"2022-06-23\"\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"2022-06-23\"\n```\n:::\n:::\n\n\n## Examining various data types\n\nSeveral functions exist to examine the features of the various data types. These include:\n\n1.  `typeof()` -- what is the data type of the object (low-level)?\n2.  `class()` -- what is the data type of the object (high-level)?\n3.  `length()` -- how long is the object?\n4.  `attributes()` -- any metadata available?\n\nLet's look at how these functions work with a few examples\n\n\n::: {.cell}\n\n```{.r .cell-code}\na <- 45.84\nb <- 858L\nc <- TRUE\nd <- 89 + 34i\ne <- 'abc'\n```\n:::\n\n\n### 1. Examine the data type at a low-level with `typeof()`\n\n\n::: {.cell}\n\n```{.r .cell-code}\ntypeof(a)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"double\"\n```\n:::\n\n```{.r .cell-code}\ntypeof(b)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"integer\"\n```\n:::\n\n```{.r .cell-code}\ntypeof(c)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"logical\"\n```\n:::\n\n```{.r .cell-code}\ntypeof(d)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"complex\"\n```\n:::\n\n```{.r .cell-code}\ntypeof(e)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"character\"\n```\n:::\n:::\n\n\n### 2. Examine the data type at a high-level with `class()`\n\n\n::: {.cell}\n\n```{.r .cell-code}\nclass(a)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"numeric\"\n```\n:::\n\n```{.r .cell-code}\nclass(b)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"integer\"\n```\n:::\n\n```{.r .cell-code}\nclass(c)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"logical\"\n```\n:::\n\n```{.r .cell-code}\nclass(d)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"complex\"\n```\n:::\n\n```{.r .cell-code}\nclass(e)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"character\"\n```\n:::\n:::\n\n\n### 3. Use the `is.____()` functions to determine the data type\n\nTo test whether the variable is of a specific type, we can use the `is.____()` functions.\n\nFirst, we test the variable `a` which is numeric.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nis.numeric(a)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] TRUE\n```\n:::\n\n```{.r .cell-code}\nis.integer(a)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] FALSE\n```\n:::\n\n```{.r .cell-code}\nis.logical(a)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] FALSE\n```\n:::\n\n```{.r .cell-code}\nis.character(a)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] FALSE\n```\n:::\n:::\n\n\nSecond, we test the variable `c` which is logical.\n\n\n::: {.cell}\n\n```{.r .cell-code}\nis.numeric(c)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] FALSE\n```\n:::\n\n```{.r .cell-code}\nis.integer(c)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] FALSE\n```\n:::\n\n```{.r .cell-code}\nis.logical(c)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] TRUE\n```\n:::\n\n```{.r .cell-code}\nis.character(c)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] FALSE\n```\n:::\n:::\n\n\n## Converting between various data types\n\nTo convert between data types we can use the `as.____()` functions. These include: `as.Date()`, `as.numeric()`, and `as.factor()`. Additionally, other helpful functions include factor() which adds levels to the data and `nchar()` which provides the length of the data.\n\n### Examples\n\n\n::: {.cell}\n\n```{.r .cell-code}\nas.integer(a)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 45\n```\n:::\n\n```{.r .cell-code}\nas.logical(0)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] FALSE\n```\n:::\n\n```{.r .cell-code}\nas.logical(1)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] TRUE\n```\n:::\n\n```{.r .cell-code}\nnchar(e)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 3\n```\n:::\n:::\n",
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_freeze/posts/r_rstudio_basics/arithmetic/arithmetic/execute-results/html.json

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+    "markdown": "---\ntitle: \"The Basics of R and RStudio\"\nsubtitle: \"Part 1: Simple Arithmetic\"\nauthor: \"William Okech\"\ndate: \"2022-06-15\"\nimage: \"r_and_rstudio.png\"\ncategories: [RStudio, R, Tutorial, Blog]\ntoc: true\ndraft: false\n---\n\n\n## Introduction\n\nThis is the first in a series of blog posts looking at the basics of R and RStudio. These programs allow us to perform various basic and complex calculations.\n\nTo get started, first, we will open R or RStudio. In R, go to the console, and in RStudio, head to the console pane. Next, type in a basic arithmetic calculation such as \"1 + 1\" after the angle bracket (\\>) and hit \"Enter.\"\n\nAn example of a basic calculation:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n1+1\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 2\n```\n:::\n:::\n\n\nThe output will be observed next to the square bracket containing the number 1 (\\[1\\]).\n\n![](r_console_1plus1.png){fig-align=\"center\" width=\"90%\"}\n\nAdditionally, to include comments into the code block we use the hash (#) symbol. Anything written after the code block will be commented out and not run.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# A simple arithmetic calculation (which is not run because of the hash symbol)\n1+1\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 2\n```\n:::\n:::\n\n\n## Arithmetic operators available in R/RStudio\n\nVarious arithmetic operators (listed below) can be used in R/RStudio.\n\n| Arithmetic Operator |            Description             |\n|:-------------------:|:----------------------------------:|\n|         \\+          |              Addition              |\n|         \\-          |            Subtraction             |\n|         \\*          |           Multiplication           |\n|          /          |              Division              |\n|     \\*\\* or \\^      |           Exponentiation           |\n|         %%          | Modulus (remainder after division) |\n|         %/%         |          Integer division          |\n\n## Examples\n\n### Addition\n\n\n::: {.cell}\n\n```{.r .cell-code}\n10+30\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 40\n```\n:::\n:::\n\n\n### Subtraction\n\n\n::: {.cell}\n\n```{.r .cell-code}\n30-24\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 6\n```\n:::\n:::\n\n\n### Multiplication\n\n\n::: {.cell}\n\n```{.r .cell-code}\n20*4\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 80\n```\n:::\n:::\n\n\n### Division\n\n\n::: {.cell}\n\n```{.r .cell-code}\n93/4\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 23.25\n```\n:::\n:::\n\n\n### Exponentiation\n\n\n::: {.cell}\n\n```{.r .cell-code}\n3^6\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 729\n```\n:::\n:::\n\n\n### Modulus (remainder with division)\n\n\n::: {.cell}\n\n```{.r .cell-code}\n94%%5\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 4\n```\n:::\n:::\n\n\n### Integer Division\n\n\n::: {.cell}\n\n```{.r .cell-code}\n54%/%7\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 7\n```\n:::\n:::\n\n\n### Slightly more complex arithmetic operations\n\n\n::: {.cell}\n\n```{.r .cell-code}\n5-1+(4*3)/16*3\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] 6.25\n```\n:::\n:::\n",
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