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Stub 2 (Using R)

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    1981

    • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    R Session: NOT STARTED

    Query \(\PageIndex{1}\)

    (unable to fetch text document from uri [status: 403 (Forbidden)]) 
    print('hello world')
    [1] "hello world"

    Original text created by N. Matloff.

    print('somthing test')
    Hello world!

    Lesson 1: First R Steps

    The R command prompt is '>'. Again, it will be shown here, but you don't type it. It is just there in your R window to let you know R is inviting you to submit a command. (If you are using RStudio, you'll see it in the Console pane.) So, just type '1+1' then hit Enter. Sure enough, it prints out 2 (you were expecting maybe 12108?):

    \[ E =mc^2 \label{Einstein} \] See equation \ref{Einstein}

    But what is that '[1]' here? It's just a row label. We'll go into that later, not needed quite yet. R includes a number of built-in datasets, mainly for illustration purposes. One of them is Nile, 100 years of annual flow data on the Nile River. Let's find the mean flow:

    mean(Nile) + 10
    929.35

    Here mean is an example of an R function, and in this case Nile is an argument -- fancy way of saying "input" -- to that function. That output, 919.35, is called the return value or simply value. The act of running the function is termed calling the function.

    Another point to note is that we didn't need to call R's print function. We could have typed,

    print(mean(Nile))
     

    but whenever we are at the R '>' prompt, any expression we type will be printed out.

    Since there are only 100 data points here, it's not unwieldy to print them out:

    Nile
    A Time Series:
    1. 1120
    2. 1160
    3. 963
    4. 1210
    5. 1160
    6. 1160
    7. 813
    8. 1230
    9. 1370
    10. 1140
    11. 995
    12. 935
    13. 1110
    14. 994
    15. 1020
    16. 960
    17. 1180
    18. 799
    19. 958
    20. 1140
    21. 1100
    22. 1210
    23. 1150
    24. 1250
    25. 1260
    26. 1220
    27. 1030
    28. 1100
    29. 774
    30. 840
    31. 874
    32. 694
    33. 940
    34. 833
    35. 701
    36. 916
    37. 692
    38. 1020
    39. 1050
    40. 969
    41. 831
    42. 726
    43. 456
    44. 824
    45. 702
    46. 1120
    47. 1100
    48. 832
    49. 764
    50. 821
    51. 768
    52. 845
    53. 864
    54. 862
    55. 698
    56. 845
    57. 744
    58. 796
    59. 1040
    60. 759
    61. 781
    62. 865
    63. 845
    64. 944
    65. 984
    66. 897
    67. 822
    68. 1010
    69. 771
    70. 676
    71. 649
    72. 846
    73. 812
    74. 742
    75. 801
    76. 1040
    77. 860
    78. 874
    79. 848
    80. 890
    81. 744
    82. 749
    83. 838
    84. 1050
    85. 918
    86. 986
    87. 797
    88. 923
    89. 975
    90. 815
    91. 1020
    92. 906
    93. 901
    94. 1170
    95. 912
    96. 746
    97. 919
    98. 718
    99. 714
    100. 740

    Now you can see how the row labels work. There are 15 numbers per row here, so the second row starts with the 16th, indicated by '[16]'.

    R has great graphics, not only in base R but also in wonderful user-contributed packages, such as ggplot2 and lattice. But we'll stick with base-R graphics for now, and save the more powerful yet more complex ggplot2 for a later lesson.

    We'll start with a very simple, non-dazzling one, a no-frills histogram:

    plot(Nile)