.hi-grey[原住民族資料分析線上訓練工作坊：R的基礎與應用]

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# .hi-grey[原住民族資料分析線上訓練工作坊：R的基礎與應用]
## .smallest.hi-slate[第一週]
### .hi-slate[Kacing 廖彥傑]
### .smallest[英國艾賽克斯大學博士候選人]

---

exclude: true

---
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# 課程設計
---
name:
&nbsp;

### 我們課程主要包括：

- 作業環境、基礎R語言、資料結構與套件導入、R的社群生態

- 向量(vector)、序列（list）、矩陣（matrix）、資料框架（dataframe）

- 資料類型結構、Tidyverse 相關模組 、函數式編程 (functional programming)、循環

- 資料視覺化EDA (explore data analysis) 、基礎統計分析與回歸、討論個人研究計畫

- 用R檢視地圖資料、製作互動式地圖、文本分析與應用、基礎機器學習

---
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# 目的
---
name:

&nbsp;

### 為什麼我們要學習資料科學？

- 人工智能對政府部門運作、變革與影響

- 如果當政府部門開始用人工智能進行政策制定與評估時，會需要資料來建立模型。

- 原住民資料與代表性的問題？哪一天我們的政策會不會也被機器決定？

---

&nbsp;

---

&nbsp;

### 希望完成課程，大家都能夠：
- 基礎的資料分析知識

- 獨立用R完成分析

- 應用這些知識在自己的研究或工作計畫上

- 持續進修

---
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class: inverse, center, middle

# 開使吧！

---
layout: true
# 基礎（Some Basics）
---
name:

### 列印

```r
print("Hello World")
```

```
#> [1] "Hello World"
```

```r
print(pi)
```

```
#> [1] 3.141593
```

```r
print(sqrt(2))
```

```
#> [1] 1.414214
```

---

```r
print(matrix(c(1, 2, 3, 4), 2, 2))
```

```
#>      [,1] [,2]
#> [1,]    1    3
#> [2,]    2    4
```

```r
print(list("a", "b", "c"))
```

```
#> [[1]]
#> [1] "a"
#> 
#> [[2]]
#> [1] "b"
#> 
#> [[3]]
#> [1] "c"
```

```r
print("The zero occurs at", 2 * pi, "radians.")
```

```r
num <- readline(prompt="有多少人: ")
cat("\n", "原住民族資料分析線上訓練工作坊：R的基礎與應用", "\n" ,"總共有", num, "\n")
```

---

### 建立變數

```r
x <- 3
```

```r
x <- 3
y <- 4
z <- sqrt(x + y) 
```

```r
print(z)
```

```
#> [1] 2.645751
```

```r
x <- c("Lbak", "Uking", "是", "Truku") 
```

```r
print(x)
```

```
#> [1] "Lbak"  "Uking" "是"    "Truku"
```

---

### 列出變數

```r
x <- 10
y <- 50
z <- c("Kacing", "David", "Liao")
```

```r
ls()
```

```
#>  [1] "black"          "blue"           "blue_green"     "brown"         
#>  [5] "green"          "grey_dark"      "grey_light"     "grey_mid"      
#>  [9] "magenta_green"  "magenta_red"    "magenta_yellow" "orange"        
#> [13] "purple"         "red"            "red_green"      "red_pink"      
#> [17] "turquoise"      "x"              "y"              "z"
```

---

```r
ls.str()
```

```
#> black :  chr "#000000"
#> blue :  chr "#3b3b9a"
#> blue_green :  chr "#4d599b"
#> brown :  chr "#9b684d"
#> green :  chr "#8bb174"
#> grey_dark :  chr "grey20"
#> grey_light :  chr "grey70"
#> grey_mid :  chr "grey50"
#> magenta_green :  chr "#4d9b68"
#> magenta_red :  chr "#9b4d80"
#> magenta_yellow :  chr "#9b8f4d"
#> orange :  chr "#FFA500"
#> purple :  chr "#6A5ACD"
#> red :  chr "#fb6107"
#> red_green :  chr "#9b4d59"
#> red_pink :  chr "#e64173"
#> turquoise :  chr "#20B2AA"
#> x :  num 10
#> y :  num 50
#> z :  chr [1:3] "Kacing" "David" "Liao"
```

---

### 刪除變數

```r
david <- "David is hot "
rm(x)
```

```r
rm(david, y, z)
```

```r
ls()
```

```r
rm(list = ls())
ls()
```

```
#> character(0)
```

---

### 製造簡單向量 (Vector)

```r
c(1, 1, 2, 3, 5, 8, 13, 21)
```

```
#> [1]  1  1  2  3  5  8 13 21
```

```r
c("好想", "吃", "momo", "paradise")
```

```
#> [1] "好想"     "吃"       "momo"     "paradise"
```

```r
c(TRUE, TRUE, FALSE, TRUE)
```

```
#> [1]  TRUE  TRUE FALSE  TRUE
```

---

### 製造簡單序列 (Sequences)

```r
1:100
```

```
#>   [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
#>  [19]  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
#>  [37]  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
#>  [55]  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72
#>  [73]  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90
#>  [91]  91  92  93  94  95  96  97  98  99 100
```

```r
100:1
```

```
#>   [1] 100  99  98  97  96  95  94  93  92  91  90  89  88  87  86  85  84  83
#>  [19]  82  81  80  79  78  77  76  75  74  73  72  71  70  69  68  67  66  65
#>  [37]  64  63  62  61  60  59  58  57  56  55  54  53  52  51  50  49  48  47
#>  [55]  46  45  44  43  42  41  40  39  38  37  36  35  34  33  32  31  30  29
#>  [73]  28  27  26  25  24  23  22  21  20  19  18  17  16  15  14  13  12  11
#>  [91]  10   9   8   7   6   5   4   3   2   1
```

---

```r
seq(from=1,to=100)
```

```r
seq(from=1,to=100,by=2)
```

```
#>  [1]  1  3  5  7  9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49
#> [26] 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99
```

---

```r
seq(from = 0, to = 100, length.out = 5)
```

```
#> [1]   0  25  50  75 100
```

```r
rep(1, times = 5)
```

```
#> [1] 1 1 1 1 1
```

---
layout: true
# 比較(Comparison)
---
name:

&nbsp;

### 語法

|     |          定義           |  
|-----|-------------------------|
| ==  | 等於                    | 
| !=  | 不等於                  |   
| <   | 小於                    |  
| >   | 大於                    |  
| <=  | 小於等於                |  
| >=  | 大於等於                |

---

### 條件比較

```r
a <- 10
b <- 11
a == b 
```

```
#> [1] FALSE
```

```r
a != b
```

```
#> [1] TRUE
```

```r
a > b
```

```
#> [1] FALSE
```

```r
a < b
```

```
#> [1] TRUE
```

```r
a >= b
```

```
#> [1] FALSE
```

---

```r
v <- c(3, "david", 4)
w <- c("david", "david", 1)
```

```r
v == w 
```

```
#> [1] FALSE  TRUE FALSE
```

```r
v != w
```

```
#> [1]  TRUE FALSE  TRUE
```

```r
v < w
```

```
#> [1]  TRUE FALSE FALSE
```

```r
v <= w
```

```
#> [1]  TRUE  TRUE FALSE
```

---

```r
v > w
```

```
#> [1] FALSE FALSE  TRUE
```

```r
v >= w
```

```
#> [1] FALSE  TRUE  TRUE
```

```r
v <- c(3, 3, 4)
v == 4
```

```
#> [1] FALSE FALSE  TRUE
```

```r
v != 4
```

```
#> [1]  TRUE  TRUE FALSE
```

---

```r
a <- 1:10
```

```r
a > 5
```

```
#>  [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
```

```r
a < 5
```

```
#>  [1]  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE
```

```r
a == 5
```

```
#>  [1] FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE
```

---

```r
all(a > 5) 
```

```
#> [1] FALSE
```

```r
any(a > 5) 
```

```
#> [1] TRUE
```

```r
b <- a > 5
```

```r
any(b)
```

```
#> [1] TRUE
```

```r
all(b)
```

```
#> [1] FALSE
```

---

```r
c <- c(a, NA)
c > 5
```

```
#>  [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE    NA
```

```r
all(c > 5) 
```

```
#> [1] FALSE
```

```r
any(c > 5) 
```

```
#> [1] TRUE
```

```r
all(c < 20) 
```

```
#> [1] NA
```

```r
any(c > 20) 
```

```
#> [1] NA
```

---

```r
is.na(a)
```

```
#>  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
```

```r
is.na(c)
```

```
#>  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
```

```r
any(is.na(c))
```

```
#> [1] TRUE
```

```r
all(is.na(c))
```

```
#> [1] FALSE
```

---

### 提取資料（Selecting Vector Elements）

```r
truku <- 1:10
truku
```

```
#>  [1]  1  2  3  4  5  6  7  8  9 10
```

```r
truku[1]
```

```
#> [1] 1
```

```r
truku[2]
```

```
#> [1] 2
```

---

```r
truku[1:3]
```

```
#> [1] 1 2 3
```

```r
truku[c(2, 5, 10)]
```

```
#> [1]  2  5 10
```

---

```r
truku[-1] # Ignore first element
```

```
#> [1]  2  3  4  5  6  7  8  9 10
```

```r
truku[1:3] # As before
```

```
#> [1] 1 2 3
```

```r
truku[-(1:3)] # Invert sign of index to exclude instead of select #> [1] 2 3 5 8 13 21 34
```

```
#> [1]  4  5  6  7  8  9 10
```

```r
num <- truku < 5 # This vector is TRUE wherever fib is less than 10

truku[num]
```

```
#> [1] 1 2 3 4
```

---

```r
v <- c(3,6,1,9,11,16,0,3,1,45,2,8,9,6,-4) 
v[ v > median(v)]
```

```
#> [1]  9 11 16 45  8  9
```

```r
v[ (v < quantile(v, 0.05)) | (v > quantile(v, 0.95)) ]
```

```
#> [1] 45 -4
```

```r
v[ abs(v - mean(v)) > sd(v)]
```

```
#> [1] 45 -4
```

```r
v<-c(1,2,3,NA,5) 
v[!is.na(v) & !is.null(v)]
```

```
#> [1] 1 2 3 5
```

---

```r
years <- c(1986, 1964, 1976, 1994)
names(years) <- c("Kennedy", "Johnson", "Carter", "Clinton")
years
```

```
#> Kennedy Johnson  Carter Clinton 
#>    1986    1964    1976    1994
```

```r
years["Carter"]
```

```
#> Carter 
#>   1976
```

```r
years[1]
```

```
#> Kennedy 
#>    1986
```

```r
years[c("Carter", "Clinton")]
```

```
#>  Carter Clinton 
#>    1976    1994
```

---
layout: true
# 算數（Arithmetic）
---
name:

### 基本加減乘除

```r
v <- c(11, 12, 13, 14, 15) 
w <- c(1,2,3,4,5) 
```

```r
v + w
```

```
#> [1] 12 14 16 18 20
```

```r
v * w
```

```
#> [1] 11 24 39 56 75
```

```r
v / w
```

```
#> [1] 11.000000  6.000000  4.333333  3.500000  3.000000
```

---

```r
w
```

```
#> [1] 1 2 3 4 5
```

```r
w + 2
```

```
#> [1] 3 4 5 6 7
```

```r
w - 2
```

```
#> [1] -1  0  1  2  3
```

```r
w * 2
```

```
#> [1]  2  4  6  8 10
```

```r
w / 2
```

```
#> [1] 0.5 1.0 1.5 2.0 2.5
```

---
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# 預告
---
name:

##### 參考書目：R Cookbook Proven Recipes for Data Analysis, Statistics, and Graphics by J. D. Long, Paul Teetor