Visualización de datos

# Visualización de datos
## Taller R Octubre 29
### Anabelle Laurent

---

# ¡Hola! 😄
--

En esta charla vamos a aprender como visualizar datos con ggplot2

---

### ¿ Porque la visualización de datos es importante ?

- Manera universal de **comunicar** información

- Dar un **mensaje claro y eficaz**.

- Encuentra **patrones, tendencias, detecta valores extremos**.

- Haga que los datos sean memorables

- Mantener el interés de la audiencia

---
### ¿Qué hace una buena visualización? 🤔

- Revela una **tendencia** o **relación** entre variables

- Siempre tenga como mínimo un **título**, **eje**, **escalas** y **símbolos**

- Símbolos distintos y legibles (es decir, use contraste)

- El título debe transmitir la mayor cantidad de información posible

- Sin ruido: mantenga la información al mínimo

- el **tipo de gráfico correcto** según el tipo de datos que se presentarán

---
class: inverse, middle, center

# Primero: ¿ que es ggplot2 ? 🤔

---

[Artwork by @allison_horst](https://github.com/allisonhorst/stats-illustrations)

---

Ayuda para todo el processo de ciencia de datos.  
Hoy vamos a explotar **ggplot2** que ayuda para la visualización de datos.

---
class: inverse, middle, center

# Primero, hacemos un grafico basico

---

```r
*paises
```
]
 
.panel2-ggplotex1-auto[

```
# A tibble: 1,704 × 6
   pais       continente  anio esperanza_de_vida poblacion pib_per_capita
   <fct>      <fct>      <int>             <dbl>     <int>          <dbl>
 1 Afganistán Asia        1952              28.8   8425333           779.
 2 Afganistán Asia        1957              30.3   9240934           821.
 3 Afganistán Asia        1962              32.0  10267083           853.
 4 Afganistán Asia        1967              34.0  11537966           836.
 5 Afganistán Asia        1972              36.1  13079460           740.
 6 Afganistán Asia        1977              38.4  14880372           786.
 7 Afganistán Asia        1982              39.9  12881816           978.
 8 Afganistán Asia        1987              40.8  13867957           852.
 9 Afganistán Asia        1992              41.7  16317921           649.
10 Afganistán Asia        1997              41.8  22227415           635.
# … with 1,694 more rows
```
]

---
count: false
 
Gráfico básico
.panel1-ggplotex1-auto[

```r
paises %>%
* ggplot()
```
]
 
.panel2-ggplotex1-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex1_auto_02_output-1.png)
]

---
count: false
 
Gráfico básico
.panel1-ggplotex1-auto[

```r
paises %>%
  ggplot() +
* aes(x = anio)
```
]
 
.panel2-ggplotex1-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex1_auto_03_output-1.png)
]

---
count: false
 
Gráfico básico
.panel1-ggplotex1-auto[

```r
paises %>%
  ggplot() +
  aes(x = anio) +
* aes(y = esperanza_de_vida)
```
]
 
.panel2-ggplotex1-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex1_auto_04_output-1.png)
]

---
count: false
 
Gráfico básico
.panel1-ggplotex1-auto[

```r
paises %>%
  ggplot() +
  aes(x = anio) +
  aes(y = esperanza_de_vida) +
* geom_point()
```
]
 
.panel2-ggplotex1-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex1_auto_05_output-1.png)
]

---
count: false
 
Gráfico básico
.panel1-ggplotex1-auto[

```r
paises %>%
  ggplot() +
  aes(x = anio) +
  aes(y = esperanza_de_vida) +
  geom_point() +
* xlab("Anio")
```
]
 
.panel2-ggplotex1-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex1_auto_06_output-1.png)
]

---
count: false
 
Gráfico básico
.panel1-ggplotex1-auto[

```r
paises %>%
  ggplot() +
  aes(x = anio) +
  aes(y = esperanza_de_vida) +
  geom_point() +
  xlab("Anio") +
* ylab("Esperanza de vida")
```
]
 
.panel2-ggplotex1-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex1_auto_07_output-1.png)
]

---

```r
*paises
```
]
 
.panel2-ggplotex2-auto[

---
count: false
 
Gráfico básico
.panel1-ggplotex2-auto[

```r
paises %>%
* filter(pais=="Ecuador")
```
]
 
.panel2-ggplotex2-auto[

```
# A tibble: 12 × 6
   pais    continente  anio esperanza_de_vida poblacion pib_per_capita
   <fct>   <fct>      <int>             <dbl>     <int>          <dbl>
 1 Ecuador Américas    1952              48.4   3548753          3522.
 2 Ecuador Américas    1957              51.4   4058385          3781.
 3 Ecuador Américas    1962              54.6   4681707          4086.
 4 Ecuador Américas    1967              56.7   5432424          4579.
 5 Ecuador Américas    1972              58.8   6298651          5281.
 6 Ecuador Américas    1977              61.3   7278866          6680.
 7 Ecuador Américas    1982              64.3   8365850          7214.
 8 Ecuador Américas    1987              67.2   9545158          6482.
 9 Ecuador Américas    1992              69.6  10748394          7104.
10 Ecuador Américas    1997              72.3  11911819          7429.
11 Ecuador Américas    2002              74.2  12921234          5773.
12 Ecuador Américas    2007              75.0  13755680          6873.
```
]

---
count: false
 
Gráfico básico
.panel1-ggplotex2-auto[

```r
paises %>%
  filter(pais=="Ecuador") %>%
* ggplot(aes(x=anio,
*            y=esperanza_de_vida))
```
]
 
.panel2-ggplotex2-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex2_auto_03_output-1.png)
]

---
count: false
 
Gráfico básico
.panel1-ggplotex2-auto[

```r
paises %>%
  filter(pais=="Ecuador") %>%
  ggplot(aes(x=anio,
             y=esperanza_de_vida)) +
* geom_line(color="blue")
```
]
 
.panel2-ggplotex2-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex2_auto_04_output-1.png)
]

---
count: false
 
Gráfico básico
.panel1-ggplotex2-auto[

```r
paises %>%
  filter(pais=="Ecuador") %>%
  ggplot(aes(x=anio,
             y=esperanza_de_vida)) +
  geom_line(color="blue") +
* xlab("Anio")
```
]
 
.panel2-ggplotex2-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex2_auto_05_output-1.png)
]

---
count: false
 
Gráfico básico
.panel1-ggplotex2-auto[

```r
paises %>%
  filter(pais=="Ecuador") %>%
  ggplot(aes(x=anio,
             y=esperanza_de_vida)) +
  geom_line(color="blue") +
  xlab("Anio") +
* ylab("Esperanza de vida")
```
]
 
.panel2-ggplotex2-auto[
![](ggplot2_TallerR_easy_files/figure-html/ggplotex2_auto_06_output-1.png)
]

Los mapeos estéticos pueden hacer parte de 'ggplot(...)'
---

```r
paises %>%                           # llama los datos y usamos la tuberia %>%
  ggplot(aes(x=anio, 
             y=esperanza_de_vida)) + # mapeos estéticos y añade capas elementos con +
  geom_line(color="blue") +          # Usa una geom para representar los datos 
  xlab("Anio") +                     # titulo del eje x
  ylab("Esperanza de vida")          # titulo del eje y
```

- Datos: siempre una tabla.

- mapeos estéticos asocian los elementos representables gráficamente (la posición x e y que son dos columnas de la tabla de datos)

- capas geometrías (geom): puntos, rectas, histogramas, densidades, etc. También se llaman capas porque pueden superponerse.

- siempre usa el elemento "+" par añadir capas con ggplot (que no se confunden con la tuberia %>%)

---

## Los datos que vamos a usar

```r
install.packages("datos")
library(datos)
paises

library(carData)
salary <- carData::Salaries
```

---

```r
head(paises, n =10) # muestra las "n" primeras lineas de datos
```

```
# A tibble: 10 × 6
   pais       continente  anio esperanza_de_vida poblacion pib_per_capita
   <fct>      <fct>      <int>             <dbl>     <int>          <dbl>
 1 Afganistán Asia        1952              28.8   8425333           779.
 2 Afganistán Asia        1957              30.3   9240934           821.
 3 Afganistán Asia        1962              32.0  10267083           853.
 4 Afganistán Asia        1967              34.0  11537966           836.
 5 Afganistán Asia        1972              36.1  13079460           740.
 6 Afganistán Asia        1977              38.4  14880372           786.
 7 Afganistán Asia        1982              39.9  12881816           978.
 8 Afganistán Asia        1987              40.8  13867957           852.
 9 Afganistán Asia        1992              41.7  16317921           649.
10 Afganistán Asia        1997              41.8  22227415           635.
```

---

```r
head(salary, n =10) # muestra las "n" primeras lineas de datos
```

```
        rank discipline yrs.since.phd yrs.service    sex salary
1       Prof          B            19          18   Male 139750
2       Prof          B            20          16   Male 173200
3   AsstProf          B             4           3   Male  79750
4       Prof          B            45          39   Male 115000
5       Prof          B            40          41   Male 141500
6  AssocProf          B             6           6   Male  97000
7       Prof          B            30          23   Male 175000
8       Prof          B            45          45   Male 147765
9       Prof          B            21          20   Male 119250
10      Prof          B            18          18 Female 129000
```
rank = rango  
displicine = disciplina  
yrs.since.phd = años desde el doctorado  
yrs.service  = años de servicio   
sex = sexo  
salary = salario

---

```r
salarios <- salary %>% 
  rename(rango =rank,    # cambiar nombre de los variables
         disciplina = discipline,
         anio.desde.phd = yrs.since.phd,
         anio.servicio = yrs.service,
         sexo = sex,
         salario = salary) %>% 
  mutate(rango=recode(rango,  # cambiar los niveles 
                     AsstProf="Profesor(a) asistente",
                     AssocProf="Profesor(a) asociada",
                     Prof= "Professor(a)"))

head(salarios,n=5)
```

```
                  rango disciplina anio.desde.phd anio.servicio sexo salario
1          Professor(a)          B             19            18 Male  139750
2          Professor(a)          B             20            16 Male  173200
3 Profesor(a) asistente          B              4             3 Male   79750
4          Professor(a)          B             45            39 Male  115000
5          Professor(a)          B             40            41 Male  141500
```

---

# Visualizar una cantidad

---

```r
*salarios
```
]
 
.panel2-barplot1-auto[

```
                    rango disciplina anio.desde.phd anio.servicio   sexo
1            Professor(a)          B             19            18   Male
2            Professor(a)          B             20            16   Male
3   Profesor(a) asistente          B              4             3   Male
4            Professor(a)          B             45            39   Male
5            Professor(a)          B             40            41   Male
6    Profesor(a) asociada          B              6             6   Male
7            Professor(a)          B             30            23   Male
8            Professor(a)          B             45            45   Male
9            Professor(a)          B             21            20   Male
10           Professor(a)          B             18            18 Female
11   Profesor(a) asociada          B             12             8   Male
12  Profesor(a) asistente          B              7             2   Male
13  Profesor(a) asistente          B              1             1   Male
14  Profesor(a) asistente          B              2             0   Male
15           Professor(a)          B             20            18   Male
16           Professor(a)          B             12             3   Male
17           Professor(a)          B             19            20   Male
18           Professor(a)          A             38            34   Male
19           Professor(a)          A             37            23   Male
20           Professor(a)          A             39            36 Female
21           Professor(a)          A             31            26   Male
22           Professor(a)          A             36            31   Male
23           Professor(a)          A             34            30   Male
24           Professor(a)          A             24            19   Male
25   Profesor(a) asociada          A             13             8 Female
26           Professor(a)          A             21             8   Male
27           Professor(a)          A             35            23   Male
28  Profesor(a) asistente          B              5             3   Male
29  Profesor(a) asistente          B             11             0   Male
30           Professor(a)          B             12             8   Male
31           Professor(a)          B             20             4   Male
32  Profesor(a) asistente          B              7             2   Male
33           Professor(a)          B             13             9   Male
34  Profesor(a) asistente          B              4             2   Male
35  Profesor(a) asistente          B              4             2 Female
36  Profesor(a) asistente          B              5             0 Female
37           Professor(a)          B             22            21   Male
38  Profesor(a) asistente          B              7             4   Male
39           Professor(a)          B             41            31   Male
40   Profesor(a) asociada          B              9             9   Male
41           Professor(a)          B             23             2   Male
42   Profesor(a) asociada          B             23            23   Male
43           Professor(a)          B             40            27   Male
44           Professor(a)          B             38            38   Male
45           Professor(a)          B             19            19   Male
46           Professor(a)          B             25            15   Male
47           Professor(a)          B             40            28   Male
48           Professor(a)          B             23            19 Female
49           Professor(a)          B             25            25 Female
50  Profesor(a) asistente          B              1             1   Male
51           Professor(a)          B             28            28   Male
52           Professor(a)          B             12            11   Male
53  Profesor(a) asistente          B             11             3 Female
54           Professor(a)          B             16             9   Male
55   Profesor(a) asociada          B             12            11   Male
56   Profesor(a) asociada          B             14             5   Male
57           Professor(a)          B             23            21   Male
58   Profesor(a) asociada          B              9             8   Male
59   Profesor(a) asociada          B             10             9   Male
60  Profesor(a) asistente          B              8             3   Male
61   Profesor(a) asociada          B              9             8   Male
62  Profesor(a) asistente          B              3             2   Male
63           Professor(a)          B             33            31   Male
64   Profesor(a) asociada          B             11            11 Female
65  Profesor(a) asistente          B              4             3   Male
66   Profesor(a) asociada          B              9             8   Male
67           Professor(a)          B             22            12   Male
68           Professor(a)          B             35            31   Male
69           Professor(a)          B             17            17 Female
70           Professor(a)          B             28            36   Male
71           Professor(a)          B             17             2   Male
72           Professor(a)          B             45            45   Male
73           Professor(a)          B             29            19   Male
74           Professor(a)          B             35            34   Male
75           Professor(a)          B             28            23   Male
76  Profesor(a) asistente          B              8             3   Male
77           Professor(a)          B             17             3   Male
78           Professor(a)          B             26            19   Male
79  Profesor(a) asistente          B              3             1   Male
80  Profesor(a) asistente          B              6             2   Male
81           Professor(a)          B             43            28   Male
82           Professor(a)          B             17            16   Male
83           Professor(a)          B             22            20   Male
84  Profesor(a) asistente          B              6             2   Male
85           Professor(a)          B             17            18 Female
86           Professor(a)          B             15            14   Male
87           Professor(a)          B             37            37   Male
88  Profesor(a) asistente          B              2             2   Male
89           Professor(a)          B             25            25   Male
90   Profesor(a) asociada          B              9             7   Male
91  Profesor(a) asistente          B             10             5 Female
92   Profesor(a) asociada          B             10             7   Male
93   Profesor(a) asociada          B             10             7   Male
94           Professor(a)          B             38            38   Male
95           Professor(a)          B             21            20   Male
96  Profesor(a) asistente          B              4             0   Male
97   Profesor(a) asociada          B             17            12   Male
98           Professor(a)          B             13             7   Male
99           Professor(a)          B             30            14   Male
100          Professor(a)          B             41            26   Male
101          Professor(a)          B             42            25   Male
102          Professor(a)          B             28            23   Male
103          Professor(a)          B             16             5   Male
104          Professor(a)          B             20            14 Female
105  Profesor(a) asociada          A             18            10   Male
106          Professor(a)          A             31            28   Male
107  Profesor(a) asociada          A             11             8   Male
108  Profesor(a) asociada          A             10             8   Male
109  Profesor(a) asociada          A             15             8   Male
110          Professor(a)          A             40            31   Male
111          Professor(a)          A             20            16   Male
112  Profesor(a) asociada          A             19            16   Male
113 Profesor(a) asistente          A              3             1   Male
114          Professor(a)          A             37            37   Male
115          Professor(a)          A             12             0 Female
116          Professor(a)          A             21             9   Male
117          Professor(a)          A             30            29   Male
118          Professor(a)          A             39            36   Male
119 Profesor(a) asistente          A              4             1   Male
120 Profesor(a) asistente          A              5             3 Female
121          Professor(a)          A             14            14   Male
122          Professor(a)          A             32            32   Male
123          Professor(a)          A             24            22   Male
124  Profesor(a) asociada          A             25            22 Female
125          Professor(a)          A             24            22   Male
126          Professor(a)          A             54            49   Male
127          Professor(a)          A             28            26   Male
128 Profesor(a) asistente          A              2             0 Female
129          Professor(a)          A             32            30   Male
130 Profesor(a) asistente          A              4             2   Male
131  Profesor(a) asociada          A             11             9   Male
132          Professor(a)          A             56            57   Male
133  Profesor(a) asociada          A             10             8 Female
134 Profesor(a) asistente          A              3             1 Female
135          Professor(a)          A             35            25   Male
136          Professor(a)          A             20            18   Male
137          Professor(a)          A             16            14   Male
138          Professor(a)          A             17            14   Male
139  Profesor(a) asociada          A             10             7   Male
140          Professor(a)          A             21            18   Male
141  Profesor(a) asociada          A             14             8   Male
142  Profesor(a) asociada          A             15            10   Male
143          Professor(a)          A             19            11   Male
144 Profesor(a) asistente          B              3             3   Male
145          Professor(a)          B             27            27   Male
146          Professor(a)          B             28            28   Male
147 Profesor(a) asistente          B              4             4   Male
148          Professor(a)          B             27            27   Male
149          Professor(a)          B             36            26 Female
150 Profesor(a) asistente          B              4             3   Male
151          Professor(a)          B             14            12   Male
152 Profesor(a) asistente          B              4             4   Male
153          Professor(a)          B             21             9   Male
154  Profesor(a) asociada          B             12            10 Female
155 Profesor(a) asistente          B              4             0   Male
156          Professor(a)          B             21            21   Male
157  Profesor(a) asociada          B             12            18   Male
158 Profesor(a) asistente          B              1             0   Male
159  Profesor(a) asociada          B              6             6   Male
160          Professor(a)          B             15            16   Male
161 Profesor(a) asistente          B              2             2   Male
162          Professor(a)          B             26            19   Male
163  Profesor(a) asociada          B             22             7   Male
164 Profesor(a) asistente          B              3             3   Male
165 Profesor(a) asistente          B              1             0   Male
166          Professor(a)          B             21             8   Male
167          Professor(a)          B             16            16   Male
168          Professor(a)          B             18            19   Male
169  Profesor(a) asociada          B              8             6   Male
170          Professor(a)          B             25            18   Male
171 Profesor(a) asistente          B              5             5   Male
172          Professor(a)          B             19            19   Male
173          Professor(a)          B             37            24   Male
174          Professor(a)          B             20            20   Male
175  Profesor(a) asociada          B             17             6   Male
176          Professor(a)          B             28            25   Male
177  Profesor(a) asociada          B             10             7   Male
178  Profesor(a) asociada          B             13             9   Male
179          Professor(a)          B             27            14   Male
180 Profesor(a) asistente          B              3             3 Female
181          Professor(a)          B             11            11   Male
182          Professor(a)          B             18             5   Male
183  Profesor(a) asociada          B              8             8   Male
184          Professor(a)          B             26            22   Male
185          Professor(a)          B             23            23   Male
186          Professor(a)          B             33            30   Male
187  Profesor(a) asociada          B             13            10 Female
188          Professor(a)          B             18            10   Male
189  Profesor(a) asociada          B             28            28   Male
190          Professor(a)          B             25            19   Male
191          Professor(a)          B             22             9   Male
192          Professor(a)          B             43            22   Male
193          Professor(a)          B             19            18   Male
194  Profesor(a) asociada          B             19            19   Male
195  Profesor(a) asociada          B             48            53   Male
196  Profesor(a) asociada          B              9             7   Male
197 Profesor(a) asistente          B              4             4   Male
198 Profesor(a) asistente          B              4             4   Male
199          Professor(a)          B             34            33   Male
200          Professor(a)          B             38            22   Male
201 Profesor(a) asistente          B              4             4   Male
202          Professor(a)          B             40            40   Male
203          Professor(a)          B             28            17   Male
204          Professor(a)          B             17            17   Male
205          Professor(a)          B             19             5   Male
206          Professor(a)          B             21             2   Male
207          Professor(a)          B             35            33   Male
208          Professor(a)          B             18            18   Male
209 Profesor(a) asistente          B              7             2   Male
210          Professor(a)          B             20            20   Male
211 Profesor(a) asistente          B              4             3   Male
212          Professor(a)          B             39            39   Male
213          Professor(a)          B             15             7   Male
214          Professor(a)          B             26            19   Male
215  Profesor(a) asociada          B             11             1   Male
216          Professor(a)          B             16            11   Male
217          Professor(a)          B             15            11   Male
218  Profesor(a) asociada          B             29            22   Male
219  Profesor(a) asociada          B             14             7 Female
220          Professor(a)          B             13            11   Male
221          Professor(a)          B             21            21   Male
222          Professor(a)          B             23            10   Male
223  Profesor(a) asociada          B             13             6   Male
224          Professor(a)          B             34            20   Male
225          Professor(a)          A             38            35   Male
226          Professor(a)          A             20            20   Male
227 Profesor(a) asistente          A              3             1   Male
228  Profesor(a) asociada          A              9             7   Male
229          Professor(a)          A             16            11   Male
230          Professor(a)          A             39            38   Male
231          Professor(a)          A             29            27 Female
232  Profesor(a) asociada          A             26            24 Female
233          Professor(a)          A             38            19   Male
234          Professor(a)          A             36            19 Female
235 Profesor(a) asistente          A              8             3   Male
236          Professor(a)          A             28            17   Male
237          Professor(a)          A             25            25   Male
238 Profesor(a) asistente          A              7             6 Female
239          Professor(a)          A             46            40   Male
240          Professor(a)          A             19             6   Male
241 Profesor(a) asistente          A              5             3   Male
242          Professor(a)          A             31            30   Male
243          Professor(a)          A             38            37   Male
244          Professor(a)          A             23            23   Male
245          Professor(a)          A             19            23   Male
246          Professor(a)          A             17            11 Female
247          Professor(a)          A             30            23   Male
248          Professor(a)          A             21            18   Male
249          Professor(a)          A             28            23   Male
250          Professor(a)          A             29             7   Male
251          Professor(a)          A             39            39   Male
252          Professor(a)          A             20             8   Male
253          Professor(a)          A             31            12   Male
254 Profesor(a) asistente          A              4             2 Female
255          Professor(a)          A             28             7 Female
256  Profesor(a) asociada          A             12             8   Male
257          Professor(a)          A             22            22   Male
258  Profesor(a) asociada          A             30            23   Male
259 Profesor(a) asistente          A              9             3   Male
260          Professor(a)          A             32            30   Male
261  Profesor(a) asociada          A             41            33   Male
262          Professor(a)          A             45            45   Male
263          Professor(a)          A             31            26   Male
264          Professor(a)          A             31            31   Male
265          Professor(a)          A             37            35   Male
266          Professor(a)          A             36            30   Male
267          Professor(a)          A             43            43   Male
268          Professor(a)          A             14            10   Male
269          Professor(a)          A             47            44   Male
270          Professor(a)          A             13             7   Male
271          Professor(a)          A             42            40   Male
272          Professor(a)          A             42            18   Male
273 Profesor(a) asistente          A              4             1   Male
274 Profesor(a) asistente          A              8             4   Male
275 Profesor(a) asistente          A              8             3 Female
276          Professor(a)          A             12             6   Male
277          Professor(a)          A             52            48   Male
278          Professor(a)          A             31            27   Male
279          Professor(a)          A             24            18   Male
280          Professor(a)          A             46            46   Male
281          Professor(a)          A             39            38   Male
282          Professor(a)          A             37            27   Male
283          Professor(a)          A             51            51   Male
284          Professor(a)          A             45            43   Male
285  Profesor(a) asociada          A              8             6   Male
286  Profesor(a) asociada          A             49            49   Male
287          Professor(a)          A             28            27   Male
288 Profesor(a) asistente          A              2             0   Male
289          Professor(a)          A             29            27   Male
290 Profesor(a) asistente          A              8             5   Male
291          Professor(a)          A             33             7   Male
292          Professor(a)          A             32            28   Male
293          Professor(a)          A             39             9   Male
294  Profesor(a) asociada          A             11             1   Male
295          Professor(a)          A             19             7   Male
296          Professor(a)          A             40            36   Male
297          Professor(a)          A             18            18   Male
298          Professor(a)          A             17            11   Male
299          Professor(a)          A             49            43   Male
300  Profesor(a) asociada          A             45            39   Male
301          Professor(a)          A             39            36   Male
302          Professor(a)          A             27            16   Male
303          Professor(a)          A             28            13   Male
304          Professor(a)          A             14             4   Male
305          Professor(a)          A             46            44   Male
306          Professor(a)          A             33            31   Male
307 Profesor(a) asistente          A              7             4   Male
308          Professor(a)          A             31            28   Male
309 Profesor(a) asistente          A              5             0   Male
310          Professor(a)          A             22            15   Male
311          Professor(a)          A             20             7   Male
312          Professor(a)          A             14             9   Male
313          Professor(a)          A             29            19   Male
314          Professor(a)          A             35            35   Male
315          Professor(a)          A             22             6   Male
316 Profesor(a) asistente          B              6             3   Male
317  Profesor(a) asociada          B             12             9 Female
318          Professor(a)          B             46            45   Male
319          Professor(a)          B             16            16   Male
320          Professor(a)          B             16            15   Male
321          Professor(a)          B             24            23   Male
322  Profesor(a) asociada          B              9             9   Male
323  Profesor(a) asociada          B             13            11   Male
324          Professor(a)          B             24            15 Female
325          Professor(a)          B             30            31   Male
326 Profesor(a) asistente          B              8             4   Male
327          Professor(a)          B             23            15   Male
328          Professor(a)          B             37            37   Male
329  Profesor(a) asociada          B             10            10   Male
330          Professor(a)          B             23            23   Male
331          Professor(a)          B             49            60   Male
332          Professor(a)          B             20             9   Male
333          Professor(a)          B             18            10 Female
334          Professor(a)          B             33            19   Male
335  Profesor(a) asociada          B             19             6 Female
336          Professor(a)          B             36            38   Male
337          Professor(a)          B             35            23   Male
338          Professor(a)          B             13            12   Male
339          Professor(a)          B             32            25   Male
340          Professor(a)          B             37            15   Male
341          Professor(a)          B             13            11   Male
342          Professor(a)          B             17            17 Female
343          Professor(a)          B             38            38   Male
344          Professor(a)          B             31            31   Male
345          Professor(a)          B             32            35   Male
346          Professor(a)          B             15            10   Male
347          Professor(a)          B             41            27   Male
348          Professor(a)          B             39            33   Male
349 Profesor(a) asistente          B              4             3   Male
350          Professor(a)          B             27            28   Male
351          Professor(a)          B             56            49   Male
352          Professor(a)          B             38            38   Male
353          Professor(a)          B             26            27   Male
354          Professor(a)          B             22            20   Male
355 Profesor(a) asistente          B              8             1   Male
356          Professor(a)          B             25            21   Male
357          Professor(a)          A             49            40   Male
358          Professor(a)          A             39            35   Male
359          Professor(a)          A             28            14 Female
360 Profesor(a) asistente          A             11             4   Male
361          Professor(a)          A             14            11   Male
362          Professor(a)          A             23            15 Female
363          Professor(a)          A             30            30   Male
364  Profesor(a) asociada          A             20            17   Male
365          Professor(a)          A             43            43   Male
366          Professor(a)          A             43            40   Male
367          Professor(a)          A             15            10   Male
368  Profesor(a) asociada          A             10             1   Male
369          Professor(a)          A             35            30   Male
370          Professor(a)          A             33            31   Male
371  Profesor(a) asociada          A             13             8   Male
372          Professor(a)          A             23            20   Male
373          Professor(a)          A             12             7   Male
374          Professor(a)          A             30            26   Male
375          Professor(a)          A             27            19   Male
376          Professor(a)          A             28            26   Male
377 Profesor(a) asistente          A              4             1   Male
378 Profesor(a) asistente          A              6             3   Male
379          Professor(a)          A             38            38   Male
380  Profesor(a) asociada          A             11             8   Male
381 Profesor(a) asistente          A              8             3   Male
382          Professor(a)          A             27            23   Male
383  Profesor(a) asociada          A              8             5   Male
384          Professor(a)          A             44            44   Male
385          Professor(a)          A             27            21   Male
386          Professor(a)          A             15             9   Male
387          Professor(a)          A             29            27   Male
388          Professor(a)          A             29            15   Male
389          Professor(a)          A             38            36   Male
390          Professor(a)          A             33            18   Male
391          Professor(a)          A             40            19   Male
392          Professor(a)          A             30            19   Male
393          Professor(a)          A             33            30   Male
394          Professor(a)          A             31            19   Male
395          Professor(a)          A             42            25   Male
396          Professor(a)          A             25            15   Male
397 Profesor(a) asistente          A              8             4   Male
    salario
1    139750
2    173200
3     79750
4    115000
5    141500
6     97000
7    175000
8    147765
9    119250
10   129000
11   119800
12    79800
13    77700
14    78000
15   104800
16   117150
17   101000
18   103450
19   124750
20   137000
21    89565
22   102580
23    93904
24   113068
25    74830
26   106294
27   134885
28    82379
29    77000
30   118223
31   132261
32    79916
33   117256
34    80225
35    80225
36    77000
37   155750
38    86373
39   125196
40   100938
41   146500
42    93418
43   101299
44   231545
45    94384
46   114778
47    98193
48   151768
49   140096
50    70768
51   126621
52   108875
53    74692
54   106639
55   103760
56    83900
57   117704
58    90215
59   100135
60    75044
61    90304
62    75243
63   109785
64   103613
65    68404
66   100522
67   101000
68    99418
69   111512
70    91412
71   126320
72   146856
73   100131
74    92391
75   113398
76    73266
77   150480
78   193000
79    86100
80    84240
81   150743
82   135585
83   144640
84    88825
85   122960
86   132825
87   152708
88    88400
89   172272
90   107008
91    97032
92   105128
93   105631
94   166024
95   123683
96    84000
97    95611
98   129676
99   102235
100  106689
101  133217
102  126933
103  153303
104  127512
105   83850
106  113543
107   82099
108   82600
109   81500
110  131205
111  112429
112   82100
113   72500
114  104279
115  105000
116  120806
117  148500
118  117515
119   72500
120   73500
121  115313
122  124309
123   97262
124   62884
125   96614
126   78162
127  155500
128   72500
129  113278
130   73000
131   83001
132   76840
133   77500
134   72500
135  168635
136  136000
137  108262
138  105668
139   73877
140  152664
141  100102
142   81500
143  106608
144   89942
145  112696
146  119015
147   92000
148  156938
149  144651
150   95079
151  128148
152   92000
153  111168
154  103994
155   92000
156  118971
157  113341
158   88000
159   95408
160  137167
161   89516
162  176500
163   98510
164   89942
165   88795
166  105890
167  167284
168  130664
169  101210
170  181257
171   91227
172  151575
173   93164
174  134185
175  105000
176  111751
177   95436
178  100944
179  147349
180   92000
181  142467
182  141136
183  100000
184  150000
185  101000
186  134000
187  103750
188  107500
189  106300
190  153750
191  180000
192  133700
193  122100
194   86250
195   90000
196  113600
197   92700
198   92000
199  189409
200  114500
201   92700
202  119700
203  160400
204  152500
205  165000
206   96545
207  162200
208  120000
209   91300
210  163200
211   91000
212  111350
213  128400
214  126200
215  118700
216  145350
217  146000
218  105350
219  109650
220  119500
221  170000
222  145200
223  107150
224  129600
225   87800
226  122400
227   63900
228   70000
229   88175
230  133900
231   91000
232   73300
233  148750
234  117555
235   69700
236   81700
237  114000
238   63100
239   77202
240   96200
241   69200
242  122875
243  102600
244  108200
245   84273
246   90450
247   91100
248  101100
249  128800
250  204000
251  109000
252  102000
253  132000
254   77500
255  116450
256   83000
257  140300
258   74000
259   73800
260   92550
261   88600
262  107550
263  121200
264  126000
265   99000
266  134800
267  143940
268  104350
269   89650
270  103700
271  143250
272  194800
273   73000
274   74000
275   78500
276   93000
277  107200
278  163200
279  107100
280  100600
281  136500
282  103600
283   57800
284  155865
285   88650
286   81800
287  115800
288   85000
289  150500
290   74000
291  174500
292  168500
293  183800
294  104800
295  107300
296   97150
297  126300
298  148800
299   72300
300   70700
301   88600
302  127100
303  170500
304  105260
305  144050
306  111350
307   74500
308  122500
309   74000
310  166800
311   92050
312  108100
313   94350
314  100351
315  146800
316   84716
317   71065
318   67559
319  134550
320  135027
321  104428
322   95642
323  126431
324  161101
325  162221
326   84500
327  124714
328  151650
329   99247
330  134778
331  192253
332  116518
333  105450
334  145098
335  104542
336  151445
337   98053
338  145000
339  128464
340  137317
341  106231
342  124312
343  114596
344  162150
345  150376
346  107986
347  142023
348  128250
349   80139
350  144309
351  186960
352   93519
353  142500
354  138000
355   83600
356  145028
357   88709
358  107309
359  109954
360   78785
361  121946
362  109646
363  138771
364   81285
365  205500
366  101036
367  115435
368  108413
369  131950
370  134690
371   78182
372  110515
373  109707
374  136660
375  103275
376  103649
377   74856
378   77081
379  150680
380  104121
381   75996
382  172505
383   86895
384  105000
385  125192
386  114330
387  139219
388  109305
389  119450
390  186023
391  166605
392  151292
393  103106
394  150564
395  101738
396   95329
397   81035
```
]

---
count: false
 
 Visualizar una cantidad con geom_bar()
.panel1-barplot1-auto[

```r
salarios %>%
* ggplot(aes(x=rango))
```
]
 
.panel2-barplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/barplot1_auto_02_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_bar()
.panel1-barplot1-auto[

```r
salarios %>%
  ggplot(aes(x=rango)) +
* geom_bar(stat = "count")   # por defecto
```
]
 
.panel2-barplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/barplot1_auto_03_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_bar()
.panel1-barplot1-auto[

```r
salarios %>%
  ggplot(aes(x=rango)) +
  geom_bar(stat = "count") +  # por defecto
* theme_bw()
```
]
 
.panel2-barplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/barplot1_auto_04_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_bar()
.panel1-barplot1-auto[

```r
salarios %>%
  ggplot(aes(x=rango)) +
  geom_bar(stat = "count") +  # por defecto
  theme_bw() +
* xlab("Rango")
```
]
 
.panel2-barplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/barplot1_auto_05_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_bar()
.panel1-barplot1-auto[

```r
salarios %>%
  ggplot(aes(x=rango)) +
  geom_bar(stat = "count") +  # por defecto
  theme_bw() +
  xlab("Rango") +
* coord_flip()
```
]
 
.panel2-barplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/barplot1_auto_06_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_bar()
.panel1-barplot1-auto[

```r
salarios %>%
  ggplot(aes(x=rango)) +
  geom_bar(stat = "count") +  # por defecto
  theme_bw() +
  xlab("Rango") +
  coord_flip() +
* theme(axis.text=element_text(size=16),
*       axis.title=element_text(size=16,
*                               face="bold"),
*       axis.text.x=element_text(angle = 45,
*                                hjust = 1))
```
]
 
.panel2-barplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/barplot1_auto_07_output-1.png)
]

---

Este grafico **representa el número de casos en cada grupo**. 
Usa 'coord_flip' para voltear las coordenadas cartesianas para que la horizontal se convierta en vertical y la vertical en horizontal

---

```r
salarios %>% 
  ggplot(aes(x = rango,y=salario)) +
  geom_bar(),     # la altura de la barra = número de casos en cada grupo +
  theme_bw() +                  # fondo blanco
  xlab("Rango") +
  theme(axis.text=element_text(size=16),        # tamaño de las etiquetas 
        axis.title =element_text(size=16,       # tamaño del titulo de los ejes
                                 face="bold"),  #  texto en negrita 
        axis.text.x = element_text(angle = 45, 
                                   hjust = 1)) +  # ángulo de 45% para el eje x
  coord_flip()                                    # voltear las coordenadas 
```

---

```r
*paises
```
]
 
.panel2-dotplot1-auto[

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
* filter(anio==2002 & continente== "Europa")
```
]
 
.panel2-dotplot1-auto[

```
# A tibble: 30 × 6
   pais                 continente  anio esperanza_de_vida poblacion pib_per_capita
   <fct>                <fct>      <int>             <dbl>     <int>          <dbl>
 1 Albania              Europa      2002              75.7   3508512          4604.
 2 Austria              Europa      2002              79.0   8148312         32418.
 3 Bélgica              Europa      2002              78.3  10311970         30486.
 4 Bosnia y Herzegovina Europa      2002              74.1   4165416          6019.
 5 Bulgaria             Europa      2002              72.1   7661799          7697.
 6 Croacia              Europa      2002              74.9   4481020         11628.
 7 República Checa      Europa      2002              75.5  10256295         17596.
 8 Dinamarca            Europa      2002              77.2   5374693         32167.
 9 Finlandia            Europa      2002              78.4   5193039         28205.
10 Francia              Europa      2002              79.6  59925035         28926.
# … with 20 more rows
```
]

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
  filter(anio==2002 & continente== "Europa") %>%
* ggplot(aes(x = pais,
*            y = esperanza_de_vida))
```
]
 
.panel2-dotplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/dotplot1_auto_03_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
  filter(anio==2002 & continente== "Europa") %>%
  ggplot(aes(x = pais,
             y = esperanza_de_vida)) +
* geom_point(col="steelblue",size=3)
```
]
 
.panel2-dotplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/dotplot1_auto_04_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
  filter(anio==2002 & continente== "Europa") %>%
  ggplot(aes(x = pais,
             y = esperanza_de_vida)) +
  geom_point(col="steelblue",size=3) +
* coord_flip()
```
]
 
.panel2-dotplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/dotplot1_auto_05_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
  filter(anio==2002 & continente== "Europa") %>%
  ggplot(aes(x = pais,
             y = esperanza_de_vida)) +
  geom_point(col="steelblue",size=3) +
  coord_flip() +
* theme_bw()
```
]
 
.panel2-dotplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/dotplot1_auto_06_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
  filter(anio==2002 & continente== "Europa") %>%
  ggplot(aes(x = pais,
             y = esperanza_de_vida)) +
  geom_point(col="steelblue",size=3) +
  coord_flip() +
  theme_bw() +
* xlab("")
```
]
 
.panel2-dotplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/dotplot1_auto_07_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
  filter(anio==2002 & continente== "Europa") %>%
  ggplot(aes(x = pais,
             y = esperanza_de_vida)) +
  geom_point(col="steelblue",size=3) +
  coord_flip() +
  theme_bw() +
  xlab("") +
* ylab("Esperanza de vida")
```
]
 
.panel2-dotplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/dotplot1_auto_08_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
  filter(anio==2002 & continente== "Europa") %>%
  ggplot(aes(x = pais,
             y = esperanza_de_vida)) +
  geom_point(col="steelblue",size=3) +
  coord_flip() +
  theme_bw() +
  xlab("") +
  ylab("Esperanza de vida") +
* theme(axis.text.x = element_text(angle = 90,
*                                  hjust = 1),
*       axis.text=element_text(size=14),
*       axis.title =element_text(size=14))
```
]
 
.panel2-dotplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/dotplot1_auto_09_output-1.png)
]

---
count: false
 
 Visualizar una cantidad con geom_point()
.panel1-dotplot1-auto[

```r
paises %>%
  filter(anio==2002 & continente== "Europa") %>%
  ggplot(aes(x = pais,
             y = esperanza_de_vida)) +
  geom_point(col="steelblue",size=3) +
  coord_flip() +
  theme_bw() +
  xlab("") +
  ylab("Esperanza de vida") +
  theme(axis.text.x = element_text(angle = 90,
                                   hjust = 1),
        axis.text=element_text(size=14),
        axis.title =element_text(size=14)) +
* labs(title="Esperanza de vida en 2002",
*      subtitle = "Ejemplo para Europa")
```
]
 
.panel2-dotplot1-auto[
![](ggplot2_TallerR_easy_files/figure-html/dotplot1_auto_10_output-1.png)
]

---

count: false
 
 Ordenar los niveles de una variable
.panel1-dotplot_reorder-auto[

```r
*paises
```
]
 
.panel2-dotplot_reorder-auto[