Data Visualization in R

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# **Data Visualization in R**
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## **<br/> Data preparation & Tables**

### Orlando Joaqui-Barandica, PhD
### 2024

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<img style="border-radius: 50%;" src="img/avatar.png"
width="160px" href="https://www.joaquibarandica.com"
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### [Orlando Joaqui-Barandica, PhD](https://www.joaquibarandica.com) <br/>
### Universidad del Valle
]

<br>

*PhD. in Engineering with emphasis in Engineering Industrial* 
 
*MSc. Applied Economics*
 
*BSc. Statistic*

<i class="fas  fa-link fa-spin "></i> [www.joaquibarandica.com](https://www.joaquibarandica.com)

]

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<img src="img/gif1.gif" width="110%" />
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# Orlando Joaqui-Barandica
### [www.joaquibarandica.com](https://www.joaquibarandica.com)

`Statistician and Master in Applied Economics from Universidad del Valle. Ph.D. in Engineering with an emphasis in Industrial Engineering. Teaching and research experience in the area of Statistics, Econometrics and Quantitative Finance in different recognized universities in the region such as Universidad del Valle, Pontificia Universidad Javeriana de Cali and Universidad ICESI. Research lines: Applied Statistics, Applied Econometrics, Quantitative Finance, Asset-Liability Management.`
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# Contenido

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.pull-left[
### <i class="fas fa-upload" role="presentation" aria-label="upload icon"></i> [Importing DATA](#Data)

### <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> [Cleaning DATA](#Clean)

]

.pull-right[
### <i class="fas fa-table" role="presentation" aria-label="table icon"></i> [Tablas](#Tablas)

### <i class="fas fa-dice-d6" role="presentation" aria-label="dice-d6 icon"></i> [Introducción a ggplot2](#ggplot2)

]

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# <i class="fas fa-upload" role="presentation" aria-label="upload icon"></i>
# Importing DATA
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# <i class="fas fa-arrow-up-1-9" role="presentation" aria-label="arrow-up-1-9 icon"></i>
# Estadísticas descriptivas
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# <i class="fas fa-arrow-up-1-9" role="presentation" aria-label="arrow-up-1-9 icon"></i> Indicadores de tendencia central

* Indicadores de tendencia central: Muestran hacia donde tienden la mayoría de los datos, un ejemplo es el promedio, que también se conoce como “el centro de gravedad de los datos”.

* Los indicadores son: Promedio, Mediana y Moda.

* Las funciones respectivas en R son: `mean()`, `median()`. R no dispone de
una función en su paquete base (stats). Por lo cuál se utiliza el paquete
`modeest`

``` r

install.packages("modeest")

library(modeest)
mlv(runif(20), method = "mfv")[1] ## Genera el valor más frecuente

```

---

# <i class="fas fa-arrow-up-1-9" role="presentation" aria-label="arrow-up-1-9 icon"></i> Indicadores de tendencia central

Para el siguiente vector, calcule la media, mediana y moda

``` r
x <- c(20,NA,10,15,NA,25,22,NA)

mean(x,na.rm=T)
median(x,na.rm=T)
mlv(x, method = "mfv",na.rm=T)[1]

```

En el caso de variable cuantitativas continuas la moda corresponde a los
valores alrededor de los cuales se produce la mayor concentración de los datos

---

# <i class="fas fa-arrow-up-1-9" role="presentation" aria-label="arrow-up-1-9 icon"></i> Indicadores de dispersión

Suponga que se tienen tres grupos de personas con las siguientes estaturas:

``` r
Grupo1 <- c(60, 100, 140, 180)
Grupo2 <- c(100, 100, 140, 140)
Grupo3 <- c(120, 120, 120, 120)
```

``` r
mean(Grupo1); mean(Grupo2); mean(Grupo3)
var(Grupo1); var(Grupo2); var(Grupo3)
sd(Grupo1); sd(Grupo2); sd(Grupo3)
```

Analice que dichos grupos tienen igual promedio pero su variabilidad es
distinta.

---

# <i class="fas fa-arrow-up-1-9" role="presentation" aria-label="arrow-up-1-9 icon"></i> Coeficiente de variación

Coeficiente de Variación: Ayuda a identificar si los datos son homogéneos o
heterogéneos. Determinar si cierta media es consistente con cierta varianza.
Su cálculo es:

$$ CV(x) = \frac{ \sigma }{\bar{x}} * 100 $$

<br>

**Ejercicio:**

Genere una función que permita calcular el coeficiente de variación a los grupos anteriormente establecidos.

``` r
cv<-function(Y){
  
  (sd(Y)/mean(Y))*100
  
}

x<-runif(20)

cv(x)

```

---

# <i class="fas fa-arrow-up-1-9" role="presentation" aria-label="arrow-up-1-9 icon"></i> Indicadores de posición

* Los indicadores de posición que más se trabaja en el análisis descriptivo
son los cuartiles, estos dividen la muestra ordenada en cuatro partes
que contienen aproximadamente el mismo número de datos

* La función en R sería `quantile()`

* También se pueden calcular los percentiles. Por ejemplo: P80 A partir
de que valor se encuentra el 80% de los datos.

``` r

x<- rnorm(10000000)

quantile(x,0.95)

```

---

# <i class="fas fa-arrow-up-1-9" role="presentation" aria-label="arrow-up-1-9 icon"></i> Datos agrupados

Sea la variable Ingreso en millones, conforme una tabla de frecuencias. Explore
la función `table.freq()` de la librería `agricolae`.

``` r

library(agricolae)

Ingreso <- c(2, 1.5, 3, 2.2, 1, 1.2, 3, 4, 5, 1, 2)
tbFreq <- table.freq(hist(Ingreso, plot=FALSE))
tbFreq

```

# Actividad

Para la variable **edad** de los datos de `CovidMuestra`. Genere las estadísticas descriptivas y la tabla de frecuencias. *(Una vez identifique como cargar la base de datos)*

---

# <i class="fas fa-upload" role="presentation" aria-label="upload icon"></i> Importar Data

Antes de que pueda visualizar sus datos, debe ingresarlos en R. Esto implica importar los datos de una fuente externa y manejarlo en un formato útil.

R puede importar datos de casi cualquier fuente, incluidos archivos de texto, hojas de cálculo de Excel, paquetes estadísticos y sistemas de administración de bases de datos. Ilustraremos estas técnicas utilizando el conjunto de datos `Salaries`, que contiene los salarios académicos de 9 meses de profesores universitarios en una sola institución en 2008-2009.

### Archivos de texto

* El paquete `readr` proporciona funciones para importar archivos de texto delimitados en marcos de datos R.

* Recordar también la función de base `read.csv()`

]

```r
library(readr)

# import data from a comma delimited file
Salaries <- read_csv("salaries.csv")

# import data from a tab delimited file
Salaries <- read_tsv("salaries.txt")
```

Estas funciones asumen que la primera línea de datos contiene los nombres de las variables, los valores están separados por comas o tabulaciones, respectivamente, y que los datos faltantes están representados por espacios en blanco.

]

---

# <i class="fas fa-upload" role="presentation" aria-label="upload icon"></i> Importar Data

### Hojas de cálculo de Excel

El paquete `readxl` puede importar datos de libros de Excel. Se admiten los formatos xls y xlsx.

----

```r
library(readxl)

# import data from an Excel workbook
Salaries <- read_excel("salaries.xlsx", sheet=1)
```

----

Dado que los libros de trabajo pueden tener más de una hoja de trabajo, puede especificar la que desee con la opción `sheet`. El valor predeterminado es `sheet=1`.

<br>

> También se puede utilizar la función `read_xlsx()`
]

```
##        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
```

]

---

# <i class="fas fa-upload" role="presentation" aria-label="upload icon"></i> Importar Data

### Desde algún software

El paquete `haven` proporciona funciones para importar datos de una variedad de paquetes estadísticos.

]

----

```r
library(haven)

# import data from Stata
Salaries <- read_dta("salaries.dta")

# import data from SPSS
Salaries <- read_sav("salaries.sav")

# import data from SAS
Salaries <- read_sas("salaries.sas7bdat")
```

----

]

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# <i class="fas fa-upload" role="presentation" aria-label="upload icon"></i> Importar Data

### Desde algún software

La importación de datos de una base de datos requiere pasos adicionales. Dependiendo de la base de datos que contiene los datos, los siguientes paquetes pueden ayudar:

* `RODBC` 
* `RMySQL` 
* `ROracle` 
* `RPostgreSQL` 
* `RSQLite`
* `RMongo`

En las versiones más recientes de **RStudio**, puede usar el panel Conexiones para acceder rápidamente a los datos almacenados en los sistemas de administración de bases de datos.

]

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![](https://media.giphy.com/media/13HgwGsXF0aiGY/giphy.gif)

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# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i>
# Cleaning DATA
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# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Cleaning DATA

Los procesos de limpieza de los datos pueden ser la parte más lenta de cualquier análisis de datos. Los pasos más importantes se consideran a continuación.

> Si bien existen muchos enfoques, los que usan los paquetes `dplyr` y `tidyr` son algunos de los más rápidos y fáciles de aprender.

Los ejemplos de esta sección utilizarán el conjunto de datos de `starwars` del paquete `dplyr`. El conjunto de datos proporciona descripciones de 87 caracteres del universo de Starwars en 13 variables.
]
]

|**Package** |	**Function** |	**Use** |
|--------| -------- |--------
|dplyr |	select |	select variables/columns|
|dplyr |	filter |	select observations/rows |
|dplyr |	mutate |	transform or recode variables|
|dplyr |	summarize |	summarize data|
|dplyr |	group_by |	identify subgroups for further processing|
|tidyr |	gather |	convert wide format dataset to long format|
|tidyr |	spread |	convert long format dataset to wide format|

]

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# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Starwars

```
## # A tibble: 25 × 14
##    name     height  mass hair_color skin_color eye_color birth_year sex   gender
##    <chr>     <int> <dbl> <chr>      <chr>      <chr>          <dbl> <chr> <chr> 
##  1 Luke Sk…    172    77 blond      fair       blue            19   male  mascu…
##  2 C-3PO       167    75 <NA>       gold       yellow         112   none  mascu…
##  3 R2-D2        96    32 <NA>       white, bl… red             33   none  mascu…
##  4 Darth V…    202   136 none       white      yellow          41.9 male  mascu…
##  5 Leia Or…    150    49 brown      light      brown           19   fema… femin…
##  6 Owen La…    178   120 brown, gr… light      blue            52   male  mascu…
##  7 Beru Wh…    165    75 brown      light      blue            47   fema… femin…
##  8 R5-D4        97    32 <NA>       white, red red             NA   none  mascu…
##  9 Biggs D…    183    84 black      light      brown           24   male  mascu…
## 10 Obi-Wan…    182    77 auburn, w… fair       blue-gray       57   male  mascu…
## # ℹ 15 more rows
## # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,
## #   vehicles <list>, starships <list>
```

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Seleccionar variables

La función `select` le permite limitar su conjunto de datos a variables específicas (columnas).

----

* Guardamos las variables: `name`, `height` y `gender`

```r
newdata <- select(starwars, name, height, gender)
```

----

* Guardamos las variables: `name`, y todas las variables entre `mass` y `species`

```r
newdata <- select(starwars, name, mass:species)
```

----

* Guardamos todas las variables, excepto `birth_year` y `gender`

```r
newdata <- select(starwars, -birth_year, -gender)
```

----

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Filtrar observaciones

La función `filter` le permite limitar su conjunto de datos a observaciones (filas) que cumplen un criterio específico. Se pueden combinar varios criterios con los símbolos `&` (Y) y `|` (O).

----

* Seleccionamos el género: `female`

```r
newdata <- filter(starwars, sex == "female")
```

----

* Seleccionar mujeres que son de Alderaan

```r
newdata <- filter(starwars, sex == "female" & homeworld == "Alderaan")
```

----

1. Seleccionar individuos que sean de Alderaan, Coruscant o Endor ➡️ ➡️ ➡️

2. Lo anterior se puede escribir de manera más sucinta como ➡️ ➡️ ➡️
]

```r
newdata <- filter(starwars, 
                  homeworld == "Alderaan" | 
                  homeworld == "Coruscant" | 
                  homeworld == "Endor")

newdata <- filter(starwars, 
                  homeworld %in% c("Alderaan", "Coruscant", "Endor"))
```

]

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Crear/Recodificar variables

La función `mutate` le permite crear nuevas variables o transformar las existentes.

* Convertir la altura en centímetros a pulgadas y la masa en kilogramos a libras.

```r
newdata <- mutate(starwars, 
                  height = height * 0.394,
                  mass   = mass   * 2.205)
```

----

La función `ifelse` (parte de la base R) se puede utilizar para recodificar datos. El formato es `ifelse(test, return if TRUE, return if FALSE)`

```r
newdata <- mutate(starwars, 
                  heightcat = ifelse(height > 180, 
                                     "tall", "short"))
newdata <- mutate(starwars, 
                  eye_color = ifelse(eye_color %in% c("black", "blue", "brown"),
                                     eye_color,"other"))
newdata <- mutate(starwars, 
                  height = ifelse(height < 75 | height > 200,
                                     NA, height))
```
]

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Crear/Recodificar variables

En el análisis de datos, puede haber muchos casos en los que tenga que lidiar con valores perdidos, valores negativos o valores no precisos que están presentes en el conjunto de datos. Estos valores también pueden afectar el resultado del análisis.

La función `replace` le permite reemplazar los valores falsos con valores apropiados.

```r
replace(x, list, values)
```

* `x` vector que contiene los valores
* `list` indica la posición del vector a reemplazar
* `values` los valores de reemplazo

----

```r
df<- c('apple', 'orange','grape','banana')
df
```

```
## [1] "apple"  "orange" "grape"  "banana"
```

```r
dy<-replace(df, 2,'blueberry')
dy
```

```
## [1] "apple"     "blueberry" "grape"     "banana"
```

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Summarize

La función `summarize` se puede utilizar para reducir varios valores a un solo valor (como una media). A menudo se utiliza junto con la función `by_group` para calcular estadísticas por grupo. En el siguiente código, la opción `na.rm=TRUE` se usa para eliminar los valores faltantes antes de calcular las medias.

<br>

```r
newdata <- summarize(starwars, 
                     mean_ht = mean(height, na.rm=TRUE), 
                     mean_mass = mean(mass, na.rm=TRUE))
```
]

```
## # A tibble: 1 × 2
##   mean_ht mean_mass
##     <dbl>     <dbl>
## 1    174.      97.3
```
]

----

<br>

```r
newdata <- group_by(starwars, gender)
newdata <- summarize(newdata, 
                     mean_ht = mean(height, na.rm=TRUE), 
                     mean_wt = mean(mass, na.rm=TRUE))
```
]

```
## # A tibble: 3 × 3
##   gender    mean_ht mean_wt
##   <chr>       <dbl>   <dbl>
## 1 feminine     165.    54.7
## 2 masculine    177.   106. 
## 3 <NA>         181.    48
```

]

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Pipes

Paquetes como `dplyr` y `tidyr` le permiten escribir su código en un formato compacto utilizando el `operador pipe` **%>%**. Aquí hay un ejemplo,

* Código clásico

```r
newdata <- filter(starwars, 
                  sex == "female")
newdata <- group_by(newdata,species)
newdata <- summarize(newdata, 
                     mean_ht = mean(height, na.rm = TRUE))
```

----

* Código con pipes

```r
newdata <- starwars %>%
  filter(sex == "female") %>%
  group_by(species) %>%
  summarize(mean_ht = mean(height, na.rm = TRUE))
```

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Reshape (Reshape2)

* **Wide:** Una tabla está en formato ancho cuando cada fila contiene un `ID` y cada columna expresa una característica de ese individuo.

* **Long:** Una tabla está en formato largo cuando las características específicas de los individuos se expresan en una sola columna `variable` y estas representan un `value` en una sola columna. Es decir, los `ID` se repiten en las filas.

### Wide

### Long

```
##    Species     variable value
## 1   setosa Sepal.Length   5.1
## 2   setosa Sepal.Length   4.9
## 3   setosa Sepal.Length   4.7
## 4   setosa Sepal.Length   4.6
## 5   setosa Sepal.Length   5.0
## 6   setosa Sepal.Length   5.4
## 7   setosa Sepal.Length   4.6
## 8   setosa Sepal.Length   5.0
## 9   setosa Sepal.Length   4.4
## 10  setosa Sepal.Length   4.9
## 11  setosa Sepal.Length   5.4
## 12  setosa Sepal.Length   4.8
```
]
]

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Reshape (Reshape2)

La librería `Reshape2` con la función `melt` ayuda a convertir una tabla a formato long. El parámetro `id` permite especificar con base en que variable se quiere generar la transformación de la data.

> `id = c("Var1","Var2",..)` Se puede especificar más de una variable.

### Long

```r
library(reshape2)
melt(iris,id="Species") 
```

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Reshape (Reshape2)

A partir del formato largo se puede pasar a distintos tipos de formatos no largos (o anchos) usando la función `dcast`

### Wide

```r
library(reshape2)

newdata<-gapminder::gapminder %>% 
  select(country, continent, pop)

dcast(newdata, country ~ continent)
```

```
## # A tibble: 7 × 3
##   country     continent      pop
##   <fct>       <fct>        <int>
## 1 Afghanistan Asia      31889923
## 2 Albania     Europe     3600523
## 3 Algeria     Africa    33333216
## 4 Angola      Africa    12420476
## 5 Argentina   Americas  40301927
## 6 Australia   Oceania   20434176
## 7 Austria     Europe     8199783
```

]

```
##       country   Africa Americas      Asia  Europe  Oceania
## 1 Afghanistan       NA       NA  31889923      NA       NA
## 2     Albania       NA       NA        NA 3600523       NA
## 3     Algeria 33333216       NA        NA      NA       NA
## 4      Angola 12420476       NA        NA      NA       NA
## 5   Argentina       NA 40301927        NA      NA       NA
## 6   Australia       NA       NA        NA      NA 20434176
## 7     Austria       NA       NA        NA 8199783       NA
## 8     Bahrain       NA       NA    708573      NA       NA
## 9  Bangladesh       NA       NA 150448339      NA       NA
```
]
]

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Reshape (tidyr)

La librería `tydir` también permite hacer el reshape a la tabla de datos.

### Long

```r
library(tidyr)
long_data <- gather(iris, 
                    key="variable", 
                    value="value", 
                    Species:Petal.Width)

head(long_data,10)
```

```
##    Sepal.Length Sepal.Width Petal.Length variable  value
## 1           5.1         3.5          1.4  Species setosa
## 2           4.9         3.0          1.4  Species setosa
## 3           4.7         3.2          1.3  Species setosa
## 4           4.6         3.1          1.5  Species setosa
## 5           5.0         3.6          1.4  Species setosa
## 6           5.4         3.9          1.7  Species setosa
## 7           4.6         3.4          1.4  Species setosa
## 8           5.0         3.4          1.5  Species setosa
## 9           4.4         2.9          1.4  Species setosa
## 10          4.9         3.1          1.5  Species setosa
```

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Reshape (tidyr)

La librería `tydir` también permite hacer el reshape a la tabla de datos.

### Wide

```r
newdata<-gapminder::gapminder %>%
  filter(year==2007) %>% 
  select(country, continent, pop)

library(tidyr)
wide_data <- spread(newdata, continent, pop)

head(wide_data,12)
```

```
## # A tibble: 6 × 6
##   country       Africa Americas     Asia  Europe  Oceania
##   <fct>          <int>    <int>    <int>   <int>    <int>
## 1 Afghanistan       NA       NA 31889923      NA       NA
## 2 Albania           NA       NA       NA 3600523       NA
## 3 Algeria     33333216       NA       NA      NA       NA
## 4 Angola      12420476       NA       NA      NA       NA
## 5 Argentina         NA 40301927       NA      NA       NA
## 6 Australia         NA       NA       NA      NA 20434176
```

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Merge

> Hacer un *merge* es unir dos conjuntos de datos por una o más columnas comunes.

### R base: función `merge()`

```r
merge(df1, df2, by.x = "df1ColName", by.y = "df2ColName")
```

* No importa el orden del marco de datos 1 y el marco de datos 2, pero el primero se considera *X* y el segundo es *Y*.

* Si las columnas por las que desea unirse no tienen el mismo nombre, debe indicarle a fusionar las columnas por las que desea unirse: `by.x` para el nombre de la columna del marco de datos *X*, y `by.y` para la *Y*.

* También puede indicar fusionar si desea todas las filas, incluidas las que no coinciden, o solo las filas que coinciden, con los argumentos `all.x = TRUE` y `all.y = TRUE`.

---

# <i class="fas fa-broom" role="presentation" aria-label="broom icon"></i> Merge

> Hacer un *merge* es unir dos conjuntos de datos por una o más columnas comunes.

### dplyr: función `left_join()`

```r
left_join(x, y, by = c("df1ColName" = "df2ColName"))
```

* `left_join` Incluye todo lo que está a la izquierda (en *X*) y todas las filas que coinciden con el marco de datos derecho (*Y*).

* Si las columnas de combinación tienen el mismo nombre, todo lo que necesita es `left_join(x, y)`.

* También puede indicar fusionar si desea todas las filas, incluidas las que no coinciden, o solo las filas que coinciden, con los argumentos `all.x = TRUE` y `all.y = TRUE`.

]

---

# Actividad
----

![](https://media.giphy.com/media/dVuyBgq2z5gVBkFtDc/giphy.gif)

]

.right-column[
1️⃣ Utilice los datos `CovidMuestra.xlsx`🦠, los cuales tienen una muestra de 1500 casos de covid. Puede entrar al repositorio del curso en el Github y descargarlos.

Genere las siguientes estadísticas por grupo, tenga presente si debe recodificar valores:

* Promedio de edad por departamento
* Promedio de edad por sexo
* Promedio de edad por departamento y sexo

2️⃣ Realizar lo mismo del punto 1, para la desviación estándar y mediana.

]

---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i>
# Tablas
----

.right[
.bottom[
####  [<i class="far fa-bell" role="presentation" aria-label="bell icon"></i>](#menu)
]
]

---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas

La visualización de datos en R es un tema enorme. No importa qué tan bueno sea su análisis de datos si no comunica sus resultados de manera efectiva. En la mayoría de los informes, **la comunicación de los resultados se realiza mediante una combinación de visualización de datos y tablas.**

<br>

> Inicialmente exploremos este tipo de visualización en:

* default
* kable
* tibble
* paged

.center[
<img src="https://rubenfcasal.github.io/bookdown_intro/images/rmarkdown.png" 
width="150px"/>
]

]

.right-column[
Las visualizaciones de estas tablas son generadas en salidas tipo `Rmarkdown` para una correcta visualización en formato PDF o HTML.
]

---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *default*

```r
print.data.frame( head(iris,20) )
```

```
##    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1           5.1         3.5          1.4         0.2  setosa
## 2           4.9         3.0          1.4         0.2  setosa
## 3           4.7         3.2          1.3         0.2  setosa
## 4           4.6         3.1          1.5         0.2  setosa
## 5           5.0         3.6          1.4         0.2  setosa
## 6           5.4         3.9          1.7         0.4  setosa
## 7           4.6         3.4          1.4         0.3  setosa
## 8           5.0         3.4          1.5         0.2  setosa
## 9           4.4         2.9          1.4         0.2  setosa
## 10          4.9         3.1          1.5         0.1  setosa
## 11          5.4         3.7          1.5         0.2  setosa
## 12          4.8         3.4          1.6         0.2  setosa
## 13          4.8         3.0          1.4         0.1  setosa
## 14          4.3         3.0          1.1         0.1  setosa
## 15          5.8         4.0          1.2         0.2  setosa
## 16          5.7         4.4          1.5         0.4  setosa
## 17          5.4         3.9          1.3         0.4  setosa
## 18          5.1         3.5          1.4         0.3  setosa
## 19          5.7         3.8          1.7         0.3  setosa
## 20          5.1         3.8          1.5         0.3  setosa
```
---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *knitr::kable*

```r
knitr::kable( head(iris,10) )
```

| Sepal.Length| Sepal.Width| Petal.Length| Petal.Width|Species |
|------------:|-----------:|------------:|-----------:|:-------|
|          5.1|         3.5|          1.4|         0.2|setosa  |
|          4.9|         3.0|          1.4|         0.2|setosa  |
|          4.7|         3.2|          1.3|         0.2|setosa  |
|          4.6|         3.1|          1.5|         0.2|setosa  |
|          5.0|         3.6|          1.4|         0.2|setosa  |
|          5.4|         3.9|          1.7|         0.4|setosa  |
|          4.6|         3.4|          1.4|         0.3|setosa  |
|          5.0|         3.4|          1.5|         0.2|setosa  |
|          4.4|         2.9|          1.4|         0.2|setosa  |
|          4.9|         3.1|          1.5|         0.1|setosa  |
---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *tibble*

```r
print(tbl_df(iris))
```

```
## # A tibble: 150 × 5
##    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
##           <dbl>       <dbl>        <dbl>       <dbl> <fct>  
##  1          5.1         3.5          1.4         0.2 setosa 
##  2          4.9         3            1.4         0.2 setosa 
##  3          4.7         3.2          1.3         0.2 setosa 
##  4          4.6         3.1          1.5         0.2 setosa 
##  5          5           3.6          1.4         0.2 setosa 
##  6          5.4         3.9          1.7         0.4 setosa 
##  7          4.6         3.4          1.4         0.3 setosa 
##  8          5           3.4          1.5         0.2 setosa 
##  9          4.4         2.9          1.4         0.2 setosa 
## 10          4.9         3.1          1.5         0.1 setosa 
## # ℹ 140 more rows
```
---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *paged*

```r
rmarkdown::paged_table(iris)
```

<div data-pagedtable="false">
  <script data-pagedtable-source type="application/json">
{"columns":[{"label":["Sepal.Length"],"name":[1],"type":["dbl"],"align":["right"]},{"label":["Sepal.Width"],"name":[2],"type":["dbl"],"align":["right"]},{"label":["Petal.Length"],"name":[3],"type":["dbl"],"align":["right"]},{"label":["Petal.Width"],"name":[4],"type":["dbl"],"align":["right"]},{"label":["Species"],"name":[5],"type":["fct"],"align":["left"]}],"data":[{"1":"5.1","2":"3.5","3":"1.4","4":"0.2","5":"setosa"},{"1":"4.9","2":"3.0","3":"1.4","4":"0.2","5":"setosa"},{"1":"4.7","2":"3.2","3":"1.3","4":"0.2","5":"setosa"},{"1":"4.6","2":"3.1","3":"1.5","4":"0.2","5":"setosa"},{"1":"5.0","2":"3.6","3":"1.4","4":"0.2","5":"setosa"},{"1":"5.4","2":"3.9","3":"1.7","4":"0.4","5":"setosa"},{"1":"4.6","2":"3.4","3":"1.4","4":"0.3","5":"setosa"},{"1":"5.0","2":"3.4","3":"1.5","4":"0.2","5":"setosa"},{"1":"4.4","2":"2.9","3":"1.4","4":"0.2","5":"setosa"},{"1":"4.9","2":"3.1","3":"1.5","4":"0.1","5":"setosa"},{"1":"5.4","2":"3.7","3":"1.5","4":"0.2","5":"setosa"},{"1":"4.8","2":"3.4","3":"1.6","4":"0.2","5":"setosa"},{"1":"4.8","2":"3.0","3":"1.4","4":"0.1","5":"setosa"},{"1":"4.3","2":"3.0","3":"1.1","4":"0.1","5":"setosa"},{"1":"5.8","2":"4.0","3":"1.2","4":"0.2","5":"setosa"},{"1":"5.7","2":"4.4","3":"1.5","4":"0.4","5":"setosa"},{"1":"5.4","2":"3.9","3":"1.3","4":"0.4","5":"setosa"},{"1":"5.1","2":"3.5","3":"1.4","4":"0.3","5":"setosa"},{"1":"5.7","2":"3.8","3":"1.7","4":"0.3","5":"setosa"},{"1":"5.1","2":"3.8","3":"1.5","4":"0.3","5":"setosa"},{"1":"5.4","2":"3.4","3":"1.7","4":"0.2","5":"setosa"},{"1":"5.1","2":"3.7","3":"1.5","4":"0.4","5":"setosa"},{"1":"4.6","2":"3.6","3":"1.0","4":"0.2","5":"setosa"},{"1":"5.1","2":"3.3","3":"1.7","4":"0.5","5":"setosa"},{"1":"4.8","2":"3.4","3":"1.9","4":"0.2","5":"setosa"},{"1":"5.0","2":"3.0","3":"1.6","4":"0.2","5":"setosa"},{"1":"5.0","2":"3.4","3":"1.6","4":"0.4","5":"setosa"},{"1":"5.2","2":"3.5","3":"1.5","4":"0.2","5":"setosa"},{"1":"5.2","2":"3.4","3":"1.4","4":"0.2","5":"setosa"},{"1":"4.7","2":"3.2","3":"1.6","4":"0.2","5":"setosa"},{"1":"4.8","2":"3.1","3":"1.6","4":"0.2","5":"setosa"},{"1":"5.4","2":"3.4","3":"1.5","4":"0.4","5":"setosa"},{"1":"5.2","2":"4.1","3":"1.5","4":"0.1","5":"setosa"},{"1":"5.5","2":"4.2","3":"1.4","4":"0.2","5":"setosa"},{"1":"4.9","2":"3.1","3":"1.5","4":"0.2","5":"setosa"},{"1":"5.0","2":"3.2","3":"1.2","4":"0.2","5":"setosa"},{"1":"5.5","2":"3.5","3":"1.3","4":"0.2","5":"setosa"},{"1":"4.9","2":"3.6","3":"1.4","4":"0.1","5":"setosa"},{"1":"4.4","2":"3.0","3":"1.3","4":"0.2","5":"setosa"},{"1":"5.1","2":"3.4","3":"1.5","4":"0.2","5":"setosa"},{"1":"5.0","2":"3.5","3":"1.3","4":"0.3","5":"setosa"},{"1":"4.5","2":"2.3","3":"1.3","4":"0.3","5":"setosa"},{"1":"4.4","2":"3.2","3":"1.3","4":"0.2","5":"setosa"},{"1":"5.0","2":"3.5","3":"1.6","4":"0.6","5":"setosa"},{"1":"5.1","2":"3.8","3":"1.9","4":"0.4","5":"setosa"},{"1":"4.8","2":"3.0","3":"1.4","4":"0.3","5":"setosa"},{"1":"5.1","2":"3.8","3":"1.6","4":"0.2","5":"setosa"},{"1":"4.6","2":"3.2","3":"1.4","4":"0.2","5":"setosa"},{"1":"5.3","2":"3.7","3":"1.5","4":"0.2","5":"setosa"},{"1":"5.0","2":"3.3","3":"1.4","4":"0.2","5":"setosa"},{"1":"7.0","2":"3.2","3":"4.7","4":"1.4","5":"versicolor"},{"1":"6.4","2":"3.2","3":"4.5","4":"1.5","5":"versicolor"},{"1":"6.9","2":"3.1","3":"4.9","4":"1.5","5":"versicolor"},{"1":"5.5","2":"2.3","3":"4.0","4":"1.3","5":"versicolor"},{"1":"6.5","2":"2.8","3":"4.6","4":"1.5","5":"versicolor"},{"1":"5.7","2":"2.8","3":"4.5","4":"1.3","5":"versicolor"},{"1":"6.3","2":"3.3","3":"4.7","4":"1.6","5":"versicolor"},{"1":"4.9","2":"2.4","3":"3.3","4":"1.0","5":"versicolor"},{"1":"6.6","2":"2.9","3":"4.6","4":"1.3","5":"versicolor"},{"1":"5.2","2":"2.7","3":"3.9","4":"1.4","5":"versicolor"},{"1":"5.0","2":"2.0","3":"3.5","4":"1.0","5":"versicolor"},{"1":"5.9","2":"3.0","3":"4.2","4":"1.5","5":"versicolor"},{"1":"6.0","2":"2.2","3":"4.0","4":"1.0","5":"versicolor"},{"1":"6.1","2":"2.9","3":"4.7","4":"1.4","5":"versicolor"},{"1":"5.6","2":"2.9","3":"3.6","4":"1.3","5":"versicolor"},{"1":"6.7","2":"3.1","3":"4.4","4":"1.4","5":"versicolor"},{"1":"5.6","2":"3.0","3":"4.5","4":"1.5","5":"versicolor"},{"1":"5.8","2":"2.7","3":"4.1","4":"1.0","5":"versicolor"},{"1":"6.2","2":"2.2","3":"4.5","4":"1.5","5":"versicolor"},{"1":"5.6","2":"2.5","3":"3.9","4":"1.1","5":"versicolor"},{"1":"5.9","2":"3.2","3":"4.8","4":"1.8","5":"versicolor"},{"1":"6.1","2":"2.8","3":"4.0","4":"1.3","5":"versicolor"},{"1":"6.3","2":"2.5","3":"4.9","4":"1.5","5":"versicolor"},{"1":"6.1","2":"2.8","3":"4.7","4":"1.2","5":"versicolor"},{"1":"6.4","2":"2.9","3":"4.3","4":"1.3","5":"versicolor"},{"1":"6.6","2":"3.0","3":"4.4","4":"1.4","5":"versicolor"},{"1":"6.8","2":"2.8","3":"4.8","4":"1.4","5":"versicolor"},{"1":"6.7","2":"3.0","3":"5.0","4":"1.7","5":"versicolor"},{"1":"6.0","2":"2.9","3":"4.5","4":"1.5","5":"versicolor"},{"1":"5.7","2":"2.6","3":"3.5","4":"1.0","5":"versicolor"},{"1":"5.5","2":"2.4","3":"3.8","4":"1.1","5":"versicolor"},{"1":"5.5","2":"2.4","3":"3.7","4":"1.0","5":"versico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  </script>
</div>
---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *gt*

```r
library(gt)
library(tidyverse)

iris %>%
  head(11) %>% 
  gt() %>% 
  tab_header(
    title = "Base de datos IRIS",
    subtitle = "Diplomado en gestión de datos"
  )
```
]

.pull-right[
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<table class="gt_table">
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      <th colspan="5" class="gt_heading gt_title gt_font_normal" style>Base de datos IRIS</th>
    </tr>
    <tr>
      <th colspan="5" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>Diplomado en gestión de datos</th>
    </tr>
  </thead>
  <thead class="gt_col_headings">
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      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Sepal.Length</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Sepal.Width</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Petal.Length</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">Petal.Width</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_center" rowspan="1" colspan="1">Species</th>
    </tr>
  </thead>
  <tbody class="gt_table_body">
    <tr><td class="gt_row gt_right">5.1</td>
<td class="gt_row gt_right">3.5</td>
<td class="gt_row gt_right">1.4</td>
<td class="gt_row gt_right">0.2</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">4.9</td>
<td class="gt_row gt_right">3.0</td>
<td class="gt_row gt_right">1.4</td>
<td class="gt_row gt_right">0.2</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">4.7</td>
<td class="gt_row gt_right">3.2</td>
<td class="gt_row gt_right">1.3</td>
<td class="gt_row gt_right">0.2</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">4.6</td>
<td class="gt_row gt_right">3.1</td>
<td class="gt_row gt_right">1.5</td>
<td class="gt_row gt_right">0.2</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">5.0</td>
<td class="gt_row gt_right">3.6</td>
<td class="gt_row gt_right">1.4</td>
<td class="gt_row gt_right">0.2</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">5.4</td>
<td class="gt_row gt_right">3.9</td>
<td class="gt_row gt_right">1.7</td>
<td class="gt_row gt_right">0.4</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">4.6</td>
<td class="gt_row gt_right">3.4</td>
<td class="gt_row gt_right">1.4</td>
<td class="gt_row gt_right">0.3</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">5.0</td>
<td class="gt_row gt_right">3.4</td>
<td class="gt_row gt_right">1.5</td>
<td class="gt_row gt_right">0.2</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">4.4</td>
<td class="gt_row gt_right">2.9</td>
<td class="gt_row gt_right">1.4</td>
<td class="gt_row gt_right">0.2</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">4.9</td>
<td class="gt_row gt_right">3.1</td>
<td class="gt_row gt_right">1.5</td>
<td class="gt_row gt_right">0.1</td>
<td class="gt_row gt_center">setosa</td></tr>
    <tr><td class="gt_row gt_right">5.4</td>
<td class="gt_row gt_right">3.7</td>
<td class="gt_row gt_right">1.5</td>
<td class="gt_row gt_right">0.2</td>
<td class="gt_row gt_center">setosa</td></tr>
  </tbody>
  
  
</table>
</div>

]

---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *gt*

```r
library(gt)
library(tidyverse)
library(glue)

# Define the start and end dates for the data range
start_date <- "2010-06-07"
end_date <- "2010-06-14"

# Create a gt table based on preprocessed
# `sp500` table data
sp500 %>%
  filter(date >= start_date & date <= end_date) %>%
  select(-adj_close) %>%
  gt() %>%
  tab_header(
    title = "S&P 500",
    subtitle = glue::glue("{start_date} to {end_date}")
  ) %>%
  fmt_date(
    columns = date,
    date_style = 3
  ) %>%
  fmt_currency(
    columns = c(open, high, low, close),
    currency = "USD"
  ) %>%
  fmt_number(
    columns = volume,
    suffixing = TRUE
  )
```
]

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#vxgwphtrwi .gt_super {
  font-size: 65%;
}

#vxgwphtrwi .gt_two_val_uncert {
  display: inline-block;
  line-height: 1em;
  text-align: right;
  font-size: 60%;
  vertical-align: -0.25em;
  margin-left: 0.1em;
}

#vxgwphtrwi .gt_footnote_marks {
  font-style: italic;
  font-weight: normal;
  font-size: 75%;
  vertical-align: 0.4em;
}

#vxgwphtrwi .gt_asterisk {
  font-size: 100%;
  vertical-align: 0;
}

#vxgwphtrwi .gt_slash_mark {
  font-size: 0.7em;
  line-height: 0.7em;
  vertical-align: 0.15em;
}

#vxgwphtrwi .gt_fraction_numerator {
  font-size: 0.6em;
  line-height: 0.6em;
  vertical-align: 0.45em;
}

#vxgwphtrwi .gt_fraction_denominator {
  font-size: 0.6em;
  line-height: 0.6em;
  vertical-align: -0.05em;
}
</style>
<table class="gt_table">
  <thead class="gt_header">
    <tr>
      <th colspan="6" class="gt_heading gt_title gt_font_normal" style>S&P 500</th>
    </tr>
    <tr>
      <th colspan="6" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style>2010-06-07 to 2010-06-14</th>
    </tr>
  </thead>
  <thead class="gt_col_headings">
    <tr>
      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1">date</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">open</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">high</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">low</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">close</th>
      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1">volume</th>
    </tr>
  </thead>
  <tbody class="gt_table_body">
    <tr><td class="gt_row gt_left">lun., jun. 14, 2010</td>
<td class="gt_row gt_right">$1,095.00</td>
<td class="gt_row gt_right">$1,105.91</td>
<td class="gt_row gt_right">$1,089.03</td>
<td class="gt_row gt_right">$1,089.63</td>
<td class="gt_row gt_right">4.43B</td></tr>
    <tr><td class="gt_row gt_left">vie., jun. 11, 2010</td>
<td class="gt_row gt_right">$1,082.65</td>
<td class="gt_row gt_right">$1,092.25</td>
<td class="gt_row gt_right">$1,077.12</td>
<td class="gt_row gt_right">$1,091.60</td>
<td class="gt_row gt_right">4.06B</td></tr>
    <tr><td class="gt_row gt_left">jue., jun. 10, 2010</td>
<td class="gt_row gt_right">$1,058.77</td>
<td class="gt_row gt_right">$1,087.85</td>
<td class="gt_row gt_right">$1,058.77</td>
<td class="gt_row gt_right">$1,086.84</td>
<td class="gt_row gt_right">5.14B</td></tr>
    <tr><td class="gt_row gt_left">mié., jun. 9, 2010</td>
<td class="gt_row gt_right">$1,062.75</td>
<td class="gt_row gt_right">$1,077.74</td>
<td class="gt_row gt_right">$1,052.25</td>
<td class="gt_row gt_right">$1,055.69</td>
<td class="gt_row gt_right">5.98B</td></tr>
    <tr><td class="gt_row gt_left">mar., jun. 8, 2010</td>
<td class="gt_row gt_right">$1,050.81</td>
<td class="gt_row gt_right">$1,063.15</td>
<td class="gt_row gt_right">$1,042.17</td>
<td class="gt_row gt_right">$1,062.00</td>
<td class="gt_row gt_right">6.19B</td></tr>
    <tr><td class="gt_row gt_left">lun., jun. 7, 2010</td>
<td class="gt_row gt_right">$1,065.84</td>
<td class="gt_row gt_right">$1,071.36</td>
<td class="gt_row gt_right">$1,049.86</td>
<td class="gt_row gt_right">$1,050.47</td>
<td class="gt_row gt_right">5.47B</td></tr>
  </tbody>
  
  
</table>
</div>

---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *kable + kableExtra*

```r
library(knitr)
library(kableExtra)

airquality %>% 
   kable(format = "html", row.names = TRUE) %>%
  kable_styling(full_width = T,
                font_size = 15) %>%
  column_spec(column = 2, bold = TRUE) %>%  # columns must be specified by number
  column_spec(column = 5, width = "5cm") %>%
  row_spec(row = 0, color = "#660033") %>%  # row = 0 allows us to format the header
  row_spec(row = 2, italic = TRUE) %>%
  row_spec(row = 3, color = "#104e8b", background = "#d3d3d3") %>%
  row_spec(row = 4, monospace = TRUE) %>%
  row_spec(row = 5, underline = TRUE) %>%
  row_spec(row = 6, strikeout = TRUE) %>% 
  scroll_box(height = "200px")
```
]

<br>

<div style="border: 1px solid #ddd; padding: 0px; overflow-y: scroll; height:200px; "><table class="table" style="font-size: 15px; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;color: #660033 !important;position: sticky; top:0; background-color: #FFFFFF;">   </th>
   <th style="text-align:right;color: #660033 !important;position: sticky; top:0; background-color: #FFFFFF;"> Ozone </th>
   <th style="text-align:right;color: #660033 !important;position: sticky; top:0; background-color: #FFFFFF;"> Solar.R </th>
   <th style="text-align:right;color: #660033 !important;position: sticky; top:0; background-color: #FFFFFF;"> Wind </th>
   <th style="text-align:right;color: #660033 !important;position: sticky; top:0; background-color: #FFFFFF;"> Temp </th>
   <th style="text-align:right;color: #660033 !important;position: sticky; top:0; background-color: #FFFFFF;"> Month </th>
   <th style="text-align:right;color: #660033 !important;position: sticky; top:0; background-color: #FFFFFF;"> Day </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 1 </td>
   <td style="text-align:right;font-weight: bold;"> 41 </td>
   <td style="text-align:right;"> 190 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 67 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:left;font-style: italic;"> 2 </td>
   <td style="text-align:right;font-weight: bold;font-style: italic;"> 36 </td>
   <td style="text-align:right;font-style: italic;"> 118 </td>
   <td style="text-align:right;font-style: italic;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; font-style: italic;"> 72 </td>
   <td style="text-align:right;font-style: italic;"> 5 </td>
   <td style="text-align:right;font-style: italic;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:left;color: #104e8b !important;background-color: #d3d3d3 !important;"> 3 </td>
   <td style="text-align:right;font-weight: bold;color: #104e8b !important;background-color: #d3d3d3 !important;"> 12 </td>
   <td style="text-align:right;color: #104e8b !important;background-color: #d3d3d3 !important;"> 149 </td>
   <td style="text-align:right;color: #104e8b !important;background-color: #d3d3d3 !important;"> 12.6 </td>
   <td style="text-align:right;width: 5cm; color: #104e8b !important;background-color: #d3d3d3 !important;"> 74 </td>
   <td style="text-align:right;color: #104e8b !important;background-color: #d3d3d3 !important;"> 5 </td>
   <td style="text-align:right;color: #104e8b !important;background-color: #d3d3d3 !important;"> 3 </td>
  </tr>
  <tr>
   <td style="text-align:left;font-family: monospace;"> 4 </td>
   <td style="text-align:right;font-weight: bold;font-family: monospace;"> 18 </td>
   <td style="text-align:right;font-family: monospace;"> 313 </td>
   <td style="text-align:right;font-family: monospace;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; font-family: monospace;"> 62 </td>
   <td style="text-align:right;font-family: monospace;"> 5 </td>
   <td style="text-align:right;font-family: monospace;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;text-decoration: underline;"> 5 </td>
   <td style="text-align:right;font-weight: bold;text-decoration: underline;"> NA </td>
   <td style="text-align:right;text-decoration: underline;"> NA </td>
   <td style="text-align:right;text-decoration: underline;"> 14.3 </td>
   <td style="text-align:right;width: 5cm; text-decoration: underline;"> 56 </td>
   <td style="text-align:right;text-decoration: underline;"> 5 </td>
   <td style="text-align:right;text-decoration: underline;"> 5 </td>
  </tr>
  <tr>
   <td style="text-align:left;text-decoration: line-through;"> 6 </td>
   <td style="text-align:right;font-weight: bold;text-decoration: line-through;"> 28 </td>
   <td style="text-align:right;text-decoration: line-through;"> NA </td>
   <td style="text-align:right;text-decoration: line-through;"> 14.9 </td>
   <td style="text-align:right;width: 5cm; text-decoration: line-through;"> 66 </td>
   <td style="text-align:right;text-decoration: line-through;"> 5 </td>
   <td style="text-align:right;text-decoration: line-through;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 7 </td>
   <td style="text-align:right;font-weight: bold;"> 23 </td>
   <td style="text-align:right;"> 299 </td>
   <td style="text-align:right;"> 8.6 </td>
   <td style="text-align:right;width: 5cm; "> 65 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 7 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 8 </td>
   <td style="text-align:right;font-weight: bold;"> 19 </td>
   <td style="text-align:right;"> 99 </td>
   <td style="text-align:right;"> 13.8 </td>
   <td style="text-align:right;width: 5cm; "> 59 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 9 </td>
   <td style="text-align:right;font-weight: bold;"> 8 </td>
   <td style="text-align:right;"> 19 </td>
   <td style="text-align:right;"> 20.1 </td>
   <td style="text-align:right;width: 5cm; "> 61 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 10 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 194 </td>
   <td style="text-align:right;"> 8.6 </td>
   <td style="text-align:right;width: 5cm; "> 69 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 11 </td>
   <td style="text-align:right;font-weight: bold;"> 7 </td>
   <td style="text-align:right;"> NA </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 74 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 11 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 12 </td>
   <td style="text-align:right;font-weight: bold;"> 16 </td>
   <td style="text-align:right;"> 256 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 69 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 13 </td>
   <td style="text-align:right;font-weight: bold;"> 11 </td>
   <td style="text-align:right;"> 290 </td>
   <td style="text-align:right;"> 9.2 </td>
   <td style="text-align:right;width: 5cm; "> 66 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 14 </td>
   <td style="text-align:right;font-weight: bold;"> 14 </td>
   <td style="text-align:right;"> 274 </td>
   <td style="text-align:right;"> 10.9 </td>
   <td style="text-align:right;width: 5cm; "> 68 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 14 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 15 </td>
   <td style="text-align:right;font-weight: bold;"> 18 </td>
   <td style="text-align:right;"> 65 </td>
   <td style="text-align:right;"> 13.2 </td>
   <td style="text-align:right;width: 5cm; "> 58 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 16 </td>
   <td style="text-align:right;font-weight: bold;"> 14 </td>
   <td style="text-align:right;"> 334 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 64 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 16 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 17 </td>
   <td style="text-align:right;font-weight: bold;"> 34 </td>
   <td style="text-align:right;"> 307 </td>
   <td style="text-align:right;"> 12.0 </td>
   <td style="text-align:right;width: 5cm; "> 66 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 17 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 18 </td>
   <td style="text-align:right;font-weight: bold;"> 6 </td>
   <td style="text-align:right;"> 78 </td>
   <td style="text-align:right;"> 18.4 </td>
   <td style="text-align:right;width: 5cm; "> 57 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 18 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 19 </td>
   <td style="text-align:right;font-weight: bold;"> 30 </td>
   <td style="text-align:right;"> 322 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 68 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 19 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 20 </td>
   <td style="text-align:right;font-weight: bold;"> 11 </td>
   <td style="text-align:right;"> 44 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 62 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 20 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 21 </td>
   <td style="text-align:right;font-weight: bold;"> 1 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 59 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 21 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 22 </td>
   <td style="text-align:right;font-weight: bold;"> 11 </td>
   <td style="text-align:right;"> 320 </td>
   <td style="text-align:right;"> 16.6 </td>
   <td style="text-align:right;width: 5cm; "> 73 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 22 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 23 </td>
   <td style="text-align:right;font-weight: bold;"> 4 </td>
   <td style="text-align:right;"> 25 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 61 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 23 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 24 </td>
   <td style="text-align:right;font-weight: bold;"> 32 </td>
   <td style="text-align:right;"> 92 </td>
   <td style="text-align:right;"> 12.0 </td>
   <td style="text-align:right;width: 5cm; "> 61 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 24 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 25 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 66 </td>
   <td style="text-align:right;"> 16.6 </td>
   <td style="text-align:right;width: 5cm; "> 57 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 25 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 26 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 266 </td>
   <td style="text-align:right;"> 14.9 </td>
   <td style="text-align:right;width: 5cm; "> 58 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 26 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 27 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> NA </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 57 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 27 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 28 </td>
   <td style="text-align:right;font-weight: bold;"> 23 </td>
   <td style="text-align:right;"> 13 </td>
   <td style="text-align:right;"> 12.0 </td>
   <td style="text-align:right;width: 5cm; "> 67 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 28 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 29 </td>
   <td style="text-align:right;font-weight: bold;"> 45 </td>
   <td style="text-align:right;"> 252 </td>
   <td style="text-align:right;"> 14.9 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 29 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 30 </td>
   <td style="text-align:right;font-weight: bold;"> 115 </td>
   <td style="text-align:right;"> 223 </td>
   <td style="text-align:right;"> 5.7 </td>
   <td style="text-align:right;width: 5cm; "> 79 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 30 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 31 </td>
   <td style="text-align:right;font-weight: bold;"> 37 </td>
   <td style="text-align:right;"> 279 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 5 </td>
   <td style="text-align:right;"> 31 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 32 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 286 </td>
   <td style="text-align:right;"> 8.6 </td>
   <td style="text-align:right;width: 5cm; "> 78 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 33 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 287 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 74 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 34 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 242 </td>
   <td style="text-align:right;"> 16.1 </td>
   <td style="text-align:right;width: 5cm; "> 67 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 3 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 35 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 186 </td>
   <td style="text-align:right;"> 9.2 </td>
   <td style="text-align:right;width: 5cm; "> 84 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 36 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 220 </td>
   <td style="text-align:right;"> 8.6 </td>
   <td style="text-align:right;width: 5cm; "> 85 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 5 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 37 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 264 </td>
   <td style="text-align:right;"> 14.3 </td>
   <td style="text-align:right;width: 5cm; "> 79 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 38 </td>
   <td style="text-align:right;font-weight: bold;"> 29 </td>
   <td style="text-align:right;"> 127 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 7 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 39 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 273 </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 87 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 40 </td>
   <td style="text-align:right;font-weight: bold;"> 71 </td>
   <td style="text-align:right;"> 291 </td>
   <td style="text-align:right;"> 13.8 </td>
   <td style="text-align:right;width: 5cm; "> 90 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 41 </td>
   <td style="text-align:right;font-weight: bold;"> 39 </td>
   <td style="text-align:right;"> 323 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 87 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 42 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 259 </td>
   <td style="text-align:right;"> 10.9 </td>
   <td style="text-align:right;width: 5cm; "> 93 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 11 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 43 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 250 </td>
   <td style="text-align:right;"> 9.2 </td>
   <td style="text-align:right;width: 5cm; "> 92 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 44 </td>
   <td style="text-align:right;font-weight: bold;"> 23 </td>
   <td style="text-align:right;"> 148 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 45 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 332 </td>
   <td style="text-align:right;"> 13.8 </td>
   <td style="text-align:right;width: 5cm; "> 80 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 14 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 46 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 322 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 79 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 47 </td>
   <td style="text-align:right;font-weight: bold;"> 21 </td>
   <td style="text-align:right;"> 191 </td>
   <td style="text-align:right;"> 14.9 </td>
   <td style="text-align:right;width: 5cm; "> 77 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 16 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 48 </td>
   <td style="text-align:right;font-weight: bold;"> 37 </td>
   <td style="text-align:right;"> 284 </td>
   <td style="text-align:right;"> 20.7 </td>
   <td style="text-align:right;width: 5cm; "> 72 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 17 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 49 </td>
   <td style="text-align:right;font-weight: bold;"> 20 </td>
   <td style="text-align:right;"> 37 </td>
   <td style="text-align:right;"> 9.2 </td>
   <td style="text-align:right;width: 5cm; "> 65 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 18 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 50 </td>
   <td style="text-align:right;font-weight: bold;"> 12 </td>
   <td style="text-align:right;"> 120 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 73 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 19 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 51 </td>
   <td style="text-align:right;font-weight: bold;"> 13 </td>
   <td style="text-align:right;"> 137 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 20 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 52 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 150 </td>
   <td style="text-align:right;"> 6.3 </td>
   <td style="text-align:right;width: 5cm; "> 77 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 21 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 53 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 59 </td>
   <td style="text-align:right;"> 1.7 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 22 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 54 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 91 </td>
   <td style="text-align:right;"> 4.6 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 23 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 55 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 250 </td>
   <td style="text-align:right;"> 6.3 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 24 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 56 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 135 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 75 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 25 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 57 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 127 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 78 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 26 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 58 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 47 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 73 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 27 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 59 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 98 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 80 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 28 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 60 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 31 </td>
   <td style="text-align:right;"> 14.9 </td>
   <td style="text-align:right;width: 5cm; "> 77 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 29 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 61 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 138 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 83 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 30 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 62 </td>
   <td style="text-align:right;font-weight: bold;"> 135 </td>
   <td style="text-align:right;"> 269 </td>
   <td style="text-align:right;"> 4.1 </td>
   <td style="text-align:right;width: 5cm; "> 84 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 63 </td>
   <td style="text-align:right;font-weight: bold;"> 49 </td>
   <td style="text-align:right;"> 248 </td>
   <td style="text-align:right;"> 9.2 </td>
   <td style="text-align:right;width: 5cm; "> 85 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 64 </td>
   <td style="text-align:right;font-weight: bold;"> 32 </td>
   <td style="text-align:right;"> 236 </td>
   <td style="text-align:right;"> 9.2 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 3 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 65 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 101 </td>
   <td style="text-align:right;"> 10.9 </td>
   <td style="text-align:right;width: 5cm; "> 84 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 66 </td>
   <td style="text-align:right;font-weight: bold;"> 64 </td>
   <td style="text-align:right;"> 175 </td>
   <td style="text-align:right;"> 4.6 </td>
   <td style="text-align:right;width: 5cm; "> 83 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 5 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 67 </td>
   <td style="text-align:right;font-weight: bold;"> 40 </td>
   <td style="text-align:right;"> 314 </td>
   <td style="text-align:right;"> 10.9 </td>
   <td style="text-align:right;width: 5cm; "> 83 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 68 </td>
   <td style="text-align:right;font-weight: bold;"> 77 </td>
   <td style="text-align:right;"> 276 </td>
   <td style="text-align:right;"> 5.1 </td>
   <td style="text-align:right;width: 5cm; "> 88 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 7 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 69 </td>
   <td style="text-align:right;font-weight: bold;"> 97 </td>
   <td style="text-align:right;"> 267 </td>
   <td style="text-align:right;"> 6.3 </td>
   <td style="text-align:right;width: 5cm; "> 92 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 70 </td>
   <td style="text-align:right;font-weight: bold;"> 97 </td>
   <td style="text-align:right;"> 272 </td>
   <td style="text-align:right;"> 5.7 </td>
   <td style="text-align:right;width: 5cm; "> 92 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 71 </td>
   <td style="text-align:right;font-weight: bold;"> 85 </td>
   <td style="text-align:right;"> 175 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 89 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 72 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 139 </td>
   <td style="text-align:right;"> 8.6 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 11 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 73 </td>
   <td style="text-align:right;font-weight: bold;"> 10 </td>
   <td style="text-align:right;"> 264 </td>
   <td style="text-align:right;"> 14.3 </td>
   <td style="text-align:right;width: 5cm; "> 73 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 74 </td>
   <td style="text-align:right;font-weight: bold;"> 27 </td>
   <td style="text-align:right;"> 175 </td>
   <td style="text-align:right;"> 14.9 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 75 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 291 </td>
   <td style="text-align:right;"> 14.9 </td>
   <td style="text-align:right;width: 5cm; "> 91 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 14 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 76 </td>
   <td style="text-align:right;font-weight: bold;"> 7 </td>
   <td style="text-align:right;"> 48 </td>
   <td style="text-align:right;"> 14.3 </td>
   <td style="text-align:right;width: 5cm; "> 80 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 77 </td>
   <td style="text-align:right;font-weight: bold;"> 48 </td>
   <td style="text-align:right;"> 260 </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 16 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 78 </td>
   <td style="text-align:right;font-weight: bold;"> 35 </td>
   <td style="text-align:right;"> 274 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 17 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 79 </td>
   <td style="text-align:right;font-weight: bold;"> 61 </td>
   <td style="text-align:right;"> 285 </td>
   <td style="text-align:right;"> 6.3 </td>
   <td style="text-align:right;width: 5cm; "> 84 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 18 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 80 </td>
   <td style="text-align:right;font-weight: bold;"> 79 </td>
   <td style="text-align:right;"> 187 </td>
   <td style="text-align:right;"> 5.1 </td>
   <td style="text-align:right;width: 5cm; "> 87 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 19 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 81 </td>
   <td style="text-align:right;font-weight: bold;"> 63 </td>
   <td style="text-align:right;"> 220 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 85 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 20 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 82 </td>
   <td style="text-align:right;font-weight: bold;"> 16 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 74 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 21 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 83 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 258 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 22 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 84 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 295 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 23 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 85 </td>
   <td style="text-align:right;font-weight: bold;"> 80 </td>
   <td style="text-align:right;"> 294 </td>
   <td style="text-align:right;"> 8.6 </td>
   <td style="text-align:right;width: 5cm; "> 86 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 24 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 86 </td>
   <td style="text-align:right;font-weight: bold;"> 108 </td>
   <td style="text-align:right;"> 223 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 85 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 25 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 87 </td>
   <td style="text-align:right;font-weight: bold;"> 20 </td>
   <td style="text-align:right;"> 81 </td>
   <td style="text-align:right;"> 8.6 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 26 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 88 </td>
   <td style="text-align:right;font-weight: bold;"> 52 </td>
   <td style="text-align:right;"> 82 </td>
   <td style="text-align:right;"> 12.0 </td>
   <td style="text-align:right;width: 5cm; "> 86 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 27 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 89 </td>
   <td style="text-align:right;font-weight: bold;"> 82 </td>
   <td style="text-align:right;"> 213 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 88 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 28 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 90 </td>
   <td style="text-align:right;font-weight: bold;"> 50 </td>
   <td style="text-align:right;"> 275 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 86 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 29 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 91 </td>
   <td style="text-align:right;font-weight: bold;"> 64 </td>
   <td style="text-align:right;"> 253 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 83 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 30 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 92 </td>
   <td style="text-align:right;font-weight: bold;"> 59 </td>
   <td style="text-align:right;"> 254 </td>
   <td style="text-align:right;"> 9.2 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 7 </td>
   <td style="text-align:right;"> 31 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 93 </td>
   <td style="text-align:right;font-weight: bold;"> 39 </td>
   <td style="text-align:right;"> 83 </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 94 </td>
   <td style="text-align:right;font-weight: bold;"> 9 </td>
   <td style="text-align:right;"> 24 </td>
   <td style="text-align:right;"> 13.8 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 95 </td>
   <td style="text-align:right;font-weight: bold;"> 16 </td>
   <td style="text-align:right;"> 77 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 3 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 96 </td>
   <td style="text-align:right;font-weight: bold;"> 78 </td>
   <td style="text-align:right;"> NA </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 86 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 97 </td>
   <td style="text-align:right;font-weight: bold;"> 35 </td>
   <td style="text-align:right;"> NA </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 85 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 5 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 98 </td>
   <td style="text-align:right;font-weight: bold;"> 66 </td>
   <td style="text-align:right;"> NA </td>
   <td style="text-align:right;"> 4.6 </td>
   <td style="text-align:right;width: 5cm; "> 87 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 99 </td>
   <td style="text-align:right;font-weight: bold;"> 122 </td>
   <td style="text-align:right;"> 255 </td>
   <td style="text-align:right;"> 4.0 </td>
   <td style="text-align:right;width: 5cm; "> 89 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 7 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 100 </td>
   <td style="text-align:right;font-weight: bold;"> 89 </td>
   <td style="text-align:right;"> 229 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 90 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 101 </td>
   <td style="text-align:right;font-weight: bold;"> 110 </td>
   <td style="text-align:right;"> 207 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 90 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 102 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 222 </td>
   <td style="text-align:right;"> 8.6 </td>
   <td style="text-align:right;width: 5cm; "> 92 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 103 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 137 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 86 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 11 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 104 </td>
   <td style="text-align:right;font-weight: bold;"> 44 </td>
   <td style="text-align:right;"> 192 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 86 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 105 </td>
   <td style="text-align:right;font-weight: bold;"> 28 </td>
   <td style="text-align:right;"> 273 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 106 </td>
   <td style="text-align:right;font-weight: bold;"> 65 </td>
   <td style="text-align:right;"> 157 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 80 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 14 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 107 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 64 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 79 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 108 </td>
   <td style="text-align:right;font-weight: bold;"> 22 </td>
   <td style="text-align:right;"> 71 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 77 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 16 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 109 </td>
   <td style="text-align:right;font-weight: bold;"> 59 </td>
   <td style="text-align:right;"> 51 </td>
   <td style="text-align:right;"> 6.3 </td>
   <td style="text-align:right;width: 5cm; "> 79 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 17 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 110 </td>
   <td style="text-align:right;font-weight: bold;"> 23 </td>
   <td style="text-align:right;"> 115 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 18 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 111 </td>
   <td style="text-align:right;font-weight: bold;"> 31 </td>
   <td style="text-align:right;"> 244 </td>
   <td style="text-align:right;"> 10.9 </td>
   <td style="text-align:right;width: 5cm; "> 78 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 19 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 112 </td>
   <td style="text-align:right;font-weight: bold;"> 44 </td>
   <td style="text-align:right;"> 190 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 78 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 20 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 113 </td>
   <td style="text-align:right;font-weight: bold;"> 21 </td>
   <td style="text-align:right;"> 259 </td>
   <td style="text-align:right;"> 15.5 </td>
   <td style="text-align:right;width: 5cm; "> 77 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 21 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 114 </td>
   <td style="text-align:right;font-weight: bold;"> 9 </td>
   <td style="text-align:right;"> 36 </td>
   <td style="text-align:right;"> 14.3 </td>
   <td style="text-align:right;width: 5cm; "> 72 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 22 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 115 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 255 </td>
   <td style="text-align:right;"> 12.6 </td>
   <td style="text-align:right;width: 5cm; "> 75 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 23 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 116 </td>
   <td style="text-align:right;font-weight: bold;"> 45 </td>
   <td style="text-align:right;"> 212 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 79 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 24 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 117 </td>
   <td style="text-align:right;font-weight: bold;"> 168 </td>
   <td style="text-align:right;"> 238 </td>
   <td style="text-align:right;"> 3.4 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 25 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 118 </td>
   <td style="text-align:right;font-weight: bold;"> 73 </td>
   <td style="text-align:right;"> 215 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 86 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 26 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 119 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 153 </td>
   <td style="text-align:right;"> 5.7 </td>
   <td style="text-align:right;width: 5cm; "> 88 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 27 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 120 </td>
   <td style="text-align:right;font-weight: bold;"> 76 </td>
   <td style="text-align:right;"> 203 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 97 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 28 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 121 </td>
   <td style="text-align:right;font-weight: bold;"> 118 </td>
   <td style="text-align:right;"> 225 </td>
   <td style="text-align:right;"> 2.3 </td>
   <td style="text-align:right;width: 5cm; "> 94 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 29 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 122 </td>
   <td style="text-align:right;font-weight: bold;"> 84 </td>
   <td style="text-align:right;"> 237 </td>
   <td style="text-align:right;"> 6.3 </td>
   <td style="text-align:right;width: 5cm; "> 96 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 30 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 123 </td>
   <td style="text-align:right;font-weight: bold;"> 85 </td>
   <td style="text-align:right;"> 188 </td>
   <td style="text-align:right;"> 6.3 </td>
   <td style="text-align:right;width: 5cm; "> 94 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 31 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 124 </td>
   <td style="text-align:right;font-weight: bold;"> 96 </td>
   <td style="text-align:right;"> 167 </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 91 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 125 </td>
   <td style="text-align:right;font-weight: bold;"> 78 </td>
   <td style="text-align:right;"> 197 </td>
   <td style="text-align:right;"> 5.1 </td>
   <td style="text-align:right;width: 5cm; "> 92 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 126 </td>
   <td style="text-align:right;font-weight: bold;"> 73 </td>
   <td style="text-align:right;"> 183 </td>
   <td style="text-align:right;"> 2.8 </td>
   <td style="text-align:right;width: 5cm; "> 93 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 3 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 127 </td>
   <td style="text-align:right;font-weight: bold;"> 91 </td>
   <td style="text-align:right;"> 189 </td>
   <td style="text-align:right;"> 4.6 </td>
   <td style="text-align:right;width: 5cm; "> 93 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 128 </td>
   <td style="text-align:right;font-weight: bold;"> 47 </td>
   <td style="text-align:right;"> 95 </td>
   <td style="text-align:right;"> 7.4 </td>
   <td style="text-align:right;width: 5cm; "> 87 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 5 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 129 </td>
   <td style="text-align:right;font-weight: bold;"> 32 </td>
   <td style="text-align:right;"> 92 </td>
   <td style="text-align:right;"> 15.5 </td>
   <td style="text-align:right;width: 5cm; "> 84 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 130 </td>
   <td style="text-align:right;font-weight: bold;"> 20 </td>
   <td style="text-align:right;"> 252 </td>
   <td style="text-align:right;"> 10.9 </td>
   <td style="text-align:right;width: 5cm; "> 80 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 7 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 131 </td>
   <td style="text-align:right;font-weight: bold;"> 23 </td>
   <td style="text-align:right;"> 220 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 78 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 132 </td>
   <td style="text-align:right;font-weight: bold;"> 21 </td>
   <td style="text-align:right;"> 230 </td>
   <td style="text-align:right;"> 10.9 </td>
   <td style="text-align:right;width: 5cm; "> 75 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 133 </td>
   <td style="text-align:right;font-weight: bold;"> 24 </td>
   <td style="text-align:right;"> 259 </td>
   <td style="text-align:right;"> 9.7 </td>
   <td style="text-align:right;width: 5cm; "> 73 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 134 </td>
   <td style="text-align:right;font-weight: bold;"> 44 </td>
   <td style="text-align:right;"> 236 </td>
   <td style="text-align:right;"> 14.9 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 11 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 135 </td>
   <td style="text-align:right;font-weight: bold;"> 21 </td>
   <td style="text-align:right;"> 259 </td>
   <td style="text-align:right;"> 15.5 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 136 </td>
   <td style="text-align:right;font-weight: bold;"> 28 </td>
   <td style="text-align:right;"> 238 </td>
   <td style="text-align:right;"> 6.3 </td>
   <td style="text-align:right;width: 5cm; "> 77 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 13 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 137 </td>
   <td style="text-align:right;font-weight: bold;"> 9 </td>
   <td style="text-align:right;"> 24 </td>
   <td style="text-align:right;"> 10.9 </td>
   <td style="text-align:right;width: 5cm; "> 71 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 14 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 138 </td>
   <td style="text-align:right;font-weight: bold;"> 13 </td>
   <td style="text-align:right;"> 112 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 71 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 15 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 139 </td>
   <td style="text-align:right;font-weight: bold;"> 46 </td>
   <td style="text-align:right;"> 237 </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 78 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 16 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 140 </td>
   <td style="text-align:right;font-weight: bold;"> 18 </td>
   <td style="text-align:right;"> 224 </td>
   <td style="text-align:right;"> 13.8 </td>
   <td style="text-align:right;width: 5cm; "> 67 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 17 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 141 </td>
   <td style="text-align:right;font-weight: bold;"> 13 </td>
   <td style="text-align:right;"> 27 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 18 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 142 </td>
   <td style="text-align:right;font-weight: bold;"> 24 </td>
   <td style="text-align:right;"> 238 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 68 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 19 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 143 </td>
   <td style="text-align:right;font-weight: bold;"> 16 </td>
   <td style="text-align:right;"> 201 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 82 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 20 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 144 </td>
   <td style="text-align:right;font-weight: bold;"> 13 </td>
   <td style="text-align:right;"> 238 </td>
   <td style="text-align:right;"> 12.6 </td>
   <td style="text-align:right;width: 5cm; "> 64 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 21 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 145 </td>
   <td style="text-align:right;font-weight: bold;"> 23 </td>
   <td style="text-align:right;"> 14 </td>
   <td style="text-align:right;"> 9.2 </td>
   <td style="text-align:right;width: 5cm; "> 71 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 22 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 146 </td>
   <td style="text-align:right;font-weight: bold;"> 36 </td>
   <td style="text-align:right;"> 139 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 81 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 23 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 147 </td>
   <td style="text-align:right;font-weight: bold;"> 7 </td>
   <td style="text-align:right;"> 49 </td>
   <td style="text-align:right;"> 10.3 </td>
   <td style="text-align:right;width: 5cm; "> 69 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 24 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 148 </td>
   <td style="text-align:right;font-weight: bold;"> 14 </td>
   <td style="text-align:right;"> 20 </td>
   <td style="text-align:right;"> 16.6 </td>
   <td style="text-align:right;width: 5cm; "> 63 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 25 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 149 </td>
   <td style="text-align:right;font-weight: bold;"> 30 </td>
   <td style="text-align:right;"> 193 </td>
   <td style="text-align:right;"> 6.9 </td>
   <td style="text-align:right;width: 5cm; "> 70 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 26 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 150 </td>
   <td style="text-align:right;font-weight: bold;"> NA </td>
   <td style="text-align:right;"> 145 </td>
   <td style="text-align:right;"> 13.2 </td>
   <td style="text-align:right;width: 5cm; "> 77 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 27 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 151 </td>
   <td style="text-align:right;font-weight: bold;"> 14 </td>
   <td style="text-align:right;"> 191 </td>
   <td style="text-align:right;"> 14.3 </td>
   <td style="text-align:right;width: 5cm; "> 75 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 28 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 152 </td>
   <td style="text-align:right;font-weight: bold;"> 18 </td>
   <td style="text-align:right;"> 131 </td>
   <td style="text-align:right;"> 8.0 </td>
   <td style="text-align:right;width: 5cm; "> 76 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 29 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 153 </td>
   <td style="text-align:right;font-weight: bold;"> 20 </td>
   <td style="text-align:right;"> 223 </td>
   <td style="text-align:right;"> 11.5 </td>
   <td style="text-align:right;width: 5cm; "> 68 </td>
   <td style="text-align:right;"> 9 </td>
   <td style="text-align:right;"> 30 </td>
  </tr>
</tbody>
</table></div>

---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *DT::datatable*

```r
library(DT)

datatable( head(iris))
```

<div id="htmlwidget-a9248159ce804d0c829d" style="width:100%;height:auto;" class="datatables html-widget"></div>
<script type="application/json" data-for="htmlwidget-a9248159ce804d0c829d">{"x":{"filter":"none","vertical":false,"data":[["1","2","3","4","5","6"],[5.1,4.9,4.7,4.6,5,5.4],[3.5,3,3.2,3.1,3.6,3.9],[1.4,1.4,1.3,1.5,1.4,1.7],[0.2,0.2,0.2,0.2,0.2,0.4],["setosa","setosa","setosa","setosa","setosa","setosa"]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>Sepal.Length<\/th>\n      <th>Sepal.Width<\/th>\n      <th>Petal.Length<\/th>\n      <th>Petal.Width<\/th>\n      <th>Species<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"columnDefs":[{"className":"dt-right","targets":[1,2,3,4]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false}},"evals":[],"jsHooks":[]}</script>

---

# <i class="fas fa-table" role="presentation" aria-label="table icon"></i> Tablas *reactable + sparkline*

```r
library(sparkline)
library(reactable)

reactable(
  iris[1:20, ],
  defaultPageSize = 5,
  bordered = TRUE,
  defaultColDef = colDef(footer = function(values) {
    if (!is.numeric(values)) return()
    sparkline(values, type = "box", width = 100, height = 30)
  })
)
```
]

<div id="htmlwidget-7dc500b2e1a897b3523c" class="reactable html-widget" style="width:auto;height:auto;"></div>
<script type="application/json" data-for="htmlwidget-7dc500b2e1a897b3523c">{"x":{"tag":{"name":"Reactable","attribs":{"data":{"Sepal.Length":[5.1,4.9,4.7,4.6,5,5.4,4.6,5,4.4,4.9,5.4,4.8,4.8,4.3,5.8,5.7,5.4,5.1,5.7,5.1],"Sepal.Width":[3.5,3,3.2,3.1,3.6,3.9,3.4,3.4,2.9,3.1,3.7,3.4,3,3,4,4.4,3.9,3.5,3.8,3.8],"Petal.Length":[1.4,1.4,1.3,1.5,1.4,1.7,1.4,1.5,1.4,1.5,1.5,1.6,1.4,1.1,1.2,1.5,1.3,1.4,1.7,1.5],"Petal.Width":[0.2,0.2,0.2,0.2,0.2,0.4,0.3,0.2,0.2,0.1,0.2,0.2,0.1,0.1,0.2,0.4,0.4,0.3,0.3,0.3],"Species":["setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa","setosa"]},"columns":[{"accessor":"Sepal.Length","name":"Sepal.Length","type":"numeric","footer":{"name":"WidgetContainer","attribs":{"key":"b3e092951d01a99b6e825169dfa24c3a"},"children":[{"name":"Fragment","attribs":[],"children":[{"name":"span","attribs":{"id":"htmlwidget-15f9c77f65d131824aef","className":"sparkline html-widget"},"children":[]},{"name":"script","attribs":{"type":"application/json","data-for":"htmlwidget-15f9c77f65d131824aef"},"children":["{\"x\":{\"values\":[5.1,4.9,4.7,4.6,5,5.4,4.6,5,4.4,4.9,5.4,4.8,4.8,4.3,5.8,5.7,5.4,5.1,5.7,5.1],\"options\":{\"type\":\"box\",\"height\":30,\"width\":100},\"width\":100,\"height\":30},\"evals\":[],\"jsHooks\":[]}"]}]}]}},{"accessor":"Sepal.Width","name":"Sepal.Width","type":"numeric","footer":{"name":"WidgetContainer","attribs":{"key":"4c00b11e2050d834874adcc5db1c40c3"},"children":[{"name":"Fragment","attribs":[],"children":[{"name":"span","attribs":{"id":"htmlwidget-4b8227202898ecb9d140","className":"sparkline html-widget"},"children":[]},{"name":"script","attribs":{"type":"application/json","data-for":"htmlwidget-4b8227202898ecb9d140"},"children":["{\"x\":{\"values\":[3.5,3,3.2,3.1,3.6,3.9,3.4,3.4,2.9,3.1,3.7,3.4,3,3,4,4.4,3.9,3.5,3.8,3.8],\"options\":{\"type\":\"box\",\"height\":30,\"width\":100},\"width\":100,\"height\":30},\"evals\":[],\"jsHooks\":[]}"]}]}]}},{"accessor":"Petal.Length","name":"Petal.Length","type":"numeric","footer":{"name":"WidgetContainer","attribs":{"key":"512edbbff0f82586ae7bd8798bae57b5"},"children":[{"name":"Fragment","attribs":[],"children":[{"name":"span","attribs":{"id":"htmlwidget-6efab005c5b880cf54ac","className":"sparkline html-widget"},"children":[]},{"name":"script","attribs":{"type":"application/json","data-for":"htmlwidget-6efab005c5b880cf54ac"},"children":["{\"x\":{\"values\":[1.4,1.4,1.3,1.5,1.4,1.7,1.4,1.5,1.4,1.5,1.5,1.6,1.4,1.1,1.2,1.5,1.3,1.4,1.7,1.5],\"options\":{\"type\":\"box\",\"height\":30,\"width\":100},\"width\":100,\"height\":30},\"evals\":[],\"jsHooks\":[]}"]}]}]}},{"accessor":"Petal.Width","name":"Petal.Width","type":"numeric","footer":{"name":"WidgetContainer","attribs":{"key":"c8048e034d91651f7c871f8608ebd1c4"},"children":[{"name":"Fragment","attribs":[],"children":[{"name":"span","attribs":{"id":"htmlwidget-04267fe82d69632c724d","className":"sparkline html-widget"},"children":[]},{"name":"script","attribs":{"type":"application/json","data-for":"htmlwidget-04267fe82d69632c724d"},"children":["{\"x\":{\"values\":[0.2,0.2,0.2,0.2,0.2,0.4,0.3,0.2,0.2,0.1,0.2,0.2,0.1,0.1,0.2,0.4,0.4,0.3,0.3,0.3],\"options\":{\"type\":\"box\",\"height\":30,\"width\":100},\"width\":100,\"height\":30},\"evals\":[],\"jsHooks\":[]}"]}]}]}},{"accessor":"Species","name":"Species","type":"factor"}],"defaultPageSize":5,"paginationType":"numbers","showPageInfo":true,"minRows":1,"bordered":true,"dataKey":"6270d5ba90e8f4939abc8b8d622bb435","key":"6270d5ba90e8f4939abc8b8d622bb435"},"children":[]},"class":"reactR_markup"},"evals":[],"jsHooks":[]}</script>

---

# <i class="fas fa-dice-d6" role="presentation" aria-label="dice-d6 icon"></i>
# Introducción a `ggplot2`
----

.right[
.bottom[
####  [<i class="far fa-bell" role="presentation" aria-label="bell icon"></i>](#menu)
]
]

---

# <i class="fas fa-dice-d6" role="presentation" aria-label="dice-d6 icon"></i> Introducción a `ggplot2`

**Las funciones del paquete de ggplot2 `library(ggplot2)` crean un gráfico en capas.** Construiremos un gráfico complejo comenzando con un gráfico simple y agregando elementos adicionales, uno a la vez.

> Al construir un gráfico `ggplot2`, solo se requieren las dos primeras funciones que se describen a continuación. Las otras funciones son opcionales y pueden aparecer en cualquier orden.

### 1️⃣ ggplot(): *Siempre debe ser la primera función.*

* `ggplot`: Contiene los datos que se trazarán.
* `mapping`: Se genera el mapeo de las variables a las propiedades visuales del gráfico. Las asignaciones se colocan dentro de la función `aes` (donde **aes** significa estética).

```r
library(ggplot2)

ggplot(data = iris,
       mapping = aes(x = Sepal.Length, y = Petal.Length))
```

.center[
El gráfico se encuentra vacío ya que no hemos declarado forma. Hemos declarado las variables a los ejes.
]

]

![](2_Data_files/figure-html/unnamed-chunk-52-1.png)

]

---

# <i class="fas fa-dice-d6" role="presentation" aria-label="dice-d6 icon"></i> Introducción a `ggplot2`

> Al construir un gráfico `ggplot2`, solo se requieren las dos primeras funciones que se describen a continuación. Las otras funciones son opcionales y pueden aparecer en cualquier orden.

### 2️⃣ geoms(): *Siempre debe ser la segunda función.*

* Los geoms son los objetos geométricos (puntos, líneas, barras, etc.) que se pueden colocar en un gráfico. Se agregan usando funciones que comienzan con `geom_`. Por ejemplo un gráfico de puntos tiene la forma geométrica `geom_point`.

* Lass funciones se encadenan mediante el `+` signo para construir una trama final.

```r
library(ggplot2)

ggplot(data = iris,
       mapping = aes(x = Sepal.Length, y = Petal.Length))+
  geom_point()
```

]

![](2_Data_files/figure-html/unnamed-chunk-54-1.png)

]

---

# <i class="fas fa-dice-d6" role="presentation" aria-label="dice-d6 icon"></i> Introducción a `ggplot2`

### themes

* Podemos ajustar la apariencia del gráfico usando temas. Las funciones del tema (que comienzan con `theme_`) controlan los colores de fondo, las fuentes, las líneas de cuadrícula, la ubicación de las leyendas y otras características del gráfico no relacionadas con los datos.

```r
library(ggplot2)

ggplot(data = iris,
       mapping = aes(x = Sepal.Length, y = Petal.Length))+
  geom_point()+
  theme_minimal()
```

Además de los `theme_` podemos tener múltiples características para mejorar nuestros gráficos, así como formas de contenido. Aquí podemos revisar el 🔗** [CHEAT SHEET de `ggplot2()`](https://www.maths.usyd.edu.au/u/UG/SM/STAT3022/r/current/Misc/data-visualization-2.1.pdf)**

]

![](2_Data_files/figure-html/unnamed-chunk-56-1.png)

]

---

# Gracias!!!

### ¿Preguntas?
]

]

### [www.joaquibarandica.com](https://www.joaquibarandica.com)
<i class="fab fa-twitter" role="presentation" aria-label="twitter icon"></i> jotajb5

<i class="fab fa-github" role="presentation" aria-label="github icon"></i> juniorjb5

<i class="far fa-envelope" role="presentation" aria-label="envelope icon"></i> orlando.joaqui@correounivalle.edu.co

]

----

*Las imágenes utilizadas para ambientar la presentación son de [pixabay](https://pixabay.com/).*  
Sources: [R for the Rest of Us](https://rfortherestofus.com/), Rob Kabacoff