R_icd-data.Rmd

---
title: 'R Package: icd.data'
author: "me of course"
subtitle: plotting
output: pdf_document
---
```{r}
getwd()
```
```{r}
setwd("/Users/zanedax/Documents/R_")
```
# ICD data

# import library
```{r}
library(icd.data)
```

# list the data chapters
```{r Chapters of dataset}
ls_icd_data()
```


# Plotly 
```{r Plotly}
library(plotly)
fig <- plot_ly(midwest, x = ~percollege, color = ~state, type = "box")
fig
```


# Scatterplot
```{r scatterplot}
library(plotly)

data <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv")

fig <- plot_ly(data, x = ~Women, y = ~Men, text = ~School, type = 'scatter', mode = 'markers',
        marker = list(size = ~Gap, opacity = 0.5,
                      color = 'rgb(255, 65, 54)'))
fig <- fig %>% layout(title = 'Gender Gap in Earnings per University',
         xaxis = list(showgrid = FALSE),
         yaxis = list(showgrid = FALSE))

fig
```

# mapping a color for continuous data variable
```{r continuous variable}
library(plotly)

data <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv")

fig <- plot_ly(data, x = ~Women, y = ~Men, text = ~School, type = 'scatter', mode = 'markers', color = ~Gap, colors = 'Reds',
        marker = list(size = ~Gap, opacity = 0.5))
fig <- fig %>% layout(title = 'Gender Gap in Earnings per University',
         xaxis = list(showgrid = FALSE),
         yaxis = list(showgrid = FALSE))

fig
```


# mapping for a categorical variable
```{r mapping categorical}
library(plotly)

data <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv")

data$State <- as.factor(c('Massachusetts', 'California', 'Massachusetts', 'Pennsylvania', 'New Jersey', 'Illinois', 'Washington DC',
                          'Massachusetts', 'Connecticut', 'New York', 'North Carolina', 'New Hampshire', 'New York', 'Indiana',
                          'New York', 'Michigan', 'Rhode Island', 'California', 'Georgia', 'California', 'California'))

fig <- plot_ly(data, x = ~Women, y = ~Men, text = ~School, type = 'scatter', mode = 'markers', size = ~Gap, color = '~State', colors = 'Paired',
        marker = list(opacity = 0.5, sizemode = 'diameter'))
fig <- fig %>% layout(title = 'Gender Gap in Earnings per University',
         xaxis = list(showgrid = FALSE),
         yaxis = list(showgrid = FALSE),
         showlegend = FALSE)

fig
```




# text over bubbles
```{r bubble text}
library(plotly)

data <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv")

data$State <- as.factor(c('Massachusetts', 'California', 'Massachusetts', 'Pennsylvania', 'New Jersey', 'Illinois', 'Washington DC',
                          'Massachusetts', 'Connecticut', 'New York', 'North Carolina', 'New Hampshire', 'New York', 'Indiana',
                          'New York', 'Michigan', 'Rhode Island', 'California', 'Georgia', 'California', 'California'))

fig <- plot_ly(data, x = ~Women, y = ~Men, type = 'scatter', mode = 'markers', size = ~Gap, color = ~State, colors = 'Paired',
        sizes = c(10, 50),
        marker = list(opacity = 0.5, sizemode = 'diameter'),
        hoverinfo = 'text',
        text = ~paste('School:', School, '<br>Gender Gap:', Gap))
fig <- fig %>% layout(title = 'Gender Gap in Earnings per University',
         xaxis = list(showgrid = FALSE),
         yaxis = list(showgrid = FALSE),
         showlegend = FALSE)

fig
```



# 2d plot
```{r 2d plot}
library(plotly)
f <- list(
  family = "Courier New, monospace",
  size = 28,
  color = "#7f7f7f"
)
x <- list(
  title = "x Axis",
  titlefont = f
)
y <- list(
  title = "y Axis",
  titlefont = f
)
fig <- plot_ly(x = ~rnorm(10), y = ~rnorm(10), mode = "markers")
fig <- fig %>% layout(xaxis = x, yaxis = y)

fig
```


# simple bar chart
```{r bar chart}
library(plotly)

fig <- plot_ly(
  x = c("giraffes", "orangutans", "monkeys"),
  y = c(20, 14, 23),
  name = "SF Zoo",
  type = "bar",
  color = "pink"
)

fig
```


# Grouped bar chart
```{r grouped bar chart}
library(plotly)

Animals <- c("giraffes", "orangutans", "monkeys")
SF_Zoo <- c(20, 14, 23)
LA_Zoo <- c(12, 18, 29)
data <- data.frame(Animals, SF_Zoo, LA_Zoo)

fig <- plot_ly(data, x = ~Animals, y = ~SF_Zoo, type = 'bar', name = 'SF Zoo')
fig <- fig %>% add_trace(y = ~LA_Zoo, name = 'LA Zoo')
fig <- fig %>% layout(yaxis = list(title = 'Count'), barmode = 'group')

fig
```