SEASONAL.Rmd

---
title: "SEASONAL"
author: "CHEN RUJIE"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: scroll
    theme: sandstone
---

```{r setup, include=FALSE}
##Loading necessary libraries.=================================================
library(readr)
library(readxl)
library(lubridate)
library(knitr)
library(ggplot2)
library(ggpubr)
library(zoo)
library(mFilter)
library(tsdecomp)
library(timeDate)
library(timeSeries)

##Set chunk options.===========================================================
knitr::opts_chunk$set(echo = FALSE, 
                      warning = FALSE,
                      fig.width = 14,
                      fig.height = 28,
                      fig.keep = "all",
                      fig.show = "hold")

## Setting up Global Enviornment.==============================================
TTS <- new.env() #Enviornment to store variabels.
```


<font size="3">INFO</font>
==================================================

BUILD AT: `r Sys.time()`

All Rights Reserved <br> Rujie Chen <br> 18666712666 <br>

TicTok {.tabset .tabset-pills .tabset-fade}
-------------------------------------

```{r Loading Daily Trading Data}
## Loading All Trading Data preprocessed.======================================
TTS$TD_All <- read_csv("DEEPLEARN/TD_All.csv", 
    col_types = cols(X1 = col_date(format = "%Y-%m-%d")))

TTS$TD_All.df <- as.data.frame(TTS$TD_All,  stringsAsFactors = FALSE)
colnames(TTS$TD_All.df)[1] <- c("Date")
# Let's derive the hpfc of all Trading Data.
TTS$CMS_Daily.index <- read_csv("DailyTDs/ref_TD.csv") # The last 1000 rows of data.
TTS$CMS_Daily.index.df <- as.data.frame(TTS$CMS_Daily.index, stringsAsFactors = FALSE)
TTS$CMS_Daily.df <- TTS$TD_All.df[, c("Date", 
                                    paste0(TTS$CMS_Daily.index.df[1, ], "_hpfc"))]
```

<font size="3">CU RELATED</font>
==================================================

Implement a monthly based change percentage, together with red and green color indicators, firstly to the RUBBER price. \n
DATA in PERCENTAGE(%)

CU RELATED {.tabset .tabset-fade}
-------------------------------------

### COPPER

```{r}
# Import necessary libraries.===================================================

# Creating Functions.===========================================================
# Functions to process data into necessary forms.
seasonalDaproc <- function(dataset.ts, # should be timeseries
                           dataset.index, # indexes of desired targets
                           dataset.suffix){ # exctract relative data.
  dataset.index <- paste(list(dataset.index), list(dataset.suffix), sep = "")
  tmp.a <- which(colnames(dataset.ts) == dataset.index)
  dataset.forProc <- dataset.ts[, tmp.a]
  # Using timeseries library to generate for monthly return.
  dataset.return.ts <- timeSeries::daily2monthly((dataset.forProc))
  tmp.x <- round(log(dataset.return.ts/lag(dataset.return.ts))*100, digits = 4) # Algorithm of return
  colnames(tmp.x) <- paste(list(dataset.index), list(c("_MoM_return")), sep = "")
  dataset.return.ts <- tmp.x
  return(dataset.return.ts)
}

#F Functions to convert data into year-month base table.
seasonalDaconv <- function(dataset.ts){# should be timeseries
  # Create the data.frame to store the data
  # ... with the year as the row, and the month as the columns
  tmp.year.max <- max(year(dataset.ts))
  tmp.year.min <- min(year(dataset.ts))
  tmp.df.col <- seq(tmp.year.min, tmp.year.max)
  tmp.df.row <- seq(1, 12)
  tmp.array <- array(NA, c(length(tmp.df.row), length(tmp.df.col)))
  tmp.df <- data.frame(tmp.array)
  colnames(tmp.df) <- tmp.df.col
  rownames(tmp.df) <- tmp.df.row
  # ... fill the every cell of the data frame with relavent data.
  for(i in 1:length(dataset.ts)){
    tmp.t <- date(dataset.ts)[i]
    tmp.v <- dataset.ts[i]
    if(is.na(tmp.v)){
      next
    }else{
      tmp.t.x <- which(tmp.df.col == year(tmp.t))
      tmp.t.y <- which(tmp.df.row == month(tmp.t))
      tmp.df[tmp.t.y, tmp.t.x] <- tmp.v
    }
  }
  
  tmp.df['AVERAGE'] <- round(rowMeans(tmp.df, na.rm = TRUE), digits = 4)
  returnConverted <- tmp.df
  return(returnConverted)
}

# Functions to plot, it will be easier to change if necessary.
seasonalPlot <- function(dataset.df){ # Require data frame format
  formattable(dataset.df, list(
    "MONTH" = formatter("span", style = x ~ ifelse(x == month.name[month(Sys.Date())], 
                                                   style(color = "black", font.weight = "bold"), 
                                                   style(color = "grey"))),
    '2015' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    '2016' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    '2017' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    '2018' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    '2019' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    '2020' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    '2021' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    '2022' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    '2023' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white"))),
    'AVERAGE' = formatter("span", style = x ~ ifelse(x < 0, 
                                                  style("background-color" = "green", color = "white"), 
                                                  style("background-color" = "red", color = "white")))
  ))
}

# # Try to anaysis the rubber price for trial.==================================
TTS$dataset.ts <- timeSeries(TTS$TD_All.df, charvec = TTS$TD_All.df$Date)
TTS$dataset.index <- c("CU0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### PALMOIL

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("P0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### SOYOIL

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("Y0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### SILVER

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("AG0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### BITUMAN

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("BU0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### ZNIC

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("ZN0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### CORN

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("C0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### ALUMINUM

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("AL0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### RAPESEED MEAL

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("RM0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### SOYMEAL

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("M0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### CF0

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("CF0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

<font size="3">RB RELATED</font>
==================================================

Implement a monthly based change percentage, together with red and green color indicators, firstly to the RUBBER price. \n
DATA in PERCENTAGE(%)

RB RELATED{.tabset .tabset-fade}
-------------------------------------

### REBAR

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("RB0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### HC

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("HC0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### IRONORE

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("I0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### PVC

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("V0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### BITUMAN

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("BU0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### J M

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("JM0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### UREA

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("UR0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### Fiber Glass

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("FG0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### METHY ALCOHOL

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("MA0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### SODIUM ACID

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("SA0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### SUGAR

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("SR0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```



<font size="3">CRUDE AND CHEMICALS </font>
==================================================

Implement a monthly based change percentage, together with red and green color indicators, firstly to the RUBBER price. \n
DATA in PERCENTAGE(%)

CRUDE AND CHEMICALS {.tabset .tabset-fade}
-------------------------------------

### CRUDE

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("CL00Y")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### SCM

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("SCM")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### GOLD

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("AU0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### PATROL GAS

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("PG0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### EB

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("EB0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### FUEL

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("FU0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### PTA

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("TA0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### PP

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("PP0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### LASTIC

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("L0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### PVC

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("V0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### LOW SULFUR FUEL

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("LUM")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### RUBBER

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("RU0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

<font size="3">YIELDS </font>
==================================================

Implement a monthly based change percentage, together with red and green color indicators, firstly to the RUBBER price. \n
DATA in PERCENTAGE(%)

YIELDS {.tabset .tabset-fade}
-------------------------------------

### CN 10yry

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("CN_10yry")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### CN 5yry

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("CN_5yry")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### US 10yry

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("US_10yry")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### UK 10yry

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("UK_10yry")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### GR 10yry

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("GR_10yry")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### AU 10yry

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("AU_10yry")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### 10yr Treasury

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("T00C1")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### 5yr Treasury

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("TF00C1")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

<font size="3">CURRENCY </font>
==================================================

Implement a monthly based change percentage, together with red and green color indicators, firstly to the RUBBER price. \n
DATA in PERCENTAGE(%)

CURRENCY {.tabset .tabset-fade}
-------------------------------------

### USDCNH

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("USDCNH")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### USDX

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("USDX")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### USDJPY

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("USDJPY")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### EURUSD

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("EURUSD")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### GBPUSD

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("GBPUSD")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### AUDUSD

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("AUDUSD")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

<font size="3">OTHERS </font>
==================================================

Implement a monthly based change percentage, together with red and green color indicators, firstly to the RUBBER price. \n
DATA in PERCENTAGE(%)

OTHERS {.tabset .tabset-fade}
-------------------------------------

### A50 INDEX

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("IH00C1")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### CSI300 INDEX

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("IF00C1")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### UK.FTSE

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("FTSE")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### US.SPX500

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("SPX")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```


### Fiber Glass

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("FG0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```

### SODIUM CARBONATE

```{r}
# ...TRY other tagets.
TTS$dataset.index <- c("SA0")
TTS$dataset.suffix <- c("Close")
# Acquire necessary data.
TTS$dataset.Daproc.ts <- seasonalDaproc(TTS$dataset.ts, TTS$dataset.index, TTS$dataset.suffix)

# Covert the dataset into year~month base table framework and statistic calculate
TTS$dataset.Converted.df <- seasonalDaconv(TTS$dataset.Daproc.ts)

# # plot out the table with gradient color.=====================================
# ...Try formattable package
library(formattable)
toPlot.ft.df <- TTS$dataset.Converted.df
# ...Adjust the table for plot
toPlot.ft.df <- cbind(data.frame(month.name), toPlot.ft.df)
colnames(toPlot.ft.df)[1] <- "MONTH"
seasonalPlot(toPlot.ft.df)
```