Tt1

03-cleaning.Rmd

@@ -115,17 +115,19 @@ for (i in 16:nrow(USDT)){
 
 ## Combine All the Value into One table
 
-Finally, we combine the volatility, return, and market capitalization with the df.close1, creating the final table df.cryto
+Finally, we combine the volatility, return, and market capitalization and volume with the df.close1, creating the final table df.crpyto
 
 ```{r}
 df.close1$Date<-rep(df.close$Date,5)
-df.cryto<-
+df.crpyto<-
   cbind(df.close1,
         market_cap=c(BTC$market_cap,BNB$market_cap,ETH$market_cap,
                      USDC$market_cap,USDT$market_cap),
         return=c(BTC$Return,BNB$Return,ETH$Return,USDC$Return,USDT$Return),
-        volatility=c(BTC$Vol,BNB$Vol,ETH$Vol,USDC$Vol,USDT$Vol))
-
+        volatility=c(BTC$Vol,BNB$Vol,ETH$Vol,USDC$Vol,USDT$Vol),
+        volumn=c(BTC$total_volume,BNB$total_volume,ETH$total_volume,
+                     USDC$total_volume,USDT$total_volume))
+df.crpyto$Date<-as.Date(df.crpyto$Date)
 ```
 
 

05-results.Rmd

@@ -1,4 +1,5 @@
 # Results
+
 ```{r}
 ggplot(df.close1, aes(price)) + 
   geom_boxplot() + coord_flip() + 
@@ -11,3 +12,21 @@ ggplot(df.close1, aes(price)) +
 plot(df.close[,2:6],pch=20, cex=0.1)
 ```
 
+```{r}
+## plot volatility by crypto
+ggplot(df.crpyto, aes(x=Date,y=volatility))+
+  geom_line()+
+  facet_wrap(~cryptocurrency,scales = "free")
+
+
+```
+
+```{r}
+## plot volatility vs market capitalization
+ggplot(df.crpyto, aes(x=market_cap,y=volatility))+
+  geom_point(pch=5, cex=0.2)+
+  facet_wrap(~cryptocurrency, scales = "free")
+```
+
+
+